Training Program

Training Program in Computational Biology and Bioinformatics at Columbia University 
(Supported by NIH grant 5T32GM082797-02, PI Dr. Barry Honig) 

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 is under the auspices on the Columbia 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:

SBI Graduate Program, Applied Physics and Applied Mathematics, Biological Sciences, Biochemistry and Molecular Biophysics, Biomedical Informatics, Chemistry, Computer Science, Electrical Engineering, Pharmacology, Statistics

For an overview of Computational and Systems Biology education at Columbia and for a list of courses see: Education 

Primary Training Program Faculty

Dimitris Anastassiou (Electrical Engineering) 
Bruce Berne (Chemistry)
Harmen Bussemaker (Biological Sciences) 
Andrea Califano (Biomedical Informatics)
Carol Friedman  (Biomedical Informatics) 
Richard Friesner (Chemistry) 
Barry Honig (Biochemistry and Molecular Biophysics)
George Hripcsak (Biomedical Informatics) 
Gail Kaiser (Computer Science) 
Diana Murray (Pharmacology) 
Liam Paninski (Statistics)
Dana Pe'er (Biological Sciences) 
Itsik Pe’er (Computer Science) 
Raul Rabadan (Biomedical Informatics) 
Ken Ross (Computer Science) 
Dennis Vitkup (Biomedical Informatics) 
Chris Wiggins (Applied Physics and Applied Mathematics) 
Tian Zheng (Statistics) 

Students Currently Funded by Training Grant 



Klara Felsovalyi (Biochemistry and Molecular Biophysics and Honig lab) is investigating protein-protein interactions between cadherins, a family of proteins which mediate cell-cell interactions, using both sequence and structural information. 



Sarah Gilman(Biomedical Informatics and Vitkup lab) is working 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. 



Lucas Ward (Biological Sciences and Bussemaker lab) is characterizing transcription factor colocalization hotspots in a variety of genomes, as well as developing methods to predict regulatory networks through cross-species analysis of transcription factor affinity.

Questions: Richard Friedman, C2B2/MAGNet Educational Coordinator, friedman [at] cancercenter.columbia.edu.