Bioinformatics | Research Interests

Name	Email	PhD Program
Schrider, Daniel WEBSITE EMAIL PUBLICATIONS	PHD PROGRAM Bioinformatics & Computational Biology RESEARCH INTEREST Bioinformatics, Computational Biology, Evolutionary Biology, Genetics, Genomics	The Schrider Lab develops and applies computational tools to use population genetic datasets to make inferences about evolutionary history. Our research areas include but are not limited to: characterizing the effects natural selection on genetic variation within species, identifying genes responsible for recent adaptation, detecting genomic copy number variants and other weird types of mutations, and adapting machine learning tools for application to questions in population genetics and evolution. Study organisms include humans, the fruit fly Drosophila melanogaster and its relatives, and the malaria vector mosquito Anopheles gambiae.
Hoadley, Katherine A. WEBSITE EMAIL PUBLICATIONS	PHD PROGRAM Genetics & Molecular Biology RESEARCH INTEREST Bioinformatics, Cancer Biology, Computational Biology, Genetics, Genomics	My research interest is in genomic characterization and integrative genomic approaches to better understand cancer. My group is part of the NCI Genome Data Analysis Center focused on RNA expression analysis. We have a number of ongoing projects including developing molecular classifications for potential clinical utility, developing methods for deconvolution to understand bulk tissue heterogeneity, analysis of driver negative cancers, and analysis of ancestry markers with cancer features.
Jiang, Yuchao WEBSITE EMAIL PUBLICATIONS	PHD PROGRAM Bioinformatics & Computational Biology RESEARCH INTEREST Bioinformatics, Cancer Biology, Computational Biology, Genomics	Dr Jiang’s primary research interests lie in statistical modeling, method development and data analysis in genetics and genomics. His current research is focused on developing statistical methods and computational algorithms to better utilize and analyze different types of next-generation sequencing data under various setting, with application to data from large-scale cohort studies of human health and disease. Special focus is on single-cell transcriptomics, single-cell epigenomics, cancer genomics, tumor phylogeny, data normalization, and copy number variation detection.
Ward-Caviness, Cavin WEBSITE EMAIL PUBLICATIONS	PHD PROGRAM Bioinformatics & Computational Biology, Toxicology RESEARCH INTEREST Bioinformatics, Computational Biology, Genomics, Systems Biology, Translational Medicine	We are actively engaged in multiple research arenas centered around understanding the associations between environmental exposures (primarily air pollution) and health outcomes. We use large clinical cohorts and electronic health records to understand associations between air pollution and health outcomes such as cardiovascular disease, metabolic disease, and aging. We use metabolomics and epigenetic data (primarily DNA methylation) to investigate molecular mechanisms, and highlight the integration of ‘omics data in a systems biology framework to better understand dysregulated pathways. Finally, we have projects centered around methods development and causal analyses to improve our understanding of the biology central to environmental health effects.
Liu, Yufeng WEBSITE EMAIL PUBLICATIONS	PHD PROGRAM Bioinformatics & Computational Biology RESEARCH INTEREST Bioinformatics, Computational Biology	Statistical machine learning and data mining, nonparametric statistics and functional estimation, bioinformatics, design and analysis of experiments
Wu, Di WEBSITE EMAIL PUBLICATIONS	PHD PROGRAM Bioinformatics & Computational Biology RESEARCH INTEREST Bioinformatics, Cancer Biology, Computational Biology, Genomics, Translational Medicine	Our group develops novel statistical bioinformatics tools and applies them in biomedical research to help understanding the precision medicine for cancer (e.g., breast cancer and lung cancer) subtypes, the disease associated integrative pathways across multiple genomic regulatory levels, and the genetics based drug repurposing mechanisms. Our recent focus includes pathway analysis, microbiome data analysis, data integration and electronica medical records (EMR). Our application fields include cancer, stem cell, autoimmune disease and oral biology. In the past, we have developed gene set testing methods with high citations, in the empirical Bayesian framework, to take care of small complex design and genewise correlation structure. These have been widely used in the microarray and RNAseq based gene expression analysis. Contamination detection for data analysis for Target DNA sequencing is work in progress. Recently, we also work on single cell sequencing data for pathway analysis with the local collaborators.
Gordon-Larsen, Penny WEBSITE EMAIL PUBLICATIONS	PHD PROGRAM Nutrition, Pathobiology & Translational Science RESEARCH INTEREST Behavior, Bioinformatics, Cardiovascular Biology, Genetics, Molecular Biology	Gordon-Larsen’s work integrates biology, behavior, and environment to understand, prevent and treat obesity, cardiovascular and cardiometabolic diseases. She works with biomarker, microbiome, metabolome, genetic, weight, diet, and environment data using multilevel modeling and pathway-based analyses. She works with several longitudinal cohorts that span more than 30 years. Most of her work uses data from the US and China. Her research teams include a wide variety of scientists working in areas such as genetics, medicine, bioinformatics, biostatistics, microbiology, nutrition, and epidemiology.
Gomez, Shawn WEBSITE EMAIL PUBLICATIONS	PHD PROGRAM Bioinformatics & Computational Biology RESEARCH INTEREST Bioinformatics, Cancer Biology, Cell Signaling, Computational Biology, Systems Biology	Our primary research is in the area of computational systems biology, with particular interest in the study of biological signaling networks; trying to understand their structure, evolution and dynamics. In collaboration with wet lab experimentalists, we develop and apply computational models, including probabilistic graphical and multivariate methods along with more traditional engineering approaches such as system identification and control theory, to current challenges in molecular biology and medicine. Examples of recent research projects include: prediction of protein interaction networks, multivariate modeling of signal transduction networks, and development of methods for integrating large-scale genomic data sets.
Dayan, Eran WEBSITE EMAIL PUBLICATIONS	PHD PROGRAM Neuroscience RESEARCH INTEREST Bioinformatics, Neurobiology, Systems Biology, Translational Medicine	Our lab studies brain network connectivity in the healthy brain and in neurological and neuropsychiatric patient populations. We focus on the organizational, dynamical, and computational properties of large-scale brain networks and determine how these properties contribute to human behavior in health and disease. We strive to advance the basic understanding of brain structure and function, while making discoveries that can be translated to clinical practice.
Carter, Charles WEBSITE EMAIL PUBLICATIONS	PHD PROGRAM Biochemistry & Biophysics, Bioinformatics & Computational Biology RESEARCH INTEREST Biochemistry, Bioinformatics, Biophysics, Computational Biology, Molecular Biology, Structural Biology	Molecular evolution and mechanistic enzymology find powerful synergy in our study of aminoacyl-tRNA synthetases, which translate the genetic code. Class I Tryptophanyl-tRNA Synthetase stores free energy as conformational strain imposed by long-range, interactions on the minimal catalytic domain (MCD) when it binds ATP. We study how this allostery works using X-ray crystallography, bioinformatics, molecular dynamics, enzyme kinetics, and thermodynamics. As coding sequences for class I and II MCDs have significant complementarity, we also pursuing their sense/antisense ancestry. Member of the Molecular & Cellular Biophysics Training Program.

Research Interest: Bioinformatics