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Computational Biology

About

computational Biology Image-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

  • Agaisse, Hervé

    Genetic approaches, cellular and molecular biology of intracellular pathogen infection

  • Bajikar, Sameer Subhash

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

  • Bekiranov, Stefan

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

  • Bochkis, Irina

    Epigenetic and genetic mechanisms underlying metabolic disease

  • Bourne, Philip E

    Data Science

  • Campbell, John

    The Neurobiology of Energy Balance

  • Condron, Barry G.

    Regulation and Function Serotonergic Neurons During Development

  • DeSimone, Douglas W.

    Cell Adhesion and Adhesion-Dependent Cell Signaling in Vertebrate Morphogenesis

  • Dolatshahi, Sepideh

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

  • Fallahi-Sichani, Mohammad

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

  • Farber, Charles R.

    Systems Genetics of Skeletal Development and Maintenance

  • Ford, Roseanne M.

    Bacterial attachment and biofilms, microbial transport in porous media

  • Janes, Kevin A.

    Systems-biology approaches to cancer biology and virology.

  • Kasson, Peter M.

    Physical mechanisms of infectious disease; influenza infection; membrane fusion; antibiotic resistance; molecular dynamics simulation; machine learning.

  • Li, Hui

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

  • Loughran, Jr., Thomas P

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

  • Manichaikul, Ani W.

    Statistical Genetics, Genetic Epidemiology, Biostatistics, Network analysis

  • Meliza, C. Daniel

    Neural Mechanisms of Pattern Learning and Recognition in the Auditory System

  • Miller, Clint L.

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

  • Naegle, Kristen

    Regulation and function of tyrosine phosphorylation in complex networks

  • Papin, Jason A.

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

  • Peirce-Cottler, Shayn M.

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

  • Platig, John H

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

  • Ratan, Aakrosh

    Genomics, Molecular Evolution, Algorithm Design and Analysis

  • Saucerman, Jeffrey J.

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

  • Sheffield, Nathan

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

  • Sheynkman, Gloria M.

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

  • Swiatecka-Urban, Agnieszka

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

  • Syed, Sana

    Understanding why a subset of children living in in low- and middle-income countries around the world develop growth and vaccine failure. Investigating the causes and progression of inflammatory enteropathies of the gastrointestinal lumen. Integrating data science-driven approaches with medicine to drive precision medicine.

  • Trinh, Bon Q

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

  • Woodfolk, Judith A.

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

  • Yang, Yaohua

    Genetic and Molecular Epidemiology; Cancer; Human Microbiome

  • Zang, Chongzhi

    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 biophysic