The graduate faculty of the BICB graduate program comes from eight institutions (University of Minnesota including Hormel Institute; Cray Inc.; IBM; Mayo Clinic; National Marrow Donor Program; Brain Sciences Center).
- University of Minnesota Faculty
- Mayo Clinic Faculty
- IBM Faculty
- National Marrow Donor Program (NMDP) Faculty
- Brain Sciences Center
- Other Affiliated Faculty
Dr. Frank Albert (Assistant 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 Amin laboratory's NIH/NIAID-funded research program focuses on CBRNE (chemical, biological, radiological, nuclear and explosive) agent mitigation, specifically Bacillus anthracis (the causative agent of anthrax), the ricin toxin, and organophosphate nerve gases such as sarin, soman, and VX. We bridge the fields of biochemistry and microbiology with computational sciences. Our main projects involve 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.
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. Joshua Baller (Research Informatics Scientific and Operations Lead, Minnesota Supercomputing Institute)
Dr. Baller's expertise in in the application of statistical modeling and machine learning to biological questions, analysis of high-throughput sequencing data, and the analysis of cytometric data. He received his Ph.D. from the BICB graduate program.
Dr. Ran Blekhman (Assistant Professor, Genetics, Cell Biol, Dev and Ecology, Evolution & Behavior, TCBS)
The Blekhman lab's broad focus is on Population, Evolutionary, and Medical Genomics in humans and other primates. The lab generates genomic data, and employs computational, statistical, network-theory, data mining, and population-genetic approaches, with the goal of achieving a comprehensive understanding of the genetic basis underlying specific complex traits and diseases. Current work in our lab aims to characterize the mechanism and evolutionary history of interactions between host and its associated microbiota.
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. 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. 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. 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. 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. 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. Yiannis Kaznessis (Professor, Department of Chemical Engineering and Materials Science)
Kaznessis' research efforts focus on synthetic biology. Combining theoretical and experimental work, Kaznessis and his group design small therapeutic molecules, such as antimicrobial peptides, and train bacteria to function like electronic circuits, such as bio-logical AND gates, bacterial comparators and proportional-integral-differential controllers. The work also entails the development of computational synthetic biology algorithms and software packages, like SynBioSS (synbioss.sourceforge.net).
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. James J. Lee (Assistant 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. Kelvin Lim (Professor, Department of Psychiatry)
Dr. Lim's research interest is the use of innovative magnetic resonance imaging techniques to study brain disorders. His primary focus has been the use of multiple modalities available with magnetic resonance to characterize the brain in schizophrenia, aging, traumatic brain injury and cocaine dependence.
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 HIV, HTLV and XMRV, a newly discovered human retrovirus associated with prostate cancer and chronic fatigue; Antiviral drug target identification; Antiviral drug resistance; HIV genetic variation, evolution and population genetics; Viral quasispecies; Virus 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. Sunil Kumar Mor (Assistant professor, department of veterinary population medicine and veterinary diagnostic laboratory, college of veterinary medicine)
Dr. Mor leads the Molecular Diagnostic Development Lab at the Veterinary Diagnostic Laboratory. This lab is focused on developing highly sensitive and specific molecular assays for rapid detection of emerging and zoonotic pathogens. His lab is also working on next generation sequencing using Illumina MiSeq for the last three years and recently started using Iseq, and Oxford Nanopore MinION for whole genome sequencing and disease diagnosis. Development, optimization and validation of molecular assays are routinely performed. Dr. Mor lab has developed three bio-informatics pipelines for pathogen detection, virus genome assembly and comparative genomics. These pipelines are being used from three years for analysis of metagenomic NGS samples, disease investigation and whole genome analysis.
Dr. Mor’s research interests are: (1) knowledge-based approaches to detect, control & prevent endemic, emerging & zoonotic pathogens (mainly viruses), and (2) pathogenesis of respiratory and enteric diseases that involve exploration of complex interactions among pathogen, host, and environment.
