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Computational Biology

Biomedical Sciences Graduate Program

About

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Research in Computational Biology at UVA uses mathematical and computational techniques to analyze, explain, and predict biological systems.The past years have brought a dramatic increase in the amount of experimental data generated by high-throughput sequencing, proteomics, metabolic and gene expression profiling, and structural techniques. Simultaneously, the computational power we have available has continued to increase exponentially.  We thus have huge data sets at our disposal coupled with the ability to make increasingly sophisticated analyses.

Computational biology at UVA includes cutting-edge research in computational biophysics, genomics, computational structural biology, and computational systems biology.  Our work is focused on addressing fundamental biological questions and understanding diseases of medical relevance, such as cancer, cardiovascular disease, lung infections in cystic fibrosis, drug-resistant bacterial infections, and influenza.

In addition to analyzing biological systems, many laboratories at UVA combine computational and experimental work, using sophisticated tools to analyze biomolecular behavior and then verifying predictions in the lab.

Faculty

Genetic approaches, cellular and molecular biology of intracellular pathogen infection

Systems biology approaches to study gene dosage in neurodevelopment and neurodevelopmental disorders

Computational Biology; Bioinformatics; Precision Medicine; Machine Learning/AI; Quantum Computing

The Neurobiology of Energy Balance

Statistical genetics and genomics.

Computational genomics and bioinformatics; long-read sequencing; structural variation; genome assembly and pangenomics; human genetic variation and disease genomics

Computational Biology; Machine Learning; Statistical Modeling; Single Cell Biology; Spatial Biology; Liquid Biopsy

Regulation and Function Serotonergic Neurons During Development

Cell Adhesion and Adhesion-Dependent Cell Signaling in Vertebrate Morphogenesis

Uncovering the molecular etiology of neurodegenerative diseases

Systems Immunology, Cancer Systems Biology, , Neonatal and Maternal Immunology

Cancer systems biology, Single-cell quantitative biology, Computational modeling

Systems Genetics of Skeletal Development and Maintenance

Bacterial attachment and biofilms, microbial transport in porous media

Systems-biology approaches to cancer biology and virology.

Gene regulation in cancer, RNA processing; Epigenetic modification; Stem cell and development

Hematologic malignancies; bone marrow disorders; leukemia; large granular lymphocyte (LGL)

Statistical Genetics, Genetic Epidemiology, Biostatistics, Network analysis

Neural Mechanisms of Pattern Learning and Recognition in the Auditory System

Genetic variation, Complex diseases, Coronary artery disease, Genomics, Epigenomics, Regulatory mechanisms, Vascular biology, Pharmacology and Physiology

Regulation and function of tyrosine phosphorylation in complex networks

Understanding the neural code underlying motivated behaviors like feeding, drinking, and social interaction, with a focus on how malfunction in associated brain areas are involved in diseases like addiction and eating disorders

Obesity and Aging

Systems biology, infectious disease, cancer, toxicology, metabolic engineering

Tissue Engineering and Regeneration, Computational Systems Biology, Vascular Growth and Remodeling, Stem Cell Therapies

Gene regulatory networks, Systems genetics, Multi-omic data integration, Network science

The Proctor Laboratory integrates systems biology with molecular, cellular, and systems neuroscience into a cutting-edge framework for investigation of multi-scale mechanisms of Alzheimer's disease risk, onset, and progression.

Genomics, Molecular Evolution, Algorithm Design and Analysis

Roles of complex signaling networks involved in the regulation of cardiovascular function and disease

computational biology & bioinformatics; high performance computing; epigenomics & chromatin; pediatric cancer; computational regulatory genomics; machine learning

Proteoform Systems Biology: proteogenomic approaches to uncover the role of proteomic variation in human disease

Regulation of cell-surface stability and intracellular trafficking of membrane proteins in epithelial cells

Understanding Protein and RNA regulations of gene expression via chromatin structure in myeloid cell development and diseases

The immune response to common cold and allergens in health and disease.

Researching fundamental roles of the epigenome in control of the context-specific transcriptional programs.

Genetic and Molecular Epidemiology; Cancer; Human Microbiome

Bioinformatics methodology development; Epigenetics and chromatin biology; Transcriptional regulation; Cancer genomics and epigenomics; Statistical methods for biomedical data integration; Advanced machine learning; Theoretical and computational biophysics

Genetics, Functional Genomics, Epigenetics, Lung repair/regeneration, Metabolic regulation, Alveolar stem cells, Chromatin interaction, Innate immune response, Live-cell imaging