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Tri-Institutional Training Program in Computational Biology and Medicine

$319,295T32FY2015GMNIH

Weill Medical Coll Of Cornell Univ, New York NY

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Abstract

DESCRIPTION (provided by applicant): The Tri-Institutional Training Program in Computational Biology and Medicine (CBM) takes advantage of the outstanding educational and research resources of Cornell University in Ithaca, NY, the Weill Cornell Medical College in New York City, and the Sloan-Kettering Institute (the research arm of the Memorial Sloan-Kettering Cancer Center) to train computational biologists in the interdisciplinary approaches they need to solve the complex problems that characterize biology and medicine. The CBM training environment is designed to address the unique challenges of training scientists in this area and is characterized by: coursework in both quantitative and biological sciences; research rotations to enable a well-informed thesis topic selection; trainee Research-in-Progress seminar series to enhance program cohesion and foster fluency in relevant disciplines; thesis research in one of a diverse array of basic to translational computational and experimental laboratories; both quantitative and biological mentorship to ensure training balance and breadth; and encouragement to engage in hybrid computational/experimental projects to foster connections between theory and experiment. A theme underlying all program components is trainee exposure to diverse approaches and areas of computational biology, a reflection of the fact that interdisciplinary approaches are invaluable for solving many problems in biology and medicine today. The program, which is well established in its 10th year, has an expanding record of training success. With this competitive renewal proposal, we are requesting an increase from 6 to 12 T32 slots, which we believe is justified by the deep pool of highly qualified training-grant eligible applicants, large array of cutting-edge thesis research opportunities with leading faculty scientists, and the training enrichment that is inherent to an increased critical mass of students. The requested T32 funding would greatly aid the CBM program in continuing to achieve its mission of training the next generation of scientists to use computational and analytical methods to solve complex problems in biology. It is our belief that the development of such a cadre of computational biologists will foster discovery in frontiers of basic biological and biomedical sciences.

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