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. 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. Claudia Neuhauser (Professor Emeritus, Department of Ecology, Evolution and Behavior)
Dr. Neuhauser’s research is at the interface of mathematics and biology, and has ranged from studying the effect of competition on the spatial structure of competitors to the effect of symbionts on the spatial distribution of their hosts or the effect of virotherapy on clusters of cancer cells. Currently, her research is primarily in the area of bioinformatics and computational biology where she is developing statistical methods ranging from detecting genomic signatures of cancer and other complex diseases in next-generation sequencing data to building dynamic protein-protein networks based on flow cytometry data. She has a strong interest in furthering the quantitative training of biology undergraduate students, which has resulted in a textbook on Calculus for Biology and Medicine and a website with open statistics and mathematics resources that is hosted by BioQUEST
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. 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. Michael Sadowsky (Professor and Director, BioTechnology Institute)
Molecular plant-microbe interactions in nitrogen-fixing symbiotic systems, investigations of the use of microorganisms for biodegradation and bioremediation; molecular methods to determine sources and kinds of bacteria in the environment; and metagenomics of soil, water, and intestinal environments.
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. 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. Tim Starr (Assistant Professor, Department of Obstetrics, Gynecology and Women's Health)
Dr. Starr is focused on understanding the genetics of ovarian and colorectal cancer in order to develop more effective therapies. We are currently studying the functional role of several genes that we suspect are drivers of colorectal cancer, including CFTR, WAC, and TM9SF2. We use in vivo and in vitro assays to understand how these proteins contribute to cancer phenotypes. In ovarian cancer we are studying gene expression and mutation burden at the single cell level in fresh tissue samples we collect from patients undergoing surgical resection of their ovarian cancer. This work is part of a larger "precision medicine" effort to fully characterize ovarian cancer at the molecular level, with the hope of translating this knowledge into more effective therapies.
Dr. Robert Stupar (Associate Professor, Department of Agronomy and Plant Genetics)
Dr. Stupar's lab focuses on the molecular genetics of legume plant species, particularly soybean. Areas of interest include genome structural variation and genomic responses to breeding, mutagenesis and genetic transformation. Dr. Stupar’s research group also applies genomic strategies to gene identification/discovery and crop improvement. Traits of interest include abiotic stress responses and soybean seed composition.
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. 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 brain cancer. We apply biochemistry, genomics, and single cell approaches to patient tumor specimens and laboratory 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. Scott Wells (Professor and Division Head, Veterinary Public Health)
Epidemiologic studies related to the prevention and control of Mycobacterium aviumsubsp.paratuberculosis (Johne’s disease), Salmonella, and other manure-cycle pathogens, and to the prevention and eradication of Mycobacterium bovis (bovine tuberculosis) in cattle and other food-producing animals; Use of analytic epidemiologic methods directed towards control of economically important disease conditions in livestock and poultry, including monitoring and surveillance, herd prevalence estimation and testing, risk factor modeling, risk assessment, and use of data from complex surveys.
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. Rendong Yang (Assistant Professor, Laboratory of Computational Cancer Genomics, Hormel Institute)
Our laboratory is interested in the integrative analysis of large-scale, multi-dimensional genomic data to understand the initiation and progression of diseases. The research projects involve in the development of highly accurate and sensitive computational methods for analyzing large-scale genomic data, especially in the area of detecting and analyzing genetic variations and somatic mutations using next generation sequencing data. Current work in the lab is to explore the functional consequences of somatic alterations in cancer patients, to identify driver alterations, and to understand the genetic mechanisms of cancer progression and drug resistance by integrating multi-dimensional data from large-scale cancer studies such as The Cancer Genome Atlas (TCGA). Example projects span from technique-driven research that aims developing algorithms for a wide range of applications to hypothesis-driven investigation of specific biological problems where the main goal is the discovery and advancement of biological knowledge.
