Graduate Faculty

Dr. Apostolos Georgopoulos (Professor of Neuroscience, Neurology, and Psychiatry)
There are three major goals of our research: First, to elucidate the neural mechanisms underlying motor control and cognitive processing; second, to develop functional brain biomarkers for various brain diseases and third, to understand the workings of developing cortical networks. For the first aim, we pursue experimental psychological studies, neurophysiological recordings, functional magnetic resonance imaging (MRI) at high fields (3, 4 and 7 Tesla), magnetoencephalography (MEG) and neural network modeling (using a supercomputer). For the second aim, we use MEG. And for the third aim, we record electrical activity from embryonic cortical cell cultures using multielectrode arrays.

Claudia Neuhauser
Yuan-Ping Pang
David I Smith
Tim Starr

Dr. Ann Bode (Research Associate Professor and Associate Director, Cellular and Molecular Biology, Hormel Institute)
Research focuses on identifying molecular targets of dietary factors applied to signal transduction pathways involved in neoplastic cell transformation and carcinogenesis. A major goal is to elucidate key protein-protein or protein-molecular interactions predicted through computer simulation methods and validated through laboratory bench studies to be used in the development of small molecule inhibitors that specifically target key cancer-related proteins.

Dr. Robert Clarke (Professor of Biochemistry, Molecular Biology and Biophysics, Hormel Institute)

Breast cancer is the most common cancer diagnosed in women (over 280,000 new cases in the US every year and over 43,000 deaths). The most prevalent subgroup of breast cancer (~70%) expresses the estrogen receptor (ESR1; ER). The Clarke laboratory takes an integrative, systems-based approach to understanding how breast cancer cells that express ER acquire resistance to ER-targeted therapies including antiestrogens and aromatase inhibitors. We collect data from human breast cancer specimens, rodent models and cell lines using both omics-based and cell and molecular biology methods to collect data for modeling (prediction) and validation (mechanistic wet laboratory studies). Studies are designed around and data are interpreted, in the context of an integrative modeling framework currently comprised of 5 functional modules (autophagy, cell death, cell metabolism, proliferation, unfolded protein response). The signaling underlying these modules is integrated (shared nodes and/or edges) and coordinated (timing) where the output from one module may serve as the input for another. Modeling uses computational tools to study high dimensional data and mathematical modeling of low dimensional data to predict topological features of each module and their integration and coordination with other modules. Modeling is further supported by new tools and workflows that we develop with our collaborators.

Dr. Bin Liu (Assistant Professor of Transcription and Gene Regulation, Hormel Institute)

Research in Dr. Bin Liu’s lab mainly focuses on two fields: (i) bacterial transcription and its regulation, and (ii) structural and mechanistic study of macromolecular complexes in SARS-CoV-2. The proposed projects in the lab are to investigate the structure and mechanism of bacterial transcription and its regulation by various transcription factors, to characterize the molecular mechanisms of how SARS-CoV-2 functions and to identify effective nanobodies or small molecules to inhibit virus by obtaining and characterizing structures of critical complexes involved in these processes using cryo-Electron Microscopy, X-ray crystallography and relevant biochemical experiments.

Dr. Rebecca Morris (Professor, Laboratory on Stem Cells and Cancer, Hormel Institute)
Research in the Morris laboratory focuses on Stem Cells and Cancer, particularly hair follicle stem cells and skin cancer. We have three projects in progress. First, we are identifying novel keratinocyte stem cell regulatory genes using traditional forward genetics in conjunction with reverse approaches such as RNA Seq and statistical genetics. Second, we are studying what seems to be a surprising new behavior for hair follicle stem cells related to non-melanoma skin cancer. Third, we are investigating the role of bone marrow derived epithelial cells in cutaneous carcinogenesis. We anticipate that our discoveries will bring new light to the roles played by stem cells in carcinogenesis.

Dr. Chuanhe Yu (Assistant Professor of Inheritance of Epigenetic Information, Hormel Institute)

During DNA replication process, both genetic (DNA sequence) and epigenetic (chromatin structure) information is duplicated. Proper chromatin replication plays a critical role in cellular differentiation and development. We are interested in the mechanisms controlling this epigenetic inheritance process. We use the genetic, biochemical and bioinformatic computational approaches in our laboratory. 

Dr. John Eberhard (Software Engineer, Java Data Access)

Dr. George Paulik (VLSI Circuit Design Engineer)
My interests are mathematical in nature and I would be more than willing to work with research groups that might benefit from a mathematical/statistical perspective. Most recently, I have been applying statistical techniques to model the yield of arrays (memory structures) in VLSI chips. I also help design VLSI circuits.

Dr. Alexej Abyzov (Professor of Biomedical Engineering and Associate Professor of Medicine, Mayo Clinic)
Research in our laboratory is focused on the discovery and analysis of genomic variants and their relevance to diseases. Of particular interest are large variants, such as deletions and duplications of thousands and millions of nucleotides in individual genomes. Special emphasis is on the discovery and analysis of somatic variants — those originating in human cells during their life span — as these can cause cancer and various diseases.

Focus areas: (i) genomic variant discovery from sequencing; (ii) prediction of variant function and impact; (iii) somatic variations and single cell genomics; (iv) cancer genomics. The ability to discover, predict and interpret the effects of genomic variants allows for personalized medical treatment, which in turn makes disease management more effective and less disturbing for a patient (for example, in the treatment of cancer). The goal of our research is to advance the understanding of genomic variants to such a degree, that it would allow for proactively identifying individual genetic risks in various diseases, monitoring these risks during the entire life of each patient and improving therapy.

Dr. Azra Alizad (Professor of Biomedical Engineering, Department of Radiology and Associate Professor of Medicine, Mayo Clinic)
Dr. Alizad’s research interest is applications of ultrasound-based methodologies for assessment of diseased tissues. Lesion stiffness has been recognized as an important factor in differentiating between malignant and benign masses. Based on this fact, Dr. Alizad’s research includes medical applications of ultrasound radiation force for imaging and characterization of biological materials and evaluation of tissue viscoelasticity. In particular, her research focus includes in vivo human studies on breast cancer imaging, characterization of breast masses, thyroid nodule characterization and differentiation, lymph node characterization and identification of metastatic nodes and quantitative assessment of bone by ultrasound methods (osteopenia prematurity, adult osteoporosis, bone fracture monitoring).

Dr. Shivaram Poigai Arunachalam (Assistant Professor of Radiology and Assistant Professor of Cardiovascular Medicine, Mayo Clinic)
Dr. Poigai Arunachalam’s research focuses on the development of novel physiologically consistent signal processing techniques of biomedical signals for accurate prognosis and diagnosis of variety of diseases with over 15 years of experience. Particular applications focus on the use of electrocardiogram (ECG), phonocardiogram (PCG) and seismocardiogram (SCG) signals for reliable diagnosis of variety of cardiac diseases. Dr. Poigai Arunachalam research also focuses on developing technology for non-invasive cardiac electrophysiological mapping of arrhythmogenic active substrates that causes and maintains several arrhythmias such as atrial fibrillation (AF), ventricular tachycardia (VT), ventricular fibrillation (VF) etc. as potential targets for cardiac ablation therapy.  Additional research areas include development of non-targeted serum protein fingerprinting approach for characterizing variety of cardiac diseases, development of flexible, stretchable and wireless electronic patch sensors for screening and monitoring variety of cardiac diseases, cardiac medical devices development and  cardiac informatics.

Dr. Jun Chen (Assistant Professor of Biostatistics, Mayo Clinic)
Dr. Chen's research lies in the area of statistical genetics and genomics. He is interested in the development and application of powerful and robust computational and statistical methods for high-dimensional genetic, genomic and particularly metagenomic data analysis. His statistical methodology research is mainly on high-dimensional statistics, nonparametric statistics and kernel methods.

Dr. Surendra Dasari (Assistant Professor of Medical Informatics)
The research interests of Surendra Dasari, Ph.D., are in the development and application of bioinformatics methods to solve problems in the areas of clinical molecular diagnostics, cancer proteogenomics, metabolomics and systems biology.

Dr. David Dingli (Professor of Medicine, Senior Associate Consultant Hematology and Molecular Medicine)
Dr Dingli's laboratory studies the use of replication competent viruses for cancer therapy. One of the major goals is to understand the dynamic interactions between tumor, virus and immune cell populations and how these impact the therapeutic outcome. A secondary aim is to develop approaches for optimization of cancer therapy with these viruses. Another major focus of research is to understand the dynamics of normal and cancer stem cells and hematopoiesis. This modeling is applied to various hematologic disorders to understand their dynamics and evolution before and during therapy.

Dr. Jungwei (Fred) Fan (Assistant Professor, Department of Artificial Intelligence & Informatics, Mayo Clinic)
Dr. Fan’s overall interest is in translating data-driven solutions to clinical practice and collaterally generating reusable knowledge from clinical practice. His current research agenda is to detect, characterize, explain, prevent and exploit medical practice variation. Specific topics include: 1) using electronic health records to detect and characterize practice variation in clinical assessment, diagnosis and treatment, 2) applying natural language processing to identify reasons for practice variation or care disruption mentioned in clinical notes, 3) implementing informatics solutions to prevent unwarranted variation or to promote variation that is supported by empirical/vetted knowledge.

Dr. Mostafa Fatemi (Professor of Biomedical Engineering)
Dr. Fatemi is interested in noninvasive methods for studying biological tissues. His research includes applications of sound, ultrasound, and mechanical vibration for imaging and quantitative evaluation of tissues. In particular, he is interested in developing multi-dimensional parameter space for detection and diagnosis of pathologies in various organs.

Dr. Robert Freimuth (Assistant Professor of Medical Informatics)
Dr. Freimuth's research includes designing scalable and semantically interoperable systems that are based on standardized ontologies and terminologies, information models and structured data elements. These systems are essential for integrating the large data sets and diverse knowledge bases that form the foundations of personalized medicine. Dr. Freimuth is exploring methods for integrating genomic data into the Mayo Clinic electronic medical record (EMR) and developing clinical decision-support tools that enable physicians to understand and make use of a patient's unique genomic data. The initial focus of his work is in the area of cancer pharmacogenomics, currently one of the most promising applications of genome-guided therapy.

Dr. Steven Hart (Assistant Professor of Biomedical Informatics, Department of Health Sciences Research)
As a faculty member in the Department of Laboratory Medicine and Pathology and the Division of Computational Pathology and Artificial Intelligence, Dr. Hart leads the development of computational infrastructure to support digital and computational pathology.  His overarching goal is to transform the qualitative field of pathology into a quantitative one. This would facilitate applications of artificial intelligence that could improve the quality of diagnosis, prognosis and theragnosis far beyond the walls of Mayo Clinic. Dr. Hart works extensively in big-data fields such as genomic and whole slide imaging, focusing on how to extract relevant bits of data from massive semi-instructured troves. He is an expert in technical systems, architecture and artificial intelligence.

Dr. David Holmes III ( Associate Professor of Biomedical Engineering, Mayo Clinic)
David R. Holmes III, Ph.D., studies the methods by which health care researchers analyze and interpret large data sets. Health-related data is constantly being collected through the digitalization of medical records and the concordant interest in personal health monitoring. Because of this wealth of information, health care data makes up significant sectors of the big data industry, including in-hospital sensing, clinical reporting, medical imaging and home-based wellness.  Research into data representation, signal processing, graph analytics and machine learning is yielding new and novel insight into basic biology and human health. To match the complexity of these algorithms and the magnitude of data, Dr. Holmes also studies the mapping of health care questions onto novel computational architecture.

Dr. Ming Huang (Assistant Professor of Artificial Intelligence and Informatics)
Dr. Huang’s research interests are largely direct toward the intersection of computer science, data science and health science. His current research focuses on: (1) developing advanced machine learning and natural language processing methods for healthcare applications (2) mining various health data such as electronic health records, patient portal messages, and social media posts to understand patient preferences, needs and values for patient-centered care (3) Creating digital health tools and solutions to advance mental health, rural health and telehealth.

