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Graduate Training in Computational and Systems Biology

Graduate Training in Computational and Systems Biology
计算和系统生物学研究生培训
批准号:
10681214
负责人:
CHRISTOPHER B BURGE
金额:
$53.05万
依托单位国家:
美国
项目类别:
财政年份:
2009
资助国家:
美国
项目状态:
已结题
起止时间:
2009-07-01 至 2024-06-30

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中文摘要
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英文摘要
Project Summary 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.
期刊论文(100)
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会议论文
DOI: 10.1016/j.crmeth.2022.100254
发表时间: 2022-07-18
期刊: Cell reports methods
影响因子: --
作者: []
通讯作者:
DOI: 10.1101/gr.184390.114
发表时间: 2015-06
期刊: Genome research
影响因子: 7
作者: [Wang ET, Ward AJ, Cherone JM, Giudice J, Wang TT, Treacy DJ, Lambert NJ, Freese P, Saxena T, Cooper TA, Burge CB]
通讯作者: Burge CB
DOI: 10.1371/journal.pcbi.1008605
发表时间: 2021-01
期刊: PLoS computational biology
影响因子: 4.3
作者: [Louie W, Shen MW, Tahiry Z, Zhang S, Worstell D, Cassa CA, Sherwood RI, Gifford DK]
通讯作者: Gifford DK
DOI: 10.1186/s13059-015-0853-4
发表时间: 2015-12-22
期刊: Genome biology
影响因子: 12.3
作者: [Sudmant PH, Alexis MS, Burge CB]
通讯作者: Burge CB
59
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