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Training Program in Computational Genomics

Training Program in Computational Genomics
计算基因组学培训计划
批准号:
10615793
负责人:
MAJA BUCAN
金额:
$39.3万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
1999
资助国家:
美国
项目状态:
未结题
起止时间:
1999-07-16 至 2025-04-30

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项目成果

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英文摘要
Project Summary University of Pennsylvania has trained computational genomicists for the past 20 years supported by the NHGRI T32 program, training 52 predoctoral and 13 postdoctoral trainees the majority of whom have gone on to careers in research and development. Here we propose to continue our Computational Genomic Training program with eight predoctoral and two postdoctoral trainees focused on the theme of Data Science and Machine/Statistical Learning methods as applied to genomics data. Our training program concentrates on a rigorous course-based curriculum supported by courses in multiple graduate groups. In addition, our training also involves 13-16 hours of Responsible Conduct of Research (RCR) and Scientific Rigor and Reproducibility (SRR) training, Individual Development Plan, and utilization of Electronic Notebooks and code repositories. Research training is enhanced by a dual mentorship model whenever possible. Our program is supported by a greater genomics training program consisting of three NHGRI T32 programs in Computational Genomics (this program), Genomic Medicine, and ELSI, as well as a NHGRI R25 Diversity Action Plan (DAP). In particular, the DAP program recruits URM undergraduate and postbacc trainees focused on the Greater Philadelphia Area whose many institutions serve the urban URM population. This vertical regional integration will allow us to develop a regional pipeline of URM students with undergraduate research experience in genomics. Our program consists of 31 trainers of which 14 are female scientists and 2 are URM scientists. Twenty one of our 31 trainers have an active computational genomics research program. The expertise of the trainers span disease genomics, genomic technologies, multidimensional statistics, algorithms, data sciences, and machine learning. Our training environment is enhanced by key facilities including large biobanks, high-throughput genomics core, high-performance computing core, and a unique immersive data visualization facility. Penn overall hosts more than 60 NIH training programs with strong institutional administrative support for managing the training programs including an Office of Biomedical Postdoctoral Programs, Office of Diversity and Inclusion, combined Biomedical Graduate Studies, among others. Success of our training program will help train the next generation of genomic workforce in the skills and knowledge necessary to apply state-of-art computational techniques to genomics and develop new techniques for novel genomic data.
期刊论文(142)
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会议论文
DOI: 10.1016/j.ymeth.2013.10.002
发表时间: 2014-05-01
期刊: METHODS
影响因子: 4.8
作者: [Ryvkin, Paul, Leung, Yuk Yee, Ungar, Lyle H., Gregory, Brian D., Wang, Li-San]
通讯作者: Wang, Li-San
DOI: 10.1186/s13040-018-0175-7
发表时间: 2018
期刊: BioData mining
影响因子: 4.5
作者: [Chen KM, Tan J, Way GP, Doing G, Hogan DA, Greene CS]
通讯作者: Greene CS
DOI: 10.1098/rsif.2017.0387
发表时间: 2018-04
期刊: Journal of the Royal Society, Interface
影响因子: --
作者: [Ching T, Himmelstein DS, Beaulieu-Jones BK, Kalinin AA, Do BT, Way GP, Ferrero E, Agapow PM, Zietz M, Hoffman MM, Xie W, Rosen GL, Lengerich BJ, Israeli J, Lanchantin J, Woloszynek S, Carpenter AE, Shrikumar A, Xu J, Cofer EM, Lavender CA, Turaga SC, Alexandari AM, Lu Z, Harris DJ, DeCaprio D, Qi Y, Kundaje A, Peng Y, Wiley LK, Segler MHS, Boca SM, Swamidass SJ, Huang A, Gitter A, Greene CS]
通讯作者: Greene CS
DOI: 10.1038/nature15540
发表时间: 2015-12-17
期刊: Nature
影响因子: 64.8
作者: [Oldridge DA, Wood AC, Weichert-Leahey N, Crimmins I, Sussman R, Winter C, McDaniel LD, Diamond M, Hart LS, Zhu S, Durbin AD, Abraham BJ, Anders L, Tian L, Zhang S, Wei JS, Khan J, Bramlett K, Rahman N, Capasso M, Iolascon A, Gerhard DS, Guidry Auvil JM, Young RA, Hakonarson H, Diskin SJ, Look AT, Maris JM]
通讯作者: Maris JM
87
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