Dr. Nuri Firat Ince (Professor of Biomedical Engineering and Neurosurgery, Mayo Clinic)

Nuri F. Ince, Ph.D., studies basic and translational research in Neural Engineering and Brain Machine Interfaces. New algorithms and machine learning techniques are cultivated in Dr. Ince's Clinical Neural Engineering Lab (CNEL), particularly focusing on exploring large-scale neural activity recorded in clinical settings. The research not only contributes to the development of algorithms and AI tools but also focuses on uncovering new methods and patterns for diagnosis and therapy applicable in clinical practice. In this scheme, close collaboration is maintained with clinicians and researchers from diverse fields such as neurosurgery, neurology and neuroscience.

Close ties to other medical institutions, including Baylor College of Medicine, Department of Neurosurgery and Department of Neurology, MD Anderson Cancer Center and Texas Children's Hospital, are maintained by the laboratory. Dr. Ince's laboratory is uniquely positioned to promote clinical translation.

Focus areas

• Neuro-biomarker discovery for closed-loop deep brain stimulation (DBS) in movement disorders.
• Computational intelligence in neurology and epilepsy.
• Decoding oscillatory neural dynamics of complex hand function for closed-loop brain machine interfaces.

Dr. Krishna Kalari (Associate Professor of Medical Informatics, Mayo Clinic College of Medicine)
Dr. Kalari has nine years of research experience in high throughput experimental methods and analytical techniques to identify pathways associated with disease and individual variation to drug response phenotypes. The need to develop novel computational methods is primarily based on the latest high-throughput tools available to address scientific questions. Her research focuses on developing novel methods to integrate multilayer omics data from a variety of next generation sequencing or genome-wide experiments to understand pathophysiological mechanisms of cancer or variation to drug response.

Dr. Eric Klee (Consultant, Division of Computational Biology, Department of Quantitative Health Sciences
The research interests of Eric W. Klee, Ph.D., are divided primarily between two major areas. First, with the Center for Individualized Medicine and the Department of Laboratory Medicine and Pathology, he leads the bioinformatics initiative centered on discovering how clinicians can apply information gathered from molecular-level data to diagnose and treat individual medical conditions. Second, Dr. Klee is a member of the Mayo Addiction Research Center, where he leads a laboratory team using zebrafish as models to identify novel therapeutic strategies for treating alcohol abuse and tobacco dependence.

Focus areas:
Clinical genomic sequencing laboratory. As co-director of Mayo Clinic's clinical next-generation sequencing laboratory, Dr. Klee conducts research focused on bioinformatics to support clinical test development, implementation, quality control and results interpretation.

Individualized medicine clinic. Dr. Klee is developing bioinformatics analytic methods to support "n-of-1" testing for two clinical service lines: late-stage, refractory tumor sequencing for assisting in therapeutic decision-making and pedigree-driven exome sequencing for identification of undiagnosed genetic disease.

Functional validation of genetic loci using zebrafish. Exome sequencing has enabled the identification of putative causal variants for an increasing number of undiagnosed diseases. This study is focused on using transcriptor activator-like effector nuclease (TALEN)-based gene knockout and single-base substitution technology to functionally validate these genetic loci in vivo.

Translational research for novel therapeutic strategies in addiction. Research in this area involves the use of preclinical zebrafish models to study tobacco and alcohol abuse with the objective of identifying novel pharmacotherapeutics for treatment and genetic modifiers of treatment. Dr. Klee places a strong emphasis on drug repurposing to expedite translation to clinical practice.

Dr. Timothy Kline (Assistant Professor, Radiology, Mayo Clinic)
The research of Dr. Timothy Kline focuses on the development of novel image acquisition and image processing techniques to study disease processes and improve patient care. Dr. Kline is actively developing algorithms to automate image analysis methods (e.g., segmentation of organs and lesions) and is searching for new imaging biomarkers of disease through both the development of new image acquisition protocols (e.g., new MR imaging pulse sequences) and analysis techniques (e.g., texture analysis, machine learning and deep learning).

Dr. Jean-Pierre Kocher (Professor of Biomedical Informatics, Division of Biomedical Informatics)
My research interest is in the domain of life science informatics. More specifically, my research activities focus on the development and application of computational methods to advance the understanding of molecular mechanisms that underlie clinical disorders. These methods span the areas of bioinformatics, computational biology and chemoinformatics.

Dr. Nicholas Larson (Associate Professor, Department of Biostatistics, Mayo Clinic)
Dr. Larson's research interests are ultimately orientated to furthering the understanding, prediction and prevention of common complex diseases through the use of high-dimensional molecular and/or EHR data sets. Analyses that uncover genetic factors associated with disease risk, prognosis and treatment response provide additional information on relevant biological mechanisms and may lead to new strategies for patient risk stratification and individualized therapies.  Specific application areas include pharmacogenomics, multi-omics data integration, EHR-based epidemiology and machine learning and radiomics.

Dr. Hu Li (Associate Professor, Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic)
Hu Li, Ph.D. and his research team are focused on systems biology, systems pharmacology and individualized systems medicine. Li's team is active in developing novel network tools and harnessing machine learning methods to study context-dependent activities of regulatory networks at genome-wide scale. The major theme in the research team is to develop novel computational methods that can detect meaningful biological information embedded in the sea of Big Data and uncover novel regulatory mechanisms that explain the properties of biological phenotypes to benefit individualized disease diagnosis, drug discovery and precision medicine. The developed computational platforms can greatly illuminate the understanding of disease mechanisms underlying drugs' modes of action, addressing key challenges in Big Data-oriented biomedical complex systems and will ultimately lead to precision medicine for each patient suffering from a devastating disease. His team is currently working on ways to elucidate how regulatory networks that constitute a constellation of genes drive disease formation and progression in different individual patients to provide novel perspective in designing network-based treatments to realize translational individualized precision medicine.

Dr. Armando Manduca (Professor of Radiology, Associate Professor of Biophysics, Professor of Biomedical Engineering)
Dr. Manduca's research interests involve all aspects of medical imaging, from image reconstruction to image processing and analysis and have spanned many modalities. Recent work has focused on compressive sensing and low-rank image reconstruction methods for undersampled MRI acquisitions, image denoising in MRI, CT and molecular breast imaging and analysis and inversion of magnetic resonance elastography (MRE) data.

Dr.  Devin Oglesbee (Associate Professor of Laboratory Medicine And Pathology; Associate Professor of Medical Genetics,  Mayo Clinic)
The research activities of Devin Oglesbee, Ph.D., center on translational applications in diagnostics for the laboratory detection of inborn errors of metabolism and rare mitochondrial disorders. Particular areas of interest include developing new clinical assays and characterizing biomarkers for rare genetic disorders; developing new methodologies for improving and expanding newborn screening for genetic conditions and organizing infrastructure, such as Mayo Clinic's Mitochondrial Disease Biobank, in order to expedite the progression of genetic research from bench to bedside.

Dr. Laura Rogers (Assistant Professor of Immunology)
The laboratory of Laura M. Rogers, Ph.D., M.S., studies cancer immunotherapy with an emphasis on understanding genetic determinants of immune cell infiltration into the tumor microenvironment. Dr. Rogers’ laboratory utilizes the Sleeping Beauty transposon system and bioinformatics approaches to identify novel molecular players in immune infiltration and then works to understand the biology and therapeutic potential of these candidates using in vivo preclinical models and in vitro approaches.

Focus areas:

Regulation of T cell trafficking into the tumor microenvironment. T cell presence in the tumor microenvironment is governed by diverse cellular processes. The lab has recently identified a number of T cell genes that influence their intratumoral accumulation by regulating surface protein expression and distribution (e.g. chemokine receptors), cellular metabolism and viability. The lab is currently investigating how perturbation of these impacts tumor growth and intratumoral trafficking of endogenous and adoptively transferred T cells. Genomics and bioinformatics to understand cancer immunotherapy response. A majority of cancer patients exhibit primary or acquired resistance to immunotherapy. A large amount of genomic sequence data is being generated to understand the complex biological mechanisms that contribute to response or resistance to improve therapies and develop biomarkers for response. Dr. Rogers’ lab also utilizes forward genetic screens to complement these studies and identify molecules that functionally contribute to varied aspects of an antitumor immune response.

Significance to patient care:

Many cancer immunotherapies that focus on enhancing cytotoxic T cell activity (e.g. CAR-T and checkpoint blockade) require T cells to be present intratumorally. Cancer patients lacking T cells in their tumors are less likely to respond to T cell mediated immunotherapies, including CAR-T cell adoptive transfer and immune checkpoint blockade. Our lab aims to identify novel strategies to enhance intratumoral T cell accumulation, with the goal of improving immunotherapy success in patients with poorly infiltrated tumors.

Dr. Susan Slager (Professor of Biostatistics, Department of Health Sciences Research, Mayo Clinic)
Dr. Slager’s research focuses on the investigation of the inherited genetic basis of lymphoma, including chronic lymphocytic leukemia, non-Hodgkin’s lymphoma, multiple myeloma and Hodgkin’s lymphoma. Dr. Slager leads the Mayo Clinic B-cell lymphoma family registry, in which more than 500 families (including relatives) have consented to participate. These families are followed over time to better understand why relatives from these families have a higher risk of lymphoma (regardless of lymphoma subtype) than that observed in the general population. Dr. Slager is also leading new efforts to combine data across 11 cancers at Mayo Clinic to facilitate across-cancer (pancancer) studies. By building this resource, Dr. Slager and colleagues will be able to evaluate risk factors that are common across cancers, as well as understand commonalities that affect cancer prognosis and patient-reported outcomes.

Dr. Carlos Sosa (Sr. Analyst, Programmer)
Dr Sosa's research is in the area of RNA-Seq to study different types of cancer using solid and liquid biopsies, in particular, to determine gene and transcript expression. The procedure to carry out this type of study requires the use of genomic pipelines, which involve starting with fragments of cDNA obtained from the sequencing machine and running them through a series of applications or genomics tools until results are obtained. Dr Sosa's research involves the application of RNA-Seq to help develop prognostic and screening models based on gene expression to study different types of cancer. In addition, in liquid biopsies is important to understand the different cellular components in the blood. This research also looks at computational techniques that can help quantify different cellular components in the blood.

Dr. Jaeyun Sung (Assistant Professor, Department of Surgery, Mayo Clinic)
Dr. Sung leads the Microbiome Systems Medicine Group, a computational biology laboratory that investigates the role of the gut microbiome in various autoimmune diseases. For our research, we mainly use principles and tools from bioinformatics, network science and machine-learning to analyze large-scale omics datasets (e.g. microbiome, metabolomics, immune profiles, transcriptomics and imaging data) to get a holistic overview of the microbiome and the host (along with their interactions) in the context of autoimmunity. These approaches are then applied to the following directions: i) Omics data analysis on biospecimens derived from the clinical practice at Mayo Clinic; ii) Examining the bacterial and viral microbiome in autoimmune disease; iii) Translational bioinformatics for clinical biomarker discovery for novel diagnostics and prognostics; iv) Modeling gut microbial community-level metabolism and ecological dynamics and v) Multi-omics systems biology and integrative network modeling. Overall, we aim to advance precision/personalized medicine, develop systems-level models of disease and design strategies for probiotic interventions. To read more about our lab, please visit: www.sung-lab.org.

Dr. Joshua Trzasko (Assistant Professor of Biomedical Engineering, Mayo Clinic)
Dr. Trzasko's research focuses on the development of novel mathematical and computational tools for medical imaging, predominantly for magnetic resonance imaging (MRI). His primary areas of focus include fast imaging methods (e.g., sparse and low-rank reconstructions), robust artifact correction strategies (e.g., off-resonance and concomitant field models) and techniques for improving the accuracy and precision of quantitative MRI applications (e.g., perfusion, MR elastography). Additionally, Dr. Trzasko is interested in the core development of modern signal processing theory.

