Training Program in Computational Biology and Bioinformatics
Supported by NIH grant 5T32GM082797-02
Principal investigator: Barry Honig, PhD
The Training Program in Computational Biology and Bioinformatics at Columbia University offers interdisciplinary training that includes coursework in quantitative studies (computation, statistics, and/or physics), life sciences, and computational biology and bioinformatics, with mentored research in computational systems and structural biology.
The program operates under the auspices on the Center for Computational Biology and Bioinformatics (C2B2) and its affiliated National Center for Multiscale Analysis of Cellular and Genomic Networks (MAGNet). Doctoral students funded by the training program may pursue their degrees in any of the following departments and programs:
C2B2 Graduate Program, Applied Physics and Applied Mathematics, Biological Sciences, Biochemistry and Molecular Biophysics, Biomedical Informatics, Chemistry, Computer Science, Electrical Engineering,Pharmacology, Statistics.
Primary Training Program Faculty
Dimitris Anastassiou (Electrical Engineering, Systems Biology)
Harmen Bussemaker (Biological Sciences, Systems Biology)
Andrea Califano (Systems Biology, Biomedical Informatics, Biochemistry and Molecular Biophysics)
Virginia Cornish (Chemistry, Systems Biology)
Aris Floratos (Systems Biology, Biomedical Informatics)
Carol Friedman (Biomedical Informatics)
Richard Friesner (Chemistry)
Barry Honig (Systems Biology, Biochemistry and Molecular Biophysics)
George Hripcsak (Biomedical Informatics)
Gail Kaiser (Computer Science)
Arthur Palmer (Biochemistry and Molecular Biophysics)
Dana Pe'er (Biological Sciences, Systems Biology)
Itsik Pe’er (Computer Science, Systems Biology)
Raul Rabadan (Systems Biology, Biomedical Informatics)
Sagi Shapira (Systems Biology, Microbiology and Immunology)
Lawrence Shapiro (Biochemistry and Molecular Biophysics, Systems Biology)
Yufeng Shen (Systems Biology, Biomedical Informatics)
Peter Sims (Systems Biology, Biochemistry and Molecular Biophysics)
Nicholas Tatonetti (Biomedical Informatics, Systems Biology)
Saeed Tavazoie (Systems Biology, Biochemistry and Molecular Biophysics)
Dennis Vitkup (Systems Biology, Biomedical Informatics)
Harris Wang (Systems Biology, Pathology and Cell Biology)
Chris Wiggins (Applied Physics and Applied Mathematics, Systems Biology)
Chaolin Zhang (Systems Biology, Biochemistry and Molecular Biophysics)
Joshua Broyde (Honig and Califano labs) is using computational structural biology methods and systems biology tools to elucidate signal trasduction pathways and gene regulatory networks downstream of the Kras oncogene.
Albert Lee (Rabadan Lab) is developing an efficient method for generating reference transcriptomes for species in which deadly viruses and drug-resistant pathogens originate. Doing so will provide opportunities for studying differences in RNA abundance between species, tissues, or disease states, as well as reliable computational and statistical frameworks for the analysis and interpretation of genomic high-throughput data.
Cameron Palmer (Integrated Program and Itsik Pe'er lab) is developing statistical methods for incorporating complexity in association studies.
Chaitanya Rastogi (Bussemaker Lab) is developing methods to incorporate methylation data and DNA shape readout into SELEX-seq. This will allow researchers to quantify how changes in DNA shape caused by epigenetic factors such as cytosine methylation contribute to variations in binding affinity.
James Chen (Genetics & Development and Califano lab) developed algorithms that integrate high-throughput genetic and genomic data to identify novel roles for genes in the differentiation of invasive and aggressive cancer subtypes, and then worked to validate predictions within biological contexts.
Mina Fazlollahi (Physics and Bussemaker lab) focused on inferring the transcriptional and post-transcriptional network structure by using natural sequence variation and linkage analysis.
Sarah Gilman (Biomedical Informatics and Vitkup lab) worked on integrating disease phenotype with molecular network information by developing new computational methods of predicting disease genes and interpreting the results of Genome Wide Association Studies (GWAS) in the context of molecular networks.
Mariam Konate (Pharmacology and Vitkup lab) is working on understanding the evolution of protein molecular function. She is developing methods to predict enzyme function based on combined structural and genomic context information.
Klara Felsovalyi (Biochemistry and Molecular Biophysics and Honig lab) investigated protein-protein interactions between cadherins, a family of proteins which mediate cell-cell interactions, using both sequence and structural information.
Lucas Ward (postdoc, Manolis Kellis Lab, MIT) studied tissue-specific chromatin structure and gene expression.