Faculty are listed in alphabetical order by last name. To see more information about a faculty member, click on his/her name.
Colin BarnstableHow interacting networks of transcription factors and signal transduction molecules guide the development of precursor/stem cells into mature neurons. Role of these networks in neurodegenerative diseases. Factors that can act as neuroprotective agents.
Professor and Chair, Neural & Behavioral Sciences
Co-Chair of the Graduate Program in Neuroscience
Philip BevilacquaRoles of RNA-binding proteins in plant physiology. Plant ribonomics. Identification and characterization of functional RNAs in plants.
Distinguished Professor of Chemistry and Biochemistry and Molecular Biology
Co-Director, Center for RNA Molecular Biology
Santhosh GirirajanThe primary focus of my research is to discover and characterize genetic changes including genomic deletions and duplications and single nucleotide mutations contributing to neurodevelopmental disorders such as autism, developmental delay and congenital malformation.
Assistant Professor of Biochemistry & Molecular Biology
Assistant Professor of Anthropology
Mark GuiltinanPlant molecular and developmental biology. Starch biosynthesis. Tropical plant biotechnology. Plant-pathogen interactions. Biofuel feedstock production.
Professor of Plant Molecular Biology, Department of Plant Science
Director, Endowed Program in the Molecular Biology of Cocoa
Molly HallMy research is focused on building tools to elucidate the complex genetic and environmental underpinnings of human disease. My lab works to integrate genetic (genotype, sequence, structural variation) and exposure (derived from surveys and metabolomics methods) big data to predict disease status. The ultimate goals of this work are to 1) enrich our understanding of the complex mechanisms that lead to common disease and 2) provide methods to identify those most at risk of disease (based on their genetic and exposure backgrounds) in a clinical setting.
Assistant Professor, Veterinary and Biomedical Sciences
Vasant Gajanan HonavarStatistical machine learning algorithms for predictive modeling from big data (large, distributed, semantically disparate data, partially specified data, richly structured (sequence, relational, network) data); Causal inference from experimental and observational data; Information Integration (logical, probabilistic, and network-based approaches); Characterization and prediction of protein-protein, protein-RNA, and protein-DNA interactions, protein sub-cellular localization, B-cell and T-cell epitopes, and other functionally important sites of protein; Automated protein structure and function annotation; Modeling and inference of biological networks; Comparative analyses of biological networks (network alignment); Biomedical Ontologies; Integrative modeling of patients from electronic medical records, genetic, physiological, environmental and lifestyle data for personalized interventions.
Professor and Edward Frymoyer Chair of Information Sciences and Technology
Vivek KapurResearch in my Laboratory seeks to define the basic mechanisms by which pathogenic microbes successfully infect, colonize, and cause disease in their hosts. The research effort is organized along two thematic lines:
Associate Director for Strategic Initiatives, Huck Institutes of the Life Sciences
Professor of Veterinary and Biomedical Sciences
Qunhua LiMy primary research interests concern developing statistical methods for uncovering complicated patterns in large and complex biological data. I have been developing latent variable models (e.g. mixture models, copula models) and machine learning techniques (e.g. clustering or classification) to identify and infer scientifically meaningful structures from high-throughput genomic and proteomic data.
Assistant Professor of Statistics
Lynn LinMy research interests include a range of related problems in Bayesian mixture model development for classification, variable selection, design and model selection, structured and hierarchical non-parametric Bayesian methods, rare event detection, and statistical computation involving simulation and optimization.
Asst. Professor, Statistics
Yanxi LiuComputational Symmetry Group Theory and Applications, Machine Learning (particularly low-dimensional subspace learning from very large, multi-modality feature set), Computer-Aided Diagnosis, Computer Vision, Computer Graphics.
Professor of Computer Science and Engineering and Electrical Engineering
Wansheng LiuStructural, functional and comparative genomics of the mammalian Y‐chromosome; characterization of Y-chromosome variations and their application in male health, fertility, and reproduction in cattle and other livestock species; function of the PRAME/PRAMEY gene family during spermatogenesis in cattle and mice
Associate Professor of Genomics
Paul MedvedevDeveloping rigorous algorithms and analysis for problems in the biological sciences. Genome assembly, variation detection, cancer genomics, phylogenetics, graph theory, computational complexity, on-line algorithms, and networking.
Assistant Professor of Computer Science and Engineering
Assistant Professor of Biochemistry and Molecular Biology
Rongling WuHe is particularly interested in integrating the idea and principle of systems biology into statistical genetic research, ultimately elucidating a comprehensive atlas of the genetic control network of complex biology.
Professor, Division of Biostatistics
Director, Center for Statistical Genetics
Feng YueStudy the function of non-coding variant in the human genome and how they contribute to diseases such as cancer Cancer epigenomics: investigate epigenetic marks for certain types of cancer with a hope that it may eventually contribute to drug discovery Study the 3D structure of the genome organization by 5C/Hi-C, in particular the interactions between enhancers and their target gene promoters Comparative genomics: investigate the evolutionary landscape of cis-regulatory elements in the mammalian genome
Assistant Professor, Biochemistry & Molecular Biology