Dr. Matthew W. Urban (Associate Professor of Biomedical Engineering)
Dr. Urban research interests lie in the field of medical imaging, particularly in the area of ultrasound radiation force imaging. He is interested in applying shear wave-based methods to characterize the viscoelastic material properties of different soft tissues. He is also interested in signal processing as it pertains to motion detection for elasticity imaging, ultrasound image formation and measurements using ultrasound imaging technology.

Dr. George Vasmatzis (Assistant Professor, Laboratory Medicine)
Dr. Vasmatzis' research interests are in theoretical and experimental oncology. He applies computational and experimental tools to generate, analyze and interpret genomics data with the intention to understand disease progression and develop predictive models for cancer prognostics and diagnostics. This is accomplished by setting multidisciplinary clinician/scientist teams that span Bioinformatics, Molecular Biology, clinical oncology and Anatomic Pathology.

Dr. Chen Wang (Assistant Professor of Biomedical Informatics, Mayo Clinic)
The research interests of Dr. Wang lie in developing and applying bioinformatics and computational tools to make disease-related discoveries from big molecular data and advance next-generation sequencing-based translational applications. With close interactions with basic science and clinical investigators, Dr. Wang has been mainly active in three focused research areas: (1) next generation sequencing-based detections of structural variations and copy number changes; (2) discovery and validation of molecular subtypes for precision medicines in gynecological cancers (e.g. ovarian and uterine cancers); (3) integrative data-mining to identify dysregulated pathways and reveal functional mechanisms across human diseases.

Dr. Liguo Wang (Associate Professor of Biomedical Informatics, Mayo Clinic)

• Develop bioinformatics tools and analytic approaches to analyze next-generation sequencing data including genomic, epigenomic and transcriptomic data. At the same time, we actively collaborate with biologists and physician-scientists working on prostate cancer, kidney cancer, central nervous system (CNS) tumors and other diseases.
• Identification of biomarkers (i.e., SNPs, mutations, DNA methylations, copy number variations, RNA splice variants) that are associated with certain phenotypes such as poor prognosis, tumor subtypes, drug resistance, etc. With the aim to help developing new therapeutic agents and enable stratified healthcare and precision medicine.
• High dimensional biomedical data mining and integration using system biology and machine learning approaches. With the aim to use data science approaches to build descriptive models or predictive models to improve healthcare.

Dr. Nansu Zong (Assistant Professor of Biomedical Informatics, Department of Artificial Intelligence and Informatics, Mayo Clinic)

Dr. Zong leads a cutting-edge lab within Mayo Clinic's Department of Artificial Intelligence and Informatics, harnessing the power of AI and biomedical knowledge to create advanced predictive models. The lab's primary focus is on developing state-of-the-art AI techniques for computational drug repurposing and predicting treatment outcomes using electronic health records (EHRs) and knowledge bases. Their research encompasses various diseases, including Alzheimer's disease and cardiovascular diseases. To achieve their objectives, the team employs advanced AI techniques such as graph neural networks, embedding, generated models, reinforcement learning and large language models to process biomedical knowledge graphs and EHR data.

Key areas of focus:

• Computational drug repurposing: Dr. Zong's team pioneers the development of novel AI methods for identifying new uses for existing drugs through computational drug repurposing. They utilize graph neural networks, embedding, large language models and other advanced AI techniques to analyze extensive biomedical data, identifying patterns and relationships that facilitate predicting drug efficacy and side effects.
• Clinical decision support: The team focuses on predicting disease and treatment outcomes while also exploring optimal regimen learning. Leveraging EHRs, they develop clinical decision support systems using AI techniques such as reinforcement learning, large language models and other advanced approaches.
• Deep phenotyping based on EHRs: Dr. Zong's team employs AI techniques to perform deep phenotyping, which involves extracting comprehensive clinical data from EHRs to gain a detailed understanding of a patient's medical history and condition. They model substantial amounts of data, including structured medication and lab test records, as well as unstructured patient clinical notes, using advanced deep learning models and large language models. The goal is to develop a thorough comprehension of a patient's medical background and condition, enabling the creation of data-driven tools that automatically identify patient subtypes within subcohorts.
• Large language models: Dr. Zong's team also leverages large language models as part of their research endeavors. These models, such as GPT-3, enable the team to process and analyze textual data in the biomedical domain.

Dr. Yung-Tsi Bolon (Director, Immunobiology & Bioinformatics Research)
Dr. Yung-Tsi Bolon directs the Immunobiology & Bioinformatics Research teams at the National Marrow Donor Program (NMDP)/Be The Match and serves as a Scientific Director for the Center for International Blood and Marrow Transplant Research (CIBMTR) with areas of expertise in omics, machine learning and predictive analytics, cellular therapy optimization and donor registry modeling. In addition, her team manages the research sample biorepository and the associated data that is used for almost every CIBMTR study that explores transplant outcomes for patients, generating the knowledge needed to improve patient lives after transplant. Her focus is on design, execution and delivery of actionable research studies into insights and resources that can improve survival outcomes and quality of life for patients from all demographics.

Mr. Stephen Spellman (Director, Immunobiology and Observational Research, CIBMTR)
Mr. Spellman directs the Immunobiology & Observational Research Program and serves as an Assistant Scientific Director in the Center for International Blood and Marrow Transplant Research (a research collaboration between the National Marrow Donor Program/Be The Match and the Medical College of Wisconsin). He has oversight for the Immunobiology and Graft versus Host Disease Working Committees and is the Principal Investigator for the CIBMTR/NMDP Research Sample Repository. Mr. Spellman’s research focuses on discerning the immunogenetic and immunobiological factors that influence the outcome of allogeneic hematopoietic stem cell transplantation.  

Dr. Frank Albert (Associate Professor, Genetics, Cell Biology and Development, TCBS)
The Albert lab studies how genomic variation influences gene expression and complex traits. Individuals in a species carry their own, unique genome. Their genomes differ from each other at thousands to millions of sites. Many of these differences have no effect. Others can dramatically influence the way an individual looks, how it behaves, or which diseases it is susceptible to. How can we tell which DNA differences have consequences for the organism? How exactly do these polymorphisms exert their effects? And how did this genomic diversity evolve? We are examining these questions by combining experimental functional genomics and computational statistical genetics. A particular focus is on emerging technologies for high-throughput reading, editing and synthesizing of genomes, which now allow us to systematically answer questions at the core of genetics. We deploy these tools in yeast and other species to learn fundamental principles of how genetic variation shapes phenotypes across eukaryotic life.

Dr. Julio Alvarez (Assistant Professor, Department of Veterinary Population Medicine, College of Veterinary Medicine)
Dr. Alvarez's trajectory has always been focused on the study of the epidemiology of infectious diseases, with an emphasis on zoonotic pathogens. His current research interests include the application of quantitative techniques for the design, implementation, monitoring and evaluation of prevention and control strategies against infectious diseases, with special emphasis in zoonoses (tuberculosis, brucellosis, foodborne salmonellosis and campylobacteriosis, etc.) and diseases affecting livestock production (paratuberculosis, PRRS, PED, swine influenza)

Dr. Elizabeth Ambrose (Associate Professor, College of Pharmacy)
The Ambrose laboratory’s research program focuses on CBRNE (chemical, biological, radiological, nuclear and high explosive) agent mitigation, particularly Bacillus anthracis (the causative agent of anthrax), the ricin toxin, and organophosphate nerve gases such as sarin, soman and VX. Our goals include the design and optimization of small-molecule anthrax toxin lethal factor (LF) inhibitors and ricin toxin A (RTA) inhibitors, to be used as emergency therapeutics in the event of bioterror attacks and engineering enzyme active sites to rapidly and effectively hydrolyze fast-acting nerve agents. We are a full-spectrum early- to mid-stage drug discovery laboratory encompassing high-throughput and fragment screening, lead optimization, structure-based design, cell-based assays and modeling. We have particular expertise in Biosafety Level (BSL)-2 and -3 and Select Agent safety and security protocols. Professor Ambrose also has research and teaching interests in CNS-targeted drug design and optimization, focusing on psychiatric pharmacy and neuropharmacology.

Dr. Massoud Amin (Professor, Electrical and Computer Engineering)
Dr. Massoud Amin's research focuses on two areas: 1) Global transition dynamics to enhance resilience, security and efficiency of complex dynamic systems. 2) Science and Technology scanning, mapping, assessment and valuation to identify new science and technology-based opportunities that meet the needs and aspirations of today's consumers, companies and the broader society. This thrust builds coherence between short- and longer-term R&D opportunities and their potential impact.

Dr. Eric Batchelor (Assistant Professor, Department of Integrative Biology and Physiology (IBP) 

The Batchelor lab seeks to develop a quantitative, system-level understanding of stress response pathways at multiple scales -- from individual cells to whole organisms. Much of our research focuses on cell stress responses mediated by the tumor suppressor protein p53. We have used long-term time-lapse imaging to show that p53 undergoes complex dynamics in response to different forms of DNA damage and our current work focuses on understanding the regulation and function of p53 dynamics in single cells. We focus on identifying the molecular details by which p53 dynamics regulate downstream damage response pathways, including those regulating cell cycle arrest, DNA repair, senescence, apoptosis and metabolism. We aim to identify how specific p53 pulse characteristics (amplitude, duration, or frequency) encode information that is decoded at the promoters of transcriptional targets. We are also applying quantitative, single-cell approaches to identify novel modes of regulation between p53 and other important signaling pathways, including the MYC proto-oncogene network and MAPK signaling. By developing a more quantitative understanding of these important signaling pathways, we hope to not only increase our basic understanding of these signaling dynamics in regulating cell fate decisions, but also provide novel methods for chemotherapeutic manipulation of signaling dynamics to alter cell fate in cancers in which the pathways are deregulated.

Dr. Paloma Gonzalez Bellido (Associate Professor Ecology, Evolution and Behavior)
In the FLYSY laboratory we study the performance of neural systems. Our aim is to understand how fast and accurate responses can be achieved with a limited number of neurons. 

We have two main methods of study: High speed video recordings of flies predating and electrophysiology to record nerve signals in response to stimuli. By carefully curating what we present in either situation we can come to a more comprehensive understanding of behavior, the physiology that drives it and the environmental factors that effect how predation is carried out by these tiny animals.

Dr. Dan Boley (Professor, Computer Science and Engineering)
Computational methods in linear algebra, scalable data mining algorithms, algebraic models in systems and evolutionary biology, biochemical metabolic networks. Current projects include scalable computation and analysis of elementary pathways through metabolic networks of single-cell organisms, Markov model of evolution of the avian influenza virus, scalable data mining algorithms for corpora of short text fragments.

Dr. Erin Carlson (Associate Professor, Chemistry)
The Carlson Group unites tools from chemistry and biology to promote the development and application of new strategies for treatment of bacterial infections and the discovery of efficacious compounds. One focus of our group is the development of strategies to dramatically expand our ability to explore natural product chemical space, with the goal of identifying privileged structures and novel antibacterial agents. We are constructing a toolkit of functional group-specific tags to facilitate compound isolation and a platform that combines mass spectrometry and informatics to assist in the detection of novel extract components and accelerate the structure elucidation process.

Dr. Yue Chen (Assistant Professor, Department of Biochemistry, Molecular Biology, and Biophysics)
The Chen Lab at the University of Minnesota develops key technologies to discover novel posttranslational modification pathways and characterize functionally significant regulatory mechanisms through quantitative and mechanistic analysis. We combine cell biology, chemical biology, bioinformatics and mass spectrometry-based proteomics technology to identify functionally significant modification and epigenetic regulatory processes. We are particularly interested in understanding how cell metabolism and cellular microenvironment regulate protein functions, homeostasis and epigenetic gene expression through posttranslational modification pathways. Current research projects systematically study the dynamics of modification regulatory networks using mouse models and model cell lines to determine the mechanisms of iron and oxygen sensing in the context of neuronal development and cancer.

