课题基金 / 基金详情

Interdisciplinary training: Statistical Genetics/Genomics and Computational Biology

Interdisciplinary training: Statistical Genetics/Genomics and Computational Biology
跨学科培训:统计遗传学/基因组学和计算生物学
批准号:
10640852
负责人:
Curtis Huttenhower
金额:
$42.44万
依托单位国家:
美国
项目类别:
财政年份:
2020
资助国家:
美国
项目状态:
未结题
起止时间:
2020-07-01 至 2025-06-30

项目摘要

项目成果

Curtis Huttenhower的其他基金

相似基金

相关文献

中文摘要
翻译
点击翻译按钮获取中文摘要
英文摘要
PROJECT SUMMARY/ABSTRACT This is an application of the Interdisciplinary Training Program in Statistical Genetics/Genomics and Computational Biology at the Harvard School of Public Health (HSPH). Trainees will be pre-doctoral students at HSPH in the Departments of Biostatistics and Epidemiology, which will jointly administer the grant. The Program proposes support for 8 predoctoral students in years 1-2 and 10 predoctoral students in years 3-5. This is the only program at Harvard School of Public Health that provides integrative training in statistical genetics/genomics and computational biology. The goal of the program is to train the next generation of quantitative genomic scientists to have a strong understanding of, and commitment to, cutting-edge methodological and collaborative research in statistical genetics/genomics and bioinformatics/computational biology with applications in genetic epidemiology, molecular biology and genomic medicine. We are committed to train trainees to become future quantitative leaders to develop and apply advanced, scalable statistical and computational methods to manage, analyze, integrate, and interpret massive genetic and genomic data in basic science, epidemiological and clinical studies, to promote interdisciplinary research, and to effectively communicate and collaborate with subject-matter scientists in genetic and genomic research. Trainees receive quantitative training in big `omics data science and reproducible research. The training program involves active participation by 26 multidisciplinary faculty members who are recognized scientific leaders, including biostatisticians, bioinformaticians and computational biologists, genetic epidemiologists, and molecular biologists, and clinical genomicists. It combines elements of training in coursework, lab rotations in both wet labs in biological science and dry labs in statistical genetics and genomics, computational biology, and genetic epidemiology, directed methodological and collaborative research, and rich career development opportunities in a stimulating and nurturing interdisciplinary environment, that will prepare graduates to become leading quantitative genomic scientists. Trainees will be provided with extensive individualized mentoring tailored towards their career objectives and are required to develop Individual Development Plans. The rich career development programs help trainees gain skills in scientific communication, teaching, grant and paper writing, teamwork, collaboration, and leadership. Trainee progress is closely monitored to ensure that those who are struggling can be quickly identified and receive timely support. The Program evaluation process involves both internal and external feedbacks from all the stakeholders, including current and past trainees, faculty and the External Advisory Committee. Recruitment and retention plans are carefully developed to promote diversity and ensure participation and full inclusion of underrepresented minorities, women, disabled and economically- disadvantaged trainees.
期刊论文(4)
专著(0)
科研奖励(0)
会议论文
DOI: 10.1186/s12889-021-11060-9
发表时间: 2021-05-28
期刊: BMC public health
影响因子: 4.5
作者: [Li D, Gaynor SM, Quick C, Chen JT, Stephenson BJK, Coull BA, Lin X]
通讯作者: Lin X
DOI: 10.1038/s41598-022-26434-1
发表时间: 2023-01-21
期刊: Scientific reports
影响因子: 4.6
作者: []
通讯作者:
DOI: 10.1038/s41467-020-19588-x
发表时间: 2020-11-30
期刊: Nature communications
影响因子: 16.6
作者: [Nait Saada J, Kalantzis G, Shyr D, Cooper F, Robinson M, Gusev A, Palamara PF]
通讯作者: Palamara PF
DOI: 10.1136/bmjopen-2021-053635
发表时间: 2022-02-21
期刊: BMJ open
影响因子: 2.9
作者: [Li D, Ren H, Varelmann DJ, Sarin P, Xu P, Wu D, Li Q, Lin X]
通讯作者: Lin X
Interdisciplinary training: Statistical Genetics/Genomics and Computational Biology
  • 批准号:
    10433911
  • 项目类别:
  • 资助金额:
    $41.63万
  • 财政年份:
    2020
  • 负责人:
    Curtis Huttenhower
  • 依托单位:
Interdisciplinary training: Statistical Genetics/Genomics and Computational Biology
  • 批准号:
    10178049
  • 项目类别:
  • 资助金额:
    $43.89万
  • 财政年份:
    2020
  • 负责人:
    Curtis Huttenhower
  • 依托单位:
A comprehensive platform for novel therapy development from the microbiome
  • 批准号:
    10206118
  • 项目类别:
  • 资助金额:
    $153.28万
  • 财政年份:
    2017
  • 负责人:
    Curtis Huttenhower
  • 依托单位:
A comprehensive platform for novel therapy development from the microbiome
  • 批准号:
    10017679
  • 项目类别:
  • 资助金额:
    $154.01万
  • 财政年份:
    2017
  • 负责人:
    Curtis Huttenhower
  • 依托单位:
海外基金