The objective is to support a Computational Systems Biology training program (CSBTP) to train students to become leaders in biomedical research at the interface of biology, computation and engineering. The effort is centered in MIT's interdisciplinary predoctoral training program in Computational and Systems Biology (CSB), which is the primary training program at MIT for students interested in computational and systems biology and is the only program that emphasizes interdisciplinary training and research in the field. Program faculty are concentrated in the three founding departments ? Biological Engineering (BE), Biology, and Electrical Engineering & Computer Science (EECS) ? with additional involvement of faculty from other departments. Research interests of training faculty span a wide range of CSB-related areas, including Regulatory Genomics and Proteomics, Precision Medicine and Medical Genomics, Molecular Biophysics and Structural Biology, Biological Networks and Machine Learning, and Cancer Systems Biology. This proposal seeks to expand the pool of training faculty significantly, including 7 faculty newly hired in the past 5 years who have active research programs in the field. Students apply directly to the CSB Ph.D. program from their undergraduate or Master?s institution and receive multi- and inter-disciplinary training in the field of computational and systems biology. The proposal seeks funding for 10 predoctoral traineeships per year, enabling extended research rotations and participation in special program activities. Unique aspects of the program include: (a) unusually diverse collection of research areas across science and engineering, with highly collaborative interdisciplinary faculty; (b) a unique core of interdisciplinary classroom subjects that combine biology, engineering, statistics and computation; (c) intensive advising and multi-disciplinary thesis committees to optimize the training experience for students from diverse academic backgrounds; (d) an annual retreat with participation of students and faculty focusing on research, careers, and challenges to interdisciplinary research.
Biological discovery is increasingly driven by large-scale generation and analysis of biomedical data, enabled by new technologies for sequencing, imaging and manipulating biological systems. We propose to train scientists who have interdisciplinary expertise in concepts, approaches and technologies from biology, computer science, and engineering. These scientists will be well positioned to apply sophisticated technologies and advanced modeling techniques to design and predict sites of intervention in complex gene networks to achieve desired therapeutic aims in complex diseases such as diabetes and cancer, and to help realize the potential of precision medicine.
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