Dr. Vladimir Cherkassky (Professor, Electrical and Computer Engineering)
My research interests include machine learning and statistical learning. This is also known as predictive learning, where the goal is to estimate a good predictive model from available data. Predictive learning broadly overlaps with data mining, statistical estimation, signal processing and artificial intelligence. In particular, I am interested in biomedical applications that use estimation of predictive / diagnostic models from patients' (clinical, genetic, demographic) data. I am also interested in bringing the gap between machine learning research and its practical acceptance by medical researchers and practitioners.

Dr. Chih-Lin Chi (Assistant Professor, School of Nursing & Institute for Health Informatics)
Dr. Chi’s research studies focus on understanding how a person's individual characteristics influence the outcome of multiple medical treatments and how an individual, care team and hospital network can select and implement the treatment decision that will maximize the overall health care outcome. His general approach starts from using machine learning techniques to mine such personalized health care knowledge from diverse type of electronic health records. Early involvement of interdisciplinary team members such as the current collaboration with nursing, pharmacy, cardiologists, dementia care specialists and health economists are essential in the subsequent translational-research studies. Our team works together to use clinical trial simulations to gather computational evidence of efficacy improvement to facilitate the following clinical studies.

Dr. Jerry D. Cohen (Gordon and Margaret Bailey Professor, Horticultural Science, CFANS)
Our laboratory focuses on the use of advanced analytical and isotopic methods to define complex biochemical events over time in plants. 

We currently have four major focus areas:

Cell signaling and growth regulation: The primary signal transduction systems in plants involve hormonal messengers that translate developmental, positional and environmental information into optimized growth and development. It is one of the fundamental goals of this laboratory to understand in precise detail how the levels of auxin (indole-3-acetic acid, IAA), the first discovered plant hormone, are regulated in specific cells and tissues within plants.

Toward single cell biology: One of the major limiting factors in plant metabolomics is the absence of effective methods for measuring spatial distributions of metabolites. We are currently evaluating many microsampling techniques for targeted metabolomics and metabolic flux analysis, especially for indolic metabolites and stress-related compounds in plants.

Communication between plants and insects: The deposition of antimicrobial plant resins in honey bee nests has important physiological benefits, however, resin foraging is difficult to approach experimentally because resin composition is highly variable among and between plant families, the environmental and plant-genotypic effects on resins are unknown and resin foragers are relatively rare and often forage in unobservable tree canopies. We use metabolomic methods as a type of environmental forensics to track individual resin forager behavior through comparisons of global resin metabolite patterns

Metabolomics and metabolic flux analysis: The flow of matter through an organism’s network of metabolic pathways is the most direct molecular indicator of an organism’s phenotype. Together with Dr. Adrian Hegeman’s laboratory, our goals are to improve the applicability of dynamic metabolic flux analysis to intact plants by optimizing methods for measurement of such fluxes in intact plant systems using timed, stable, isotope-labeled nutrient incorporation, LC and GC-MS analysis, and automated data extraction and calculation of dynamic fluxes.

Dr. Peter Crawford, MD, PhD (Professor, Departments of Medicine and Biochemistry, Molecular Biology, and Biophysics)
We leverage recent advances in mass spectrometry to develop and deploy stable isotope tracer untargeted metabolomics-based informatic algorithms in the study of metabolism on a systems level. We also employ established techniques in nuclear magnetic resonance spectroscopy, molecular cell biology and biochemistry to reveal phenotypic shifts at the cellular level. Complex in vivo phenotyping methodologies are strategically aligned with these sophisticated chemical profiling platforms to generate high resolution phenotypic pictures. In addition to mouse studies, we perform studies in human subjects to learn how alterations of ketone metabolism and related pathways may serve as diagnostic biomarkers and therapeutic targets for obesity, diabetes, fatty liver disease, heart failure and metabolic maladaptations that can occur in any disease state.

Dr. Yang Da (Professor, Department of Animal Science)
Dr. Yang Da's current research includes developing quantitative and computational methods for genome-wide association analysis and QTL and eQTL mapping to detect genes affecting human diseases and animal quantitative traits and includes finding genes underlying production, reproduction and health phenotypes in the Holstein breed of dairy cattle using genome-wide association and QTL mapping methods.

Dr. Yibin Deng (Professor, Department of Urology and Masonic Cancer Center)
Generation and establishment of experimental models that recapitulate the salient features of human cancers harboring various types of genetic changes (prostate, breast, lung and colon) for oncology research and cancer medicine utilizing human organoids, patient-derived xenograft (PDX) models and genetically engineered mouse models (GEMMs); Cancer Genetics; Cancer Cell Death (Apoptosis, Necroptosis, Ferroptosis, Pyroptosis and Autophagic Cell Death); Cell/Tissue Metabolomics; Structural Biology (X-Ray crystallography and Cryo-electron microscopy) and Computational Bioinformatics. 

Dr. Xiao Dong  (Assistant Professor, Department of Genetics, Cell Biology and Development; Institute on the Biology of Aging and Metabolism)
The general interest of the Dong Laboratory is discovering causal mechanisms of human aging. Currently, we focus on testing the mutation theory of aging: if accumulation of DNA mutations in normal somatic cells is a causal mechanism to age-related functional decline. We approach this by developing and applying state-of-the-art single-cell multi-omics technologies and machine learning algorithms.

Dr. Meghan Driscoll (Assistant Professor in the Department of Pharmacology, School of Medicine)Cells have convoluted and dynamic morphologies. Their morphology is a critical element of the vast signaling network regulating cellular functioning. Focusing on cancer and immune cells, which are often highly dynamic, the Driscoll lab investigates how the interplay between cell morphology, dynamics and signaling governs cell function. To visualize quick subcellular dynamics, we use state-of-the-art microscopy, especially high-resolution light-sheet microscopy. The detailed 3D movies produced by these microscopes necessitate dedicated computational pipelines and so we develop algorithms rooted in computer graphics, computer vision and machine learning to facilitate biological discovery.

Dr. Sian Durward-Akhurst (Assistant Professor, Department of Veterinary Clinical Sciences)
I am co principal investigator of the University of Minnesota Equine Genetics and Genomics Laboratory. We investigate genetic diseases that are highly detrimental to horses and in many cases have translational potential as spontaneous models of human disease. My research is especially focused on investigating cardiac arrhythmias and sudden cardiac death in racehorses. Our group is interested in developing genomic tools to facilitate future research efforts and in developing guidelines for facilitating the development and use of genetic tests.

Dr. Lynn Eberly (Professor, Division of Biostatistics, School of Public Health)
My research focuses on methods and applications for correlated data across a wide variety of statistical/machine learning/data science contexts. "Correlated" can mean longitudinally correlated or cluster correlated, where a cluster might be a person or a place or some other entity. I have a particular interest in multi-modal magnetic resonance imaging (MRI) and the use of MRI in clinical/intervention trials, neuroscience and neurodegenerative diseases, psychiatry/psychology, endocrinology and other related applications.

Dr. Jasmine Foo (Associate Professor, School of Mathematics) Institute)
I work in the areas of applied mathematics and mathematical biology. My research focuses on using mathematical models of population dynamics to study the processes of somatic evolution. Some applications of interest are evolutionary processes leading to cancer, the emergence of drug resistance and the feedback between spatially structured populations and their local microenvironments.

Dr. Steven Friedenberg (Assistant Professor, Department of Veterinary Clinical Sciences, College of Veterinary Medicine)
Dr. Friedenberg studies complex genetic diseases in dogs as a model for orthologous diseases in humans. We are particularly interested in autoimmune diseases that require urgent care or hospitalization in intensive care units, such as Addison’s disease and immune-mediated hemolytic anemia. We also have ongoing collaborations with researchers at North Carolina State University to study mitral valve degeneration in dogs. Much of our work involves “big data” efforts including genome-wide associations studies, whole genome sequencing, RNA sequencing and sequencing of antigen receptor loci. Our ultimate goal is to improve canine health by understanding the genetic mechanisms that cause these diseases and to help develop new treatment options for animals (and people) affected by these conditions.Dr. Steven Friedenberg (Assistant Professor, Department of Veterinary Clinical Sciences, College of Veterinary Medicine) studies complex genetic diseases in dogs as a model for orthologous diseases in humans. We are particularly interested in autoimmune diseases that require urgent care or hospitalization in intensive care units, such as Addison’s disease and immune-mediated hemolytic anemia. We also have ongoing collaborations with researchers at North Carolina State University to study mitral valve degeneration in dogs. Much of our work involves “big data” efforts including genome-wide associations studies, whole genome sequencing, RNA sequencing and sequencing of antigen receptor loci. Our ultimate goal is to improve canine health by understanding the genetic mechanisms that cause these diseases and to help develop new treatment options for animals (and people) affected by these conditions."

Dr. Joshua Gamble (Adjunct Assistant Professor in the Department of Soil, Water, and Climate)
My research aims to develop and evaluate cropping systems incorporating perennial crops intended to improve water and soil quality, protect against erosion and that provide resiliency in response to climate change. I utilize small-plot and whole-field research combined with statistical or process modeling to evaluate the impacts of agronomic management on long-term system productivity and provisioning of ecosystem services. I work extensively on quantifying field-scale changes in soil carbon, net ecosystem carbon balances and water quality in response to crop rotation, cover cropping, manure management and irrigation. Recent work is also focused on quantifying uncertainty and reconciling methods for C accounting in agricultural systems. I work with established crops like alfalfa and novel perennial systems including low-input native grassland for biomass and bioenergy, cover crops and living mulches, agroforestry systems and Kernza intermediate wheatgrass.

Dr. Jiali Gao (Professor, Department of Chemistry and Digital Technology Center)
We develop computational methods to study systems of biological or chemical significance. We develop the theory and implement it in a computer program to carry out detailed simulations of the system. In particular, we combine quantum mechanics and molecular mechanics (QM/MM) to model large molecular systems, including proteins and nucleic acids. The focus of our group includes: (1) development of novel combined QM/MM methods to study chemical and biological reactions, (2) an understanding of the origin of enzyme catalysis and (3) modeling the diffusion and interactions of macromolecular particles in cellular environment.

Dr. Melissa Gardner (Associate Professor, Genetics, Cell Biology, and Development)
Our research group uses a combination experimental and computational approach to dissect molecular mechanisms for how cells divide, and for how cell division is controlled to prevent genetic diseases, pathogenic anti-fungal drug resistance and cancer. Specifically, we are interested in how proteins regulate the dynamics and mechanics of critical cell division components. These components include microtubules, which align duplicated chromosomes and then pull them apart during cell division and also the chromosomes themselves, whose own mechanics contribute to their proper segregation during mitosis. Our overarching goal is to improve human health by developing an improved mechanistic understanding for how cells divide.

Dr. Tim Griffin (Professor, Biochemistry, Molecular Biology, Biophysics)
Work in Dr. Griffin's group involves the development and application of mass spectrometry-based tools to study proteins and proteomes. The goal of this work is to enable the comprehensive characterization of the entire complement of proteins expressed within a cell, tissue, organism or bodily fluid, in order to better understand basic mechanisms of biological function and disease. The development of these tools is highly interdisciplinary in nature, integrating front-end molecular biology and biochemical methods, protein and peptide chemistry, analytical separations, instrumental analysis and back-end computational software for data processing and bioinformatic analysis.

Dr. Weihua Guan (Associate Professor, Division of Biostatistics)
My research focuses on statistical genetics and the identification of genes involved in complex diseases and traits, with a special emphasis on developing statistical and analytical methods for the genetic data with new high-throughput technologies. Expertise: Chronic diseases, genetics, methods, statistical genetics, genomics, genome-wide association, DNA methylation.