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. 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. Nicholas Chia (Assistant Professor of Biophysics, Head of the Theoretical Biology Group, Mayo Clinic)
Dr. Chia is currently heading the Theoretical Biology Group at Mayo Clinic. There, he is working with the Center for Individalized Medicine and the Department of Surgery as part of the UIUC-Mayo alliance in an effort to combine bioinformatics, ecological, and evolutionary theory with medicine. He is interested in a broad range of biological phenomena with emphasis on microbiology, ecology, and evolution. His focus includes studying how the microbiome influences human health and can be used as both a biomarker and a treatment as well as examining the role of collective effects and emergent properties in biological systems, with particular interest in the role of gene transfers and mobile genetic elements such as viruses, transposons, and plasmids.
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. Stephen Ekker (Professor, Biochemistry and Molecular Biology, Mayo Clinic Cancer Center)
The Ekker laboratory has pioneered the use of transposons and morpholino antisense oligonucleotides in zebrafish genetics to identify genes with important roles in clinically relevant processes. The Ekker lab has genome-wide efforts that cover processes including angiogenesis, sensory organ and kidney development, and nicotine response and sensitization.
Dr. Jung-Wei Fan (Assistant Professor, Department of Biomedical 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 collaborative scientist in Mayo Clinic's Bioinformatics Core, Steven N. Hart, Ph.D., focuses his research on the application of next-generation DNA sequencing analysis in large-scale sequencing projects, including several whole-genome, -exome and targeted custom capture sequencing projects for inherited cancer predisposition. Dr. Hart led the development of the GenomeGPS DNA sequencing workflow, the primary analytical pipeline for all genomic sequencing at Mayo Clinic. As associate director of bioinformatics for the Clinical Genome Sequencing Laboratory from 2015-2017, he oversaw genomics data processing for clinical practice and investigated the implications of genetic cancer predisposition testing and how to bring research findings into clinical practice. Of special interest are ongoing collaborations with the Department of Laboratory Medicine and Pathology, where Dr. Hart is developing artificial intelligence algorithms in the new subfield of digital pathology. In particular, he is interested in correlating genomic signatures with histologic features from H&E slides to decrease unnecessary testing procedures and identify patients who would benefit from genetic predisposition testing.
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. Guoqian Jiang (Associate Professor of Biomedical Informatics, Department of Health Sciences Research, Mayo Clinic)
Dr. Jiang conducts clinical informatics research mainly focusing on the study of data standards and interoperability, biomedical terminologies and ontologies, clinical information modeling, quality assurance of clinical study metadata and data models, standards-based phenotype models, and their applications in clinical and translational research and big data analytics. Current projects in his research program include 1) building quality assurance tools for cancer study common data elements and data models; 2) creating methods and tools for standardizing and harmonizing clinical research metadata; 3) developing standards-based electronic medical records-driven phenotype algorithms authoring and execution infrastructure and 4) advancing semantic interoperability of clinical and research applications leveraging Semantic Web technologies.
Dr. John Kalantari (Assistant Professor, Department of Surgery, Mayo Clinic)
Dr. Kalantari is an Assistant Professor in the Department of Surgery and the Center for Individualized Medicine at Mayo Clinic. His research focuses on novel applications of artificial intelligence to problems in biology and medicine with a specific focus on the development of algorithms and computational frameworks for probabilistic Bayesian machine learning, reinforcement learning, causal inference and complex adaptive system modeling. The mission of his research group, the Biomedical Artificial General Intelligence Lab (BAGIL), is to create AI/ML technologies that will transform medicine along two main fronts—predictive analytics for real-time decision feedback, and causal inference for preventive medicine. Among his current research efforts is the development of diagnostic and prognostic forecasting platforms that leverage experimental and clinical data for risk stratification, patient outcome prediction, and individualized causal treatment effect estimation.
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. 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. Hongfang Liu (Professor of Biomedical Informatics, Mayo Clinic Department of Health Sciences Research, Senior Associate Consultant in Biomedical Informatics)
Dr. Hongfang Liu's research focuses on i) improving the accessibility of information stored in unstructured text for systems biology and medicine research through natural language processing (NLP) ii) improving the semantic interoperability of different information sources through database integration, ontology, and semantic web techniques iii) bringing biomedical informatics research into practice through collaborations with systems biology and medicine researchers. Current projects in the lab include i) mining evidence of genetic mutations, splicing variations, and protein post-translational modification from literature ii) linking text semantics of genes and proteins with molecular database entries through biomedical ontology iii) advancing clinical NLP research and practice.