Dr. PingHsun Hsieh (Assistant Professor, Genetics, Cell Biology and Development)
We are interested in studying translational and evolutionary medicine at the intersection of long-read based multi-omics, evolutionary biology and human health. Our lab is particularly interested in the fitness consequences of structural variants (SVs, e.g., deletions, duplications and variable number of tandem repeats)—an important but understudied class of genomic variation that is known to alter many more bases than single-nucleotide variants (SNVs) in the human genome, more likely to result in phenotypes and, thus, subject to selection. We use population genomics to study key evolutionary processes, such as hybridization and selection, that lead to genetic novelties in populations in response to environmental changes. Our approach to these questions combines the development of statistical modeling, long-read sequencing technology, large multi-omics and biobanking databases.

Dr. R. Stephanie Huang (Associate Professor, Experimental and Clinical Pharmacology, College of Pharmacy)
The Huang laboratory’s main research focus is translational pharmacogenomics with particular interest in the pharmacogenomics of anti-cancer agents.  By systematically evaluating human genome and its relationships to drug response and toxicity, their goal is to develop clinically useful models that predict risks for adverse drug reactions and non-response prior to administration of chemotherapy.  With her broad training background, Dr. Huang assembles and leads a multi-disciplinary team that consists of computational biologist, geneticist, pharmacist, physician, molecular biologist and biostatistician to tackle a series of serious problems in cancer research. These include the lack of mechanistic understanding of genomic regulation of cancer phenotypes; the lack of reproducible predictive biomarkers for cancer therapeutic agents and the lack of effective treatment for many hard to treat cancers.

Dr. Paul Iaizzo (Professor, Surgery; Integrative Biology and Physiology; Carlson School of Management)
Paul Iaizzo, Ph.D., is a professor of Surgery, Integrative Biology and Physiology, and the Carlson School of Management. He is also the Medtronic Professor and principal investigator for the Visible Heart® Research Laboratory which focuses on Translational Systems Physiology. He is a Distinguished University Teaching Professor, director for Education of the Lillehei Heart Institute and director of the Malignant Hyperthermia Muscle Biopsy Center and past associate director for Education, Institute for Engineering in Medicine, among other positions. Some of Dr. Iaizzo’s research interests include medical device design, cardiac anatomy and physiology, thermoregulation, skeletal muscle pathophysiology, ischemia protection and black bear hibernation physiology.

Dr. Tinen Iles (Assistant Professor Surgery, Medical School)

• Cardiac anatomy and physiology
• Computational Simulation and Modeling for surgical planning, teaching and visualization
• Device design and testing- bench testing and Visible Heart Methodologies
• Hibernation physiology and translational applications of biomimicry
• Ex Vivo Perfusion and pharmacologic pre/post-treatment for cardiothoracic surgery and transplantation

Dr. Zhenong Jin (Assistant Professor in Bioproducts and Biosystems Engineering)
Agriculture is the cornerstone of human society, but we can’t achieve food security without preserving the environment and mitigating climate change. As a broadly trained quantitative agroecologist, Dr Jin’s research aims to push the frontier of big-data analytics for sustainable agriculture by integrating remote sensing, computational modeling and machine learning, such that we can monitor and manage every cropland, track pollutants, forecast agricultural risks, provide farmers best solutions to minimize negative environmental impacts and ultimately help the world to achieve a sustainable food future.

Dr. Karunya Kandimalla (Associate Professor, Department of Pharmaceutics, College of Pharmacy)
The Kandimalla Laboratory has been developing experimental methods and models to facilitate the early diagnosis and treatment of Alzheimer’s disease. In collaboration with investigators at the Mayo Clinic, Kandimalla Lab has been investigating insulin signaling/trafficking deficiencies in the cerebral vasculature of Alzheimer’s disease patients and is discovering methods to reposition existing drugs to treat these patients. Further, Kandimalla Lab has been involved in designing nanotheranostics for the diagnosis and treatment of stroke and cerebral amyloid angiopathy in collaboration with the National High Magnetic Field Laboratory and the Mayo Clinic.

Dr. Fumi Katagiri (Professor, Plant and Microbial Biology)
Our research focuses on inducible immunity of plants, particularly pathogen recognition and ensuing signal transduction processes. Unlike many other biological response systems, in inducible immunity pathogens not only initiate the signaling event but also attack the host's signaling network to negate the host immunity. To withstand attack from pathogens, which evolve much faster than the host, the immune signaling network needs to have properties much more complex than other biological signaling networks. We take systems biology approaches to study this biological network using genomically tractable model plant host and pathogen: Arabidopsis thaliana and Pseudomonas syringae.

Dr. George Karypis (Professor, Department of Computer Science and Engineering)
My research interests are concentrated in the areas of data mining,recommender systems, learning analytics, high-performance computing and chemical informatics and from time-to-time, I look at various problems in the areas of health informatics, information retrieval, bioinformatics and scientific computing.

Dr. Arkady Khodursky (Associate Professor, Biochemistry, Molecular Biology, and Biophysics)
My laboratory studies transcriptional activity of genomes of model microbes: Escherichia coli, Synechocystis and Saccaromyces cerevisiae. We design, manufacture and use whole genome DNA microarrays to understand relationships between genotypes and phenotypes, structure of the chromosome and its transcriptional activity, as well as between environmental conditions and transcriptional responses.

Dr. Dan Knights (Assistant Professor, Computer Science and Engineering)
Our lab’s focus is the functional characterization of complex host-microbe interactions in host diseases and behavior. Perhaps the grandest bioinformatics challenge of the genomics era is to place genes into functional disease pathways using data sets of limited sample size. Human genome studies have identified associations between our own genetics and disease, but in a surprising number of diseases, including cancer, autoimmune diseases, autism, HIV and obesity, as well as aspects of animal behavior, our “second genome”–the mixture of genes in our resident microbes–has recently been implicated. In many of these cases we still understand little about the mechanisms of host-microbe interactions. Read more >>

Dr. Rui Kuang (Associate Professor, Computer Science and Engineering)
My lab develops machine-learning algorithms to extract and integrate subtle and elusive information hiding in genome-wide large-scale biological data for understanding the association between genomic characteristics and phenotypes. We are particularly interested in designing novel kernel methods and graph-based learning algorithms for a unified analysis of high-throughput data in a data-driven perspective.

Dr. Vipin Kumar (Regents Professor, Computer Science and Engineering)
Motivated by the need to solve important bio-medical problems using computational approaches, Dr. Kumar's group works on several interesting problems using data mining techniques. These include protein function prediction, connecting disease characteristics with genomic and phenotypic factors, characterizing brain dynamics and studying their role in mental disorders and mining electronic medical records.

Dr. Ryan Langlois (Associate Professor McKnight Presidential Fellow, School of Medicine)
The Langlois lab aims to address fundamental questions in virology and viral immunology that have been difficult to dissect using conventional approaches. We generate novel recombinant viruses, virus-host model systems, and animal models to probe the antiviral responses. We are also interested in how viruses evolve in the face of antiviral immune responses and how viruses make jumps into new species. To study this, we develop new model systems to track viruses within both the reservoir and host. To address all of these questions, we use a combination of wet lab and computational approaches. Find out more about Dr. Langlois’s lab on the lab’s website https://www.langloislab.umn.edu/.

Dr. James J. Lee (Associate Professor, Psychology, CLA)
Dr. Lee conducts genome-wide association studies (GWAS), specializing in bioinformatic analyses elucidating the cellular and molecular mechanisms through which genetic variation affects the trait of interest. He has contributed to studies of cognition, personality, mental illness, substance use and fertility. He is currently interested in using GWAS data to study how natural selection has shaped phenotypic variation over the course of human evolution.

Dr. Gilad Lerman (Professor, School of Mathematics; Director of Minnesota Center for Industrial Mathematics; Director of Institute of Mathematics and its Applications)
Professor Lerman has been developing solutions to data and information science problems. His investigations and collaborations have led to original and much-needed theoretical foundations, novel algorithms that outperform commonly used ones, and successful solutions to applied problems. In particular, he has managed to unite strong performance guarantees with flexible and efficient algorithms that can scale to huge, real datasets. Applications have included structure from motion, motion tracking and segmentation in computer vision and robust dimensionality reduction in machine learning.

Dr. Danni Li (Associate Professor, Department of Laboratory Medicine and Pathology)

The Li Lab focuses on understanding the pathophysiology of Alzheimer’s disease (AD) and AD-related dementias (ADRDs) through peripheral systems. We believe that peripheral systems play a critical role in developing neurodegenerative diseases. We use proteomics- and lipidomics-based approach to investigate plasma lipoproteins and correlate protein and lipid level data with neuroimaging and cognitive outcomes to inform plasma lipoprotein-associated proteins and networks that contribute to the pathogenesis and disease progression of AD and ADRDs. We examine disease-progression-related changes in tau interactome to inform therapeutic development that potentially slows down tau aggregation, a hallmark of many neurodegenerative diseases. APOE4 is a significant genetic risk factor for AD. We study the impact of APOE genotypes and transgenic APP/PS1 expression on mitochondrial lipidomic dynamics and their correlations with neuropathology and cognitive impairments during brain aging and pathogenesis and progression of AD.

Dr. Kelvin Lim (Professor, Department of Psychiatry)
My research interest is in the use of neuroimaging approaches to identify circuit abnormalities in brain disorders such as schizophrenia, traumatic brain injury and addiction and then to use these circuits as treatment targets for noninvasive neuromodulation interventions.

Dr. Julia Liu (Assistant Professor, Department of Integrative Biology and Physiology (IBP))
The Liu Lab studies the role of mitochondria in generating, signaling and responding to cellular stress, particularly in cardiac and skeletal muscle. In particular, we currently focus on how the dysregulation of mitochondrial calcium leads to physiological changes in mouse models. Mitochondrial calcium handling plays a critical role in energy production as well as cell death. To decipher the impact of calcium perturbation on multiple scales, our approaches span a variety of experimental techniques, from biochemical measurements on isolated mitochondria to live cell microscopy to in vivo phenotyping. We also incorporate large-scale transcriptomics, proteomics and metabolomics techniques to gain more quantitative understanding of how mitochondrial stress drives cellular changes.

Dr. Walter Low (Professor and Associate Head for Research, Department of Neurosurgery)
Dr. Low’s research is focused on translating neuroscience developments from the laboratory to the clinic. He has been involved in a number of technologies that include neural progenitor/stem cell therapies, gene therapies, neuroprotective therapies and medical devices for treating a variety of neurological conditions. Neural disorders of interest include ischemic and hemorrhagic stroke, Parkinson’s disease, brain tumors, Alzheimer’s disease, lysosomal storage disorders of the brain, Huntington’s disease, spinal cord injury and traumatic brain injury.

Dr. Mitchell Luskin (Professor, School of Mathematics)
Mitchell Luskin's research expertise is multiscale modeling and computing, numerical analysis, applied mathematics and differential equations. He develops theory and algorithms for finite element methods, molecular dynamics, material microstructure and atomistic-to-continuum coupling methods.

Dr. Louis Mansky (Professor, Diag/Biological Sciences, School of Dentistry, Microbiology, Medical School and Director, Institute for Molecular Virology)
Cell and molecular biology of human cancer viruses (hepatitis B virus; human T-cell leukemia virus) and HIV; antiviral drug target identification; antiviral drug resistance; virus evolution, genetic diversity and population genetics; single-molecule fluorescence; cryo-electron microscopy; virus particle assembly; evolution of emerging viruses.

Dr. Molly McCue (Associate Professor, Veterinary Diagnostic Laboratory)
Our research group uses is to use the latest molecular genetics and genomics tools to study complex genetic disease, physiological variation and genetic diversity in equine populations. Our goals are to improve equine health through the understanding of complex genetic disease, allowing veterinarians to better predict, diagnose and treat genetic disease and to improve human health through the use of the horse as a biomedical model.

Dr. Lauren Mills (Researcher, Department of Pediatrics)
My research focuses on discovering the genetic and epigenetic traits of pediatric sarcomas that lead to onset, progression and severity of disease. Working with both primary human samples as well as canine sarcomas, I can also take a comparative genomics approach to the study of sarcomas to improve both human and canine treatments for sarcomas. I have expertise in a wide range of genomic, transcriptomic and epigenomic data analyzes and advanced data visualizations.

Dr. Mohamed Mokbel (Associate Professor, Computer Science and Engineering)
Research Areas: Database systems, scalable data management techniques, query processing and optimization, spatial databases, context-aware data management, location-based services and Geographic Information Systems (GIS)

Dr. Bryon Mueller (Associate Professor, Department of Psychiatry and Behavioral Sciences)
My research focuses on the design, implementation, acquisition and analysis of magnetic resonance imaging (MRI) studies that seek to better understand the structure and function of the human brain. I have particular interest in applying the advanced MRI acquisition and analysis methods being developed at the Center for Magnetic Resonance Research (CMRR) at the University of Minnesota to study brain disorders. MRI is used to characterize the brain differences in clinical populations compared to matched healthy controls, to explore how the brain changes over time, to correlate brain metrics of clinical symptoms and cognitive metrics and to investigate how the brain changes in reaction to intervention.

Dr. Ramaiah Muthyala (Research Associate Professor, Department of Experimental and Clinical Pharmacology, College of Pharmacy)
The vision of our research program is to translate biological and chemical information into leads to drug-like molecules and optimize the lead small molecules to drug molecules using synthetic organic chemistry. The drug discovery will be combined with structure information obtained from ligand-protein structures, enzyme data derived from computational, modeling and biological experiments. The potential for speedy optimization of drug discovery, selective and carefully designed combinatorial small libraries along with rapid, sensitive and specific assay procedures are being explored. Natural products with desired biological activity at nanomolar range are considered as informed lead compounds for further development into drug candidates.

Dr. Chad Myers (Associate Professor, Computer Science and Engineering)
Professor Myers's research focuses on machine learning approaches for integrating diverse genomic data to make inferences about gene function and biological networks. He is also interested in experimental and computational characterization of genetic network structure and how it relates to phenotypic properties of biological systems.

Dr. Noelle Noyes (Assistant Professor, Department of Veterinary Population Medicine (VPM))
I am a veterinary epidemiologist with diverse research interests including antibiotic resistance, microbial ecology, livestock production microbiomes, metagenomics, antibiotic use in veterinary medicine, bioinformatics and statistics. Please visit our lab website for a complete description of our work: www.thenoyeslab.org.

Dr. Hai Dan Nguyen (Assistant Professor, Department of Pharmacology)
In response to DNA damage from environmental and endogenous sources, cells activate an elaborate signaling network called DNA damage response (DDR). This response functions to preserve genomic integrity, which is critical for normal development and cancer prevention. The ATR kinase is a master regulator of a broad spectrum of DNA damage and replication problems.

Sensors of DNA Damage, Replication and Transcription Problems: Our recent studies revealed that ATR is not only important for sensing DNA damage and replication stress, but also to problems associated with transcription. R-loop, a transcription intermediate resulting from the formation of stable RNA:DNA hybrids and a displaced single-stranded DNA (ssDNA), is a major source of genomic instability. We found that ATR is activated by R-loops and plays a critical role in suppressing R-loop-induced genomic instability, thus uncovering a new function of ATR in maintaining genome integrity. The Nguyen laboratory will continue to dissect how ATR regulates R-loop resolution in cancers.

Cancer Genomics and Targeted Therapy: we found that the splicing factor mutations associated with myelodysplastic syndromes (MDS) and acute myeloid leukemia (AML) induce R-loops and trigger an ATR response. Cells that express these splicing factor mutants are sensitive to ATR inhibitors, providing a new strategy to target R-loop response for the treatment of MDS and potentially other malignancies associated with RNA splicing mutations. The Nguyen laboratory will determine additional R-loop regulators in different cancer contexts to develop new therapeutic strategies in the future.

The Nguyen laboratory is currently developing small molecule probes, biochemical, cell biological and genetic approaches to investigate the underlying mechanisms of sensing and resolving R-loops in different cancers. Results obtained from these researches will provide molecular insight for the development of new targeted cancer therapeutic approaches. Interested applicants should have a PhD and/or MD degree with a strong background in either biochemistry, cell biology, functional genomics or pharmacology. The laboratory accepts Master and PhD students through Department of Pharmacology program.

Dr. Michael Olin (Associate Professor, Department of Pediatrics, Medical School)
I have dedicated my career to developing immunotherapy for pediatric brain tumors. We, among others, have utilized tumor cells as vaccine components, demonstrating promising results with minimal toxicity. However, progression to a productive immune response necessitates passing a number of immunological checkpoints that act as barriers to effective immunotherapy because of “self” antigen recognition. Our primary research is focused on the CD200 immune checkpoint, which modulates the immune system through paired receptors, i.e., an inhibitory receptor (CD200R1) and four activation receptors (CD200AR) in mice, two in humans. We developed a strategy to engage the CD200AR with a peptide ligand (CD200AR-L), which improved survival in breast and glioma murine models when used with tumor lysates (TL) to direct an anti-tumor response. Moreover, in dogs bearing spontaneous high-grade glioma receiving a canine-specific CD200AR-L, administered concomitantly with autologous TL, we showed a 43% 3-year progression-free survival, enhancing the median survival to 18 months as compared to 6 months in dogs receiving lysates alone. No toxicity or immune-related adverse effects were observed. We suggest that these unprecedented responses are due to CD200 acting as a “master regulator” for multiple immune checkpoints. Our preliminary studies showed that CD200AR-L overcomes the suppressive effects of CD200 and PD-L1 which are both shed by tumors, by downregulating the inhibitory CD200R1 and PD-1, on both antigen presenting cells (APC) and T cells, and PD-L1 on APCs, through the activation of the DAP10/12 pathways.  We now derived a humanized peptide inhibitor in a GMP facility and are submitting an IND for an upcoming Phase I trial.

Dr. Wei Pan (Professor, School of Public Health, Division of Biostatistics)
Wei Pan's research interests include statistical and machine learning approaches to analyzing microarray and other high-throughput data, and integrative analysis of genomic and proteomic data.

Dr. Serguei Pakhomov (Professor, Department of Pharmaceutical Care & Health Systems)
Research is the laboratory of Serguei Pakhomov is dedicated to developing computational linguistic methods and approaches for automated processing of speech and language in the biomedical domain. This research includes primary and secondary uses of automated linguistic analysis. Primary uses consist of identifying characteristics of speech and language produced by individuals affected by medications and patients with neurodegenerative and mental health conditions and developing conversational agents for improving health and wellbeing. Secondary uses consist of structuring unstructured free text of electronic health records and biomedical literature for subsequent information retrieval and clinical decision support systems. We are currently working on several projects.

Dr. Hongbo Pang (Assistant Professor, Department of Pharmaceutics)
The central question that Dr. Pang's lab focuses on is how to transport the cargo to the site of interest in human body with the high specificity and efficiency. His research synergizes multiple disciplines spanning from cell and cancer biology, peptide chemistry, nanomaterial to clinical imaging and cancer therapies. The ultimate goals are to discover new delivery technologies, decode the underlying transport machineries and develop novel diagnosis and treatment for cancer and other human diseases.

Dr. Nathan Pankratz (Associate Professor, Lab Medicine and Pathology)
Dr. Pankratz's research program is focused on identifying the genetic causes of complex diseases, such as Parkinson disease and cardiovascular disease. His lab routinely analyzes genome-wide association data tagging both single nucleotide polymorphisms and copy number variation, as well as sequence data for targeted regions, entire exomes and for whole genomes. Databases from NCBI and elsewhere are regularly used to inform primary and secondary analyses. The lab also actively develops Java software to organize and visualize genetic data, especially as it relates to copy number variation.

Dr. Laurie Parker (Associate Professor, Department of Biochemistry, Molecular Biology, and Biophysics, College of Biological Sciences)
Our research program is broadly directed at assay development for post-translational modifications (PTMs), with a focus on protein phosphorylation by tyrosine kinases. Protein tyrosine kinases play key roles in disease and are particularly important in cancer: mutations in several protein tyrosine kinase genes have been identified as drivers of many tumor types and drugs targeted at inhibiting these enzymes represent ~20% (>$9 billion) of the current oncology market. We use a “decoy” substrate biosensor approach (funded initially by a K99/R00 award from the NCI) in which an artificial, optimized substrate peptide is designed to report the activity of a specific enzyme in living cells. Delivery is achieved using cell-penetrating peptides and enzymatic modification is measured using a range of readout strategies—some that require extraction of the cell contents and some that leave the cell intact. Targeting the function of the enzyme in its intracellular environment preserves protein-protein interactions, localization and scaffolding-dependent activation and decoy substrates provide a snapshot of enzymatic activity that circumvents the need for pre-knowledge of every endogenous substrate site. We also develop multiplex-compatible readouts, so we can use a suite of biosensors for different enzymes in order to profile pathways. We have established our approach and laid the groundwork of a substrate development workflow to expand our repertoire of biosensors for kinases and other enzymes. Long term, our lab will maintain a pipeline of biosensor and read-out technology development while also taking an active role in studying signaling biology with our tools.

Dr. Andres Perez (Professor, Department of Veterinary Population Medicine, College of Veterinary Medicine; Endowed Chair of Global Animal Health and Food Safety; Director, Center for Animal Health and Food Safety)
Dr. Andres Perez is the Endowed Chair of Global Animal Health and Food Safety and the Director of the Center for Animal Health and Food Safety (CAHFS) at the College of Veterinary Medicine. Dr. Perez is an epidemiologist with an interest in the quantitative analysis of data to support decision making and policy with an impact on food animal health and food safety, with the ultimate goal facilitating food and animal trade and social development.

Dr. Jen Poynter (Associate Professor, Department of Pediatrics)
Dr. Poynter is a molecular epidemiologist with training in population studies, bench science and statistical methods. Her research is focused on the field of germ cell tumor (GCT) development and myeloid malignancy. She is the PI on a large molecular epidemiology study of pediatric GCT focused on genetic susceptibility and epigenetic alterations in pediatric GCTs using a case parent triad design (NIH R01 CA151284). GWAS data, whole genome sequencing data and tumor methylation data are available for the cases enrolled in this study.  She is also the PI of a funded Minnesota-based case-control study of myelodysplastic syndromes (MDS; NIH R01 CA142714) that includes questionnaire data and array genotyping data. Her laboratory work is focused on DNA methylation, genomic imprinting and susceptibility to childhood cancer.

Dr. Cavan Reilly (Associate Professor, School of Public Health, Division of Biostatistics)
Dr. Reilly's research focuses on statistical methods for high dimensional data for complex study designs, such as longitudinal and cross over studies. Currently he works primarily with LC-MS and next generation sequencing data sets with applications to the study of HIV and COPD.

Dr. Marc Riedel (Associate Professor, Electrical and Computer Engineering)
Dr. Riedel's research encompasses topics in nanoscale digital circuits design and in synthetic/computational biology. A broad theme is the application of computational expertise from the former (circuit design) to analysis and design problems in the latter (biology). A specific theme that cuts across both domains is constructing and deconstructing probabilistic behavior.

Dr. Juan Carlos Rivera-Mulia (Assistant Professor of Biochemistry, Molecular Biology, and Biophysics) Research in the Rivera-Mulia Lab is focused on the control mechanisms of genome architecture and function. Our goal is to understand how the genome is regulated, maintained in distinct cell types and remodeled during development. We exploit human embryonic stem cells (hESCs) and optimized differentiation systems to model development and computational tools to construct integrative models of genome organization and function

Dr. Zohar Sachs (Lois and Richard King Assistant Professor of Medicine, Division of Hematology, Oncology and Transplantation)
Acute myeloid leukemia stem cells: My lab’s goal is to identify molecular mechanisms of leukemia stem cell self-renewal in primary murine and human acute myeloid leukemia (AML). Self-renewal is a feature of leukemia stem cells that allow them to recapitulate leukemia and cause relapse. Since AML cells are highly heterogenous, we specialize in the application of single-cell, high throughput technologies (including mass cytometry/CyTOF and single-cell RNA sequencing) to address these research questions.