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. Yuan-Ping Pang (Professor, Pharmacology)
Explore how particular structures and atomic interactions underlie angiogenesis, apoptosis, metalloenzyme catalysis, and protein folding; develop molecular databases and scalable supercomputer hardware and software to facilitate the integration of biological data in order to understand how biological systems function; and use models of biological systems to develop therapeutics for treating cancers and emerging infectious diseases.
Dr. Kalyan S. Pasupathy (Associate Professor of Health Care Systems Engineering)
Dr. Kalyan S. Pasupathy is an expert in systems science and health informatics and is focused on both advancing the science and translating knowledge to improve care delivery, demonstrated through his academic and practice leadership roles. Dr. Pasupathy is the founding scientific director of the Mayo Clinic Clinical Engineering Learning Laboratories and has over 20 years of experience leading and pioneering efforts in improving complex care delivery systems. Notably, his work has impacted social service delivery at the American Red Cross and British Red Cross and within health care in nursing, pharmacy, surgery and emergency medicine. Dr. Pasupathy's team has won awards and created inventions that have been replicated. He has conducted several funded projects, has published over 70 peer-reviewed articles and a book on health informatics, serves as a scholarly reviewer for journals and federal agencies, and is frequently sought to consult or talk internationally.
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. Jeff A. Sloan (Professor of Biostatistics and Oncology, Professor of Health Science Research, Mayo Clinic)Research, Mayo Clinic)
Dr. Sloan, Ph.D., is Professor of Biostatistics and Oncology at the Mayo Clinic in Rochester, Minnesota. Dr. Sloan is also the Chair of the Quality of Life Research Initiative at the Mayo Clinic and the Health Outcomes Committee for the Alliance Cancer Research Group. Dr. Sloan was trained as a mathematical statistician, obtaining his doctorate from the University of Manitoba, Canada in 1991. He held appointments in the Faculty of Nursing at the University of Manitoba for 10 years before coming to the Mayo Clinic in 1995. He has over 25 years of experience as a statistical consultant and researcher into measurement issues and clinical trials.
Dr. Sloan is also the lead statistician for the Alliance NCORP Cancer Control Program. Other areas of emphasis have included phase I clinical trials, pediatric oncology, and lung cancer. Widely published with over 450 peer-reviewed citations, Dr. Sloan has focused recent research activities on methods of assessing quality of life (QOL) of cancer patients and other patient-reported outcomes. Determining a clinically meaningful difference in these measures, combining survival and toxicity endpoints, exploring the relationship between patient-reported outcomes and genetic makeup, and finding ways to facilitate the incorporation of patient-reported outcomes into clinical practice have been specific areas of interest within the past two years. Most recently Dr. Sloan’s research demonstrating that simple single item measures of patient QOL domains are prognostic for survival has led to their routine incorporation into oncology clinical practice for every patient visit at Mayo.
Dr. David I. Smith (Professor, Department of Laboratory Medicine and Pathology, Mayo Clinic)
Dr. Smith's laboratory utilizes the latest technological tools to better understand the molecular alterations that underly the development of cancer. Dr. Smith's laboratory then focuses on two main areas: (1) the role that long non-coding transcripts play in the development of cancer; and (2) using Next Generation sequencing to develop better clinical strategies for the treatment of head and neck cancer. He is also the Chairman of the Technology Assessment Group which is responsible for the evaluation of new technologies for their potential impact on both basic and translational research.