My earlier work demonstrated that the activated NRAS oncogene mediates self-renewal in AML and that individual leukemia cells vary significantly in their functional status and ability to self-renew (Sachs et al. Blood 2014). Recently, we defined the gene expression profile of AML self-renewal at the single-cell level and used this data to identify a functionally unique subset of leukemia cells with leukemia-repopulating potential. We are using these approaches to identify effective therapeutic targets for this deadly disease.

Dr. Uzma Samadani (Associate Professor, Department of Neurosurgery)
Dr. Samadani’s goal is to provide the best care humanly possible for her patients. She also believes that research can improve patient outcomes and offer greater options to people who would otherwise have relatively few. “I am honored by the trust that my patients place in me and will strive to always be deserving of that trust," she said. Although Dr. Samadani has broad surgical capabilities as a general neurosurgeon, she has a primary interest in cranial neurosurgery and a research interest in traumatic brain injury and hemorrhage. She has expertise in image-guided minimally invasive surgical techniques.

Dr. Declan Schroeder (Associate Professor, Department of Veterinary Population Medicine)
Areas of interest: molecular virology, biodiversity, pathology and genomics – in particular the use of genomic tools to study key biological processes. His research program is focused on pathogen discovery; comparing and contrasting a diverse array of host-virus systems. In particularly, his lab is interested in seeing fundamental research translated into practical solutions.  An example being their recent discovery of a new virus resistance mechanism in honey bees; providing a novel way of protecting this important pollinator. His lab will continue to develop molecular tools to enhance detection and surveillance of viral pathogens to enhance agricultural production, animal husbandry and human health (One Health paradigm) through an improved understanding of the true impact of (1) viral pathogens on honey bee health, (2) viral pathogens in swine respiratory diseases, (3) application of virus or phage therapy in pig, cattle and fish farms, and (4) the evaluation of the environmental Virome in disease outcomes in pig, cattle, honey bee & fish husbandry practices and their impact on human health.

Dr. Anna Selmecki (Assistant Professor and Dean's Fellow - Kavli Fellow, National Academy of Sciences, Department of Microbiology and Immunology)
Understanding the dynamics of how growth-promoting mutations arise and accumulate in a population of cells is a fundamental problem underlying our understanding of drug resistance, tumorigenesis and the treatment of cancer. We use experimental evolution, mathematical modeling and comparative genomics to understand the impact of mutations on the adaptation of a cell and its surrounding population.

We employ diverse yeast model systems (Saccharomyces cerevisiae, Candida albicans, Candida auris, etc.) to understand how genome instability contributes to adaptation (eg. antifungal drug resistance) and determine the underlying mechanisms that promote genome instability.

In the human fungal pathogen Candida albicans, genome rearrangements resulting in copy number variation (CNV) and loss of heterozygosity (LOH) confer increased virulence and antifungal drug resistance, yet the mechanisms driving these rearrangements are not completely understood. We recently identified an extensive array of long repeat sequences (65–6499 bp) that are associated with CNV, LOH and chromosomal inversions and are a significant source of genome plasticity across diverse strain backgrounds - including clinical, environmental and experimentally evolved C. albicans isolates. Many of these long repeat sequences were uncharacterized and encompass one or more coding sequences that are actively transcribed. Further, the repeats associated with genome rearrangements were predominantly inverted and separated by up to ~1.6 Mb, an extraordinary distance for homology-based DNA repair/recombination in yeast!

We also utilize flow cytometry-based systems that enable us to detect the acquisition and spread of beneficial mutations within populations. We found that polyploid S. cerevisiae adapted more rapidly than isogenic haploid or diploid cells in poor carbon medium and that polyploid cells acquired more mutations, including point mutations, large segmental aneuploidies and whole chromosome aneuploidies (Selmecki et al., Nature 2015). Additionally, polyploid cells acquired a broader spectrum of beneficial mutations than lower ploidy cells (Scott et al., MBE 2017). We continue to use these ploidy lineages to study how changes in chromosome number (ploidy and aneuploidy), cell size and environment affect genome stability and evolvability.

Our previous research identified chromosome aneuploidy as a driver for the acquisition of antifungal drug resistance in the pathogenic yeast C. albicans (Selmecki et al., Science 2006). We found that aneuploid cells arose within a population very rapidly in the presence of antifungal drug (Selmecki et al., PLoS Genetics 2009) and that increased copy number of two specific genes found on the most common aneuploid chromosome provided the drug resistance phenotype (Selmecki et al., Molecular Microbiology 2008).

Dr. Yuk Sham (Assistant Professor, Department of Integrative Biology and Physiology, Medical School)
The Sham laboratory focuses on the development of consistent and accurate computational models for understanding binding selectivity. We employ high performance computing to examine the molecular recognition process involved in cellular signaling and enzyme catalysis. Ability to quantify the intermolecular interactions provides the rational basis to structure-based drug design. Our biomolecular systems of interest are typically therapeutic protein targets involved in antiviral, antibacterial and anticancer discovery.

Dr. Laura Shannon (Assistant Professor, Department of Horticultural Science)
The Shannon Lab uses population and quantitative genetics to develop better understandings of potato genomics, diversity and evolution. This goal is complicated by the fact that, potatoes are autopolyploid, clonal and highly heterozygous. We leverage potato genomics to develop and apply methods to speed the potato breeding process and develop new varieties for Minnesota growers.

Dr. Kingshuk Sinha (Department Chair and Mosaic Company Professor of Corporate Responsibility, Supply Chain and Operations)
Dr. Sinha's scholarly pursuits are committed to advancing the areas of Management of Technology and Innovation, Global Supply Chain Management, Quality Management, Health Care Supply Chain Management, Responsible Supply Chain Management and Big Data Analytics. His inquiries are committed to identifying and addressing contemporary and consequential issues related to managing technologies, processes and people both within and across organizational and country boundaries. The inquiries are predominantly empirical. Typically, he conducts his scholarly projects in collaboration with industry partners. The empirical settings of his projects have included the high-tech; health care/medical; retail; food; and energy/oil and gas industries.

Dr. Michael Smanski (Assistant Professor, Biochemistry, Molecular Biology, and Biophysics)
Specialized metabolites, also known as 'natural products', are small molecules produced by plants, animals and microorganisms that have had a society-changing impact in areas such as medicine, agriculture and food production. Natural product research is poised to enter a new 'Golden Age', as currently available genome sequences contain the information required to produce tens of thousands of new molecules. Mining these genomes for the molecules they encode promises to re-invigorate our waning drug discovery pipelines, for example to find new antibiotics against drug-resistant pathogens. One focus of our group is to leverage new synthetic DNA technologies for the sequence-guided discovery of new bioactive molecules.

Dr. Logan Spector (Professor and Division Director, Epidemiology and Clinical Research)
Dr. Logan Spector is head of the Childhood Cancer Genomics Group (CCGG) at the University of Minnesota.  Dr. Spector and CCGG colleagues harness genome-scal techologies in order to understand the genetic basis of pediatric cancer etiology and outcome. Data includes whole genome/exome sequencing and SNP arrays on many pediatric cancers: acute lymphoblastic leukemia, acute myeloid leukemia, Hodgkin's lymphoma, neuroblastoma, Wilm's tumor, osteosarcoma, Ewing sarcoma, germ cell tumors and hepatoblastoma. The major thrust of his research is currently germline gene discovery through integrative genomic analysis, admixture mapping, Mendelian randomization and examination of gene-by-environment interaction. Areas of growing interest include use of genomewide methylation data to assess prenatal exposures and the integration of tumor genomics into epidemiologic studies.  In addition to NIH and national foundation funding, CCGG is backed by the strong local philanthropy of the Children's Cancer Research Fund.  The ultimate goal of Dr. Spector's and CCGG research is to enable risk prediction, early detection, prevention and cure of pediatric cancer.

Dr. Christopher Staley (Assistant Professor, Division of Basic and Translational Research, Department of Surgery)
The microbiome (the collection of microorganisms inhabiting a particular habitat or body site) plays a pivotal role in human development, functioning and health. The Staley lab’s research focus is to determine how disruptions of healthy microbial communities influence the onset and progression of diseases ranging from obesity to cancers. We utilize state-of-the-art, next-generation sequencing and (meta)-genomics methods to characterize microbial communities and leverage ecological principals and computational analyses to evaluate patterns associated with health and disease. Working with human microbiota-associated mouse models, we are able to translationally evaluate how changes in the microbiome affect the host in order to evaluate microbiota-based therapeutic interventions. The ultimate goal of our research is to develop personalized microbial therapies to improve clinical care and patient outcomes.

Dr. Sabbaya Subramanian (Assistant Professor, Division of Basic and Translational Research)
Subree Subramanian received a Bachelor of Science degree in Agriculture from Tamil Nadu Agricultural University, India in 1995. He then earned a Master of Science in Biotechnology in 1998 and a post-graduate Diploma in Patents Law from the National Academy of Legal Studies and Research, India in 2003. In the same year, he received his Ph.D. in Molecular and Cellular Biology from Jawaharlal Nehru University. From 2003 to 2007, he was a postdoctoral Research Scholar in the Department of Pathology at Stanford University. In late 2007, he was recruited as an Assistant Professor in the Department of Laboratory Medicine and Pathology at the University of Minnesota and then transferred to the Department of Surgery in 2010. Subree's laboratory is basically interested in understanding the microRNA (miRNA) mediated gene regulatory networks in sarcoma and other cancer types. We explore miRNA-mRNA associations that have potential role in tumor onset, progression and aggressiveness through miRNA and mRNA profiling as well as functional characterization of candidate miRNAs using in vitro and in vivo approaches. This will aid in the identification and development of novel miRNA-based biomarkers and targets for therapy. Our laboratory also is interested in engineering miRNA dysregulation in vivo and developing assays for screening small molecule inhibitors that can potentially modulate miRNA expression. The specific areas of research includes:

• Understanding the role of miRNAs in malignant transformation process

• Characterization of miRNA regulatory networks using comparative oncology of human and canine osteosarcoma

• Molecular mechanisms of microRNA expression and regulations

• Competing endogenous RNA (ceRNAs) in cancer gene regulation

Dr. Ruping Sun (Assistant Professor, Department of Laboratory Medicine and Pathology)
Dr. Sun is a computational geneticist with a PhD degree in genetics His research focus is on the translational genomics of solid tumors in conjunction with the Masonic Cancer Center. He has developed considerable expertise in algorithm design and statistical analysis of (epi)genetic sequencing data, as well as in the computational modeling of cancer, such as gene regulatory circuits and cellular automata models. For example, he pioneered research linking intra-tumor heterogeneity with underlying tumor growth dynamics using a data-driven modeling approach of multi-region sequencing (MRS) of solid tumors. He also first introduced regional-assembly into fusion transcript prediction and identified CD74-NRG1 as a potential target of the deadly invasive mucinous subtype of lung cancer. The unique experiences and quantitative training have equipped Sun to initiate a team effort to computationally decompose and model tumor heterogeneity, connecting the multiple facets of tumor evolutionary patterns to clinical features. His group will innovate algorithms and computational methods that advance a mechanistic understanding of tumor evolution and that are broadly utilized by the cancer bioinformatics community.

Understanding the underlying mechanisms behind the initiation, clonal expansion and progression of human cancers requires collaborative teamwork, in Sun's view. Mentoring trainees and teaching courses is a particular interest of his. The future of the fast-moving field of cancer bioinformatics will depend on the ability of students to develop analytical skills and a broader mindset for critical thinking.

Dr. Beth Thielen (Assistant Professor in the Department of Pediatrics, School of Medicine)

Dr. Thielen’s academic work encompasses both an active adult and pediatric clinical infectious diseases practice and a research program focused on host-pathogen interactions in the human respiratory tract, in particular innate immune signaling pathways induced by viral infections. Her lab is particularly interested in understanding the factors that influence the severity of respiratory viral infections, including viral sequence variants, respiratory microbiota composition and host genetics. The Thielen lab has several active projects focused on these questions:

- We are currently enrolling participant in a longitudinal cohort study (MINNE-LOVE) (z.umn.edu/minnelove) in which we seek to correlate respiratory microbiota dysbiosis and incident respiratory viral infections in a cohort of Minnesota children. As part of this study, we seek to analyze the genome sequences of circulating respiratory viruses, including influenza and SARS-CoV-2

- We are developing a respiratory epithelial-respiratory microbiota-influenza co-culture model to study mechanisms interactions between the respiratory microbiota and respiratory viral pathogens in vitro.

- We are developing a new longitudinal household-based study of respiratory viral molecular epidemiology across the state as an academic partner in the Pathogen Genomics Center of Excellence based at the Minnesota Department of Health.  This study will focus on engagement of traditionally underrepresented populations across the state.

- We are conducting a study of viral causes of fever in children undergoing chemotherapy for cancer treatment at the Uganda Cancer Institute in Kampala, Uganda.

- We are developing and testing novel techniques for diagnosing the molecular causes of suspected inborn errors of immunity in human patients using transcriptomic approaches paired with whole genomic sequencing.

Dr. Bharat Thyagarajan (Professor, Department of Laboratory Medicine and Pathology)
Dr. Thyagarajan is director of the Division of Molecular Pathology and Genomics, and a faculty investigator in the Advanced Research and Diagnostic Laboratory (ARDL). The MDL processes some 25,000 specimens annually related to inherited and infectious diseases, bone marrow engraftment and blood and solid tumor malignancies.  Thyagarajan and his MDL colleagues are implementing next-generation DNA sequencing (NGS) for diagnosing genetic disease.

The MDL has the capacity to test some 5,000 genes implicated in monogenic disorders with the goal of testing all the genes in the human genome (>20,000) and has implemented DNA sequence-based tumor diagnostics.  MDL clinicians have issued hundreds of patient molecular pathology reports based on individual genetic tests and expect that pace of reporting to increase as NGS technology is mainstreamed into clinical medicine. Thyagarajan’s team collaborates in this effort with the University of Minnesota Genomics Center, which produces the raw sequence from DNA extracted from clinical samples and the bioinformatics group at the Minnesota Supercomputing Center, which puts the raw sequence data in a readable format from which clinicians can interpret the diagnostic and prognostic value of genetic variants.

At ARDL, Dr. Thyagarajan is principal laboratory investigator for the Hispanic Community Health Study, an NIH-funded multicenter epidemiologic study of Hispanic/Latino populations, and the NIH-funded Long Life Family Study, an international collaborative study of the genetics and familial components of exceptional survival, longevity, and healthy aging. Thyagarajan’s personal research program focuses on the role of mitochondria in breast and colorectal cancer.

Dr. Kimberly VanderWaal (Assistant Professor, Department of Veterinary Population Medicine, College of Veterinary Medicine)
My research focuses on disease ecology, data analytics, network analysis and animal health. The goal of my research is to understand factors mediating pathogen transmission processes and to model the spread of animal diseases. In general, I strive to integrate methods and tools from multiple disciplines in order to investigate novel questions about pathogen transmission dynamics. Research areas include disease ecology, transmission processes at the wildlife-livestock interfaces, network modeling of livestock diseases using animal movement databases and Big Data approaches for advancing animal health.

Dr. Andrew Venteicher (Assistant Professor, Department of Neurosurgery, Medical School)
The Venteicher lab (venteicherlab.umn.edu) uses a combination of advanced genomics and computational approaches to study the tipping point when cells in neurodevelopment transform into cancer. We apply biochemistry, genomics and single cell approaches to patient tumor specimens and preclinical models to map these determinants of malignant transformation and to delineate features of epigenetic heterogeneity.  Using these approaches, we identify molecular signatures that serve as prognostic markers directly useful for patients as well as key pathways that conspire to promote tumorigenesis from previously normal cells.

Dr. Larry Wackett (Professor, Biochemistry, Molecular Biology and Biophysics)
The Wackett laboratory studies biocatalysis, genomics and web-based computational tools. Microbial enzymes are studied for their feasibility to degrade wastes or manufacture chemicals. Web-based databases have been developed for representing information pertaining to biocatalysis or biofuels. The former contains a tool for predicting metabolic pathways.

Dr. Trevor Wardill (Assistant Professor Ecology, Evolution and Behavior)
Dr. Wardill investigates information processing during visually guided behaviours in invertebrate species. The Wardill Lab studies how relevant information is extracted from visual scenes and used for appropriate behaviour.  For example, what are the general principles that neurons use for extracting motion, colour, shape and polarization. The lab aims to understand the neural basis for dynamic skin signaling in cephalopods and visual feature extraction in flies. 

The Wardill Lab use the model animal, Drosophila melanogaster to identify visual circuit components and then apply the knowledge gained (from genetic, physiology and behavioural experiments) to locate analogous circuits in other fly species, such as Spotted Wing Drosophila (Drosophila suzukii) and Killer flies (Coenosia attenuata). Taking this comparative approach allows us to reveal general principles of circuit function. The lab also investigates how cephalopods detect and express various forms of signals on their skin (movement, colour, pattern, polarization and 3D shapes). This research is currently in collaboration with Roger Hanlon at the Marine Biological Laboratory, Woods Hole, MA, USA. The lab uses advanced methods in genetics, 2-photon imaging and behavioural quantification and are seeking interest from PhD students.

Dr. Scott Wells (Professor, Veterinary Population Medicine Department, Ruminant Health)
Analytic epidemiologic studies related to the prevention and control of infectious diseases of cattle and other ruminants, including Mycobacterium avium subsp..paratuberculosis (Johne’s disease), Mycobacterium bovis (bovine tuberculosis), bovine leukemia virus and chronic wasting disease.  Includes monitoring and surveillance, herd prevalence estimation and testing, risk factor modeling, risk assessment and use of data from complex surveys."

Dr. Jesse Williams (Assistant Professor, Integrative Biology & Physiology)
My lab is interested in understanding the contribution of myeloid cells in the pathogenesis of metabolic and cardiovascular diseases, like atherosclerosis. We aim to determine mechanisms regulating the development and function of tissue-resident macrophages, as well as fate-decisions of circulating monocytes upon entry into inflamed tissues.

Dr. Ce Yang (Assistant Professor, Department of Bioproducts and Biosystems Engineering of Biomedical Informatics, Mayo Clinic)
Yang's research is to apply advanced ideas of robotics, remote sensing, data mining and information technology into the areas of plant high-throughput phenotyping and precision agriculture. The core techniques we use include multispectral/hyperspectral imaging, spectroscopy, machine learning, geographic information system (GIS), digital mapping, biochemical sensing, etc. The tools available for carrying out our researches are unmanned aerial vehicle, unmanned ground vehicle, video camera, multispectral camera, hyperspectral camera, DGPS and various electrical, optical and chemical sensors

Dr. Rui Zhang (Associate Professor, Department of Pharmaceutical Care & Health Systems, Institute for Health Informatics)
Dr. Zhang’s research focuses on the development of novel natural language processing (NLP) methods to analyze biomedical big data, including published biomedical literature, electronic health records (EHRs), patient-generated data from millions of patients. This research include: i) the secondly analysis of EHR data for patient care, ii) pharmacovigilance knowledge discovery through mining biomedical literature and iii) creation of knowledge base through database integration, terminology and ontology. Current projects in the lab include: i) developing NLP methods and applications to extract information from clinical reports; ii) mining biomedical literature to discover novel drug-supplement interactions through genetic pathways; iii) Repurposing existing drugs for COVID-19 treatment through link predictions and literature-based discovery; iv) developing computational methods to predict personalized cancer treatment caused cardiotoxicity in EHRs; v) developing conversational agent for consumers with developed knowledge base.

Dr. Abeer Madbouly (Senior Bioinformatics Scientist, Bioinformatics Research, CIBMTR)
Abeer Madbouly is a Senior Bioinformatics Scientist at the Center for International Blood and Marrow Transplant Research (CIBMTR). The CIBMTR is a collaboration between the bone marrow transplant outcomes registry at the Medical College of Wisconsin and the National Marrow Donor Program (NMDP). The NMDP operates the Be The Match Registry®, the world’s largest listing of potential marrow donors and donated cord blood units, helping thousands of patients diagnosed with blood cancers worldwide. Abeer’s research focuses on improving the matching process of donors and patients in need of a transplant. She is leading multiple research projects including ones to investigate the effect of genetics ancestry on survival after transplant and the incorporation of genetic analysis to improve the collection of ancestry information from donors that join the Registry. Abeer is also actively involved in multiple projects to help countries around the world start local marrow registries. Prior to joining the NMDP, Abeer was at Vanderbilt University Medical Center, where she was a bioinformatics Systems Engineer and the technical lead of the medical simulation lab at the Department of Anesthesiology. She received her Ph.D degree in Electrical and Computer Engineering from the University of Miami with research focus on Medical Imaging. Her research interests fall in the areas of bioinformatics, genetic ancestry, population genetics, immunology, data mining and machine learning. Currently, she is an active member of the American Society for Histocompatibility and Immunogenetics, the European Federation for Immunogenetics and the American Society of Human Genetics.

Dr. Susan Van Riper (Data Scientist, Best buy)
Dr. Susan Van Riper (Vice President of Data Science and Professional Services, Hopper Franklin)

I am an innovative Data and Data Science (Machine Learning and Artificial Intelligence) Leader. I provide thought leadership, vision creation, strategy (road mapping), architecture and implementation of the Data Science (Machine & Artificial Intelligence) end-to-end capabilities (people, process, technology, data). Whether starting from the ground up or accelerating Data Science practices, I lead the delivery of value through data.

With a background in machine learning, coupled with deep experience IT delivery management and engineering, I have a track record of leading value-based organizations and teams to deliver solutions. Teams utilize the latest technologies and process methodologies (Agile, SCRUM, SDLC, ISO delivery in a CI/CD) environment targeting various cloud and on-premise architectures. Known as a thought leader with a vision, an organization and team builder, technology and data translator and with an emphasis on value and a bias towards action.

Dr. Sara Vetter (Manager, Infectious Disease Laboratory, Minnesota Department of Health)
Public health is a dynamic interdisciplinary field that solves problems on a population level. In the infectious disease laboratory at the MN department of health, we monitor disease in our communities so we can know what pathogens are making people sick. We are sequencing many of the organisms isolated in our laboratory and are using bioinformatics tools to solve outbreaks, characterize strains of pathogens and look for antibiotic resistance.

Dr. Mandy Waters (Crop Bioinformatician, PepsiCo Global R&D)
Dr. Waters’ research focuses on unlocking flavor, nutritional and regenerative agronomic insights to improve raw ingredients for PepsiCo through development of bioinformatic/genomic tools. She currently works on the Agro Discovery team within PepsiCo R&D to deliver innovations in bioinformatic pipelines, genomic tools, genotyping technologies and gene discovery in plants with complex genomes. This work helps elucidate mechanisms that impact processing of raw materials and overall sensory satisfaction consumers obtain from Lays, Fritos, Cheetos, Doritos, Quaker Oats and Tropicana Juices.  Her work is cross-functional and global as it spans multiple crop species with varying ploidy levels and reproductive strategies and delivers critical technology unlocks in pathway elucidation, genomic breeding, gene-environment interactions and advances in agronomy and storage/processing practices.