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. 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. Yung-Tsi Bolon (Principal Scientist, Laboratory Services)
Dr. Bolon is the Principal Scientist and Research Lead for the Laboratory and Biorepository Services department at the National Marrow Donor Program (NMDP). She holds a Ph.D. in Biochemistry, Molecular Biology, and Biophysics and is a research scientist/teacher/mentor in molecular biology, biochemistry, and genomics fields involving bioinformatics data analyses and computational applications. At NMDP, she investigates scientific and technical concepts related to histocompatibility and immunogenetics research for translation into actionable policies, systems, and tools for the NMDP and the Be The Match Registry®. In this role, she partners with internal and external Laboratory, Research, Bioinformatics and Information Technology teams to develop protocols, pipelines, and databases for research and incorporation into operations. Her projects include the addition of Next Generation Sequencing (NGS)-derived genotyping results for HLA loci and blood type to the Be The Match Registry® at the time of donor recruitment to accelerate efficient donor selection and timely transplantation for patients. NGS technologies along with samples from donors of diverse racial and ethnic backgrounds are leveraged to examine the suitability of sample types, the efficacy of NGS methods, and the correlation rate between phenotype and genotype for testing strategies. The discovery and incorporation of signature genetic variants and frequencies are key to optimizing genotype and phenotype prediction algorithms and for effective translation of results to end users in the field of stem cell transplantation.
Dr. Robert Milius (Senior Data Analyst, Bioinformatics Research)
Dr. Milius' work is focused on biomedical informatics data standards and tool development. The NMDP Bioinformatics Research group advances translational medicine, including stem cell therapeutics, using informatics to study immunology, histocompatibility, and population genetics. Two of our most important resources are the BeTheMatch registry of potential stem cell donors, and CIBMTR's Outcomes Database. These databases have been decades in the making, and includes data generated by methods evolving over the years, from serology to DNA based typing methods, and gathered from all over the world. As technology continues to improve (e.g., NGS methods) and our understanding of the complexities of the biology increases, it has become increasingly important to 'future-proof' these data for reinterpretation in light of new knowledge. Key to this is the development of standards for data exchange that foster semantic and syntactic interoperability. This includes full understanding of the methodologies used to generate the data, and the nomenclature, vocabulary, and rules to curate the data. We reuse current standards and participate in their further development whenever possible (e.g., BRIDG and LS-DAM domain models, existing vocabularies and ontologies, caDSR data standard repositories, NCBI Genetic Testing Registry, and HL7 messages, documents, and information models). We also develop our own standards when necessary, such as the Histoimmunogenetics Markup Language (a XML based reporting format for HLA and KIR typing data), and GL String (grammar to represent full allele and genotype ambiguity in a text string). In addition to standards development, we develop tools that "make the right thing to do, the easy thing to do." Tool development has focused on RESTful web services that can be incorporated into both research and clinical workflows.
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. 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.
Dr. Mark Brown (Senior Principal Scientist | Medtronic, Inc.)
Dr. Brown's research focuses on applying signal processing methods for discrimination to provide diagnostic and therapeutic decisions in implantable medical devices. He is also interested in methods for determining patient risks for disease progression or cardiac event for the purpose of selecting appropriate populations to receive medical devices. He also is interested in sensors that can be used as direct or surrogate measures of patient medical status for improved patient care.
Dr. Caleb Kennedy (Director, Bioinformatics, United Health Group)
Dr. Kennedy active research areas are high-throughput (next-generation) DNA sequencing, web- and cloud-based delivery of new histocompatibility biomarkers, machine learning, and data mining. Caleb’s experience in the biotechnology industry includes positions at Thermo Fisher Scientific (formally Life Technologies), Good Start Genetics, and the Massachusetts Institute of Technology. He is particularly interested in helping students who may want to cross over from academic research to commercial application. Caleb holds BS and MS degrees in molecular and cellular biology from Texas A&M University and a PhD in genetics from Harvard University.
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. Van Riper's research comprises computational methods for mass spectrometry based proteomics and metabolomics. The overarching goal of this research is to improve repeatability and reproducibility of data generated via mass spectrometry based analysis of complex biological samples. This research has broad applications, including studies in protein and peptide phosphorylation during in vitro tissue growth, glucose metabolism, and oral cancer progression.
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.