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NLM Research Training Program in Biomedical Informatics and Data Science for Predoctoral and Postdoctoral Fellows

NLM Research Training Program in Biomedical Informatics and Data Science for Predoctoral and Postdoctoral Fellows
NLM 博士前和博士后生物医学信息学和数据科学研究培训计划
批准号:
10656288
负责人:
Lydia E. Kavraki
金额:
$65.98万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
1992
资助国家:
美国
项目状态:
未结题
起止时间:
1992-07-01 至 2027-06-30

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中文摘要
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PROJECT SUMMARY/ABSTRACT We seek renewal of our NLM Research Training Program in Biomedical Informatics and Data Science (NLMTP), which for 29 years has consistently produced outstanding pre- and postdoctoral trainees as the program has evolved along with Biomedical Informatics and Data Science (BMI and DS) themselves, successfully bringing computation, data science, applied mathematics, statistics, biomedicine, modeling, data- driven inference and decision-making, and advances in cognitive informatics, to bear on biomedical problems. With this renewal, we will further expand our research training program to explore and exploit the dynamic interaction of BMI and DS with artificial intelligence (AI), including machine learning, and their applications in biomedicine and human health and disease. Our program will not only equip trainees with solid DS methodology and the latest tools, computational approaches, and statistical methods to solve BMI problems, but also provide broad foundations that will enable them to invent the methodologies of the future to attack problems currently beyond our reach; this will produce a new generation of BMI scientists who can extract new knowledge from experience and experiment to inform basic research, patient care and public health. We, therefore, seek to train our students and postdocs to work effectively at the interface between theory and practice, between knowledge acquisition and knowledge sharing. Our 46 training faculty, with broad expertise in BMI, DS, and AI coupled with basic science and clinical knowledge, have a record of high research productivity, extensive collaborations, and federal funding. Their track record of the recruitment, training, and career advancement of underrepresented (UR) groups including women is strong, having mentored 264 predocs and 337 postdocs over the past 10 years, with 208 predocs (31% UR, 39% women) and 132 postdocs (16% UR, 31% women) currently in their labs. Our 9 predoctoral trainees will have completed one year of study and joined a lab at one of six participating institutions before joining the NLMTP (typically for 3-year appointments), thus ensuring that their research projects fit well into the training areas of the NLM. Our 6 postdoctoral trainees will be selected through national recruiting and from the labs of our faculty, for typically 2-year appointments. NLMTP training will combine core courses in BMI and DS, advanced elective courses, training in rigor and reproducibility and the responsible conduct of research, professional/career development activities, monthly meetings with experts, and interdisciplinary dual-mentored research projects in health care/clinical informatics, translational bioinformatics, and clinical research informatics. Our research training program will undergo regular evaluations by external experts with adjustments made as needed. This program will provide the perfect opportunity for trainees to acquire the skills, expertise and intellectual abilities to foster innovative research and prepare them for applied research or related careers in which they can profoundly affect such critical areas as personalized medicine, clinical decision making, and data-driven health.
期刊论文(341)
专著(0)
科研奖励(0)
会议论文
Prioritization of risk genes in multiple sclerosis by a refined Bayesian framework followed by tissue-specificity and cell type feature assessment.
通过完善的贝叶斯框架对多发性硬化症中的风险基因进行优先排序,然后进行组织特异性和细胞类型特征评估。
DOI: 10.1186/s12864-022-08580-y
发表时间: 2022-05-11
期刊: BMC genomics
影响因子: 4.4
作者: []
通讯作者:
Toward a standard formal semantic representation of the model card report.
迈向模型卡报告的标准正式语义表示。
DOI: 10.1186/s12859-022-04797-6
发表时间: 2022-07-14
期刊: BMC BIOINFORMATICS
影响因子: 3
作者: [Amith, Muhammad Tuan, Cui, Licong, Zhi, Degui, Roberts, Kirk, Jiang, Xiaoqian, Li, Fang, Yu, Evan, Tao, Cui]
通讯作者: Tao, Cui
DOI: 10.1016/j.ijid.2021.09.067
发表时间: 2021-12
期刊: International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases
影响因子: --
作者: [Nigo M, Rasmy L, May SB, Rao A, Karimaghaei S, Kannadath BS, De la Hoz A, Arias CA, Li L, Zhi D]
通讯作者: Zhi D
DOI: 10.1016/j.jmb.2008.10.093
发表时间: 2009-01-30
期刊: JOURNAL OF MOLECULAR BIOLOGY
影响因子: 5.6
作者: [Wu, Yinghao, Dousis, Athanasios D., Chen, Mingzhi, Li, Jialin, Ma, Jianpeng]
通讯作者: Ma, Jianpeng
195
    PROTEAN-CR: Proteomics Toolkit for Ensemble Analysis in Cancer Research
    • 批准号:
      10188196
    • 项目类别:
    • 资助金额:
      $40.21万
    • 财政年份:
      2021
    • 负责人:
      Lydia E. Kavraki
    • 依托单位:
    PROTEAN-CR: Proteomics Toolkit for Ensemble Analysis in Cancer Research
    • 批准号:
      10615697
    • 项目类别:
    • 资助金额:
      $38.36万
    • 财政年份:
      2021
    • 负责人:
      Lydia E. Kavraki
    • 依托单位:
    PROTEAN-CR: Proteomics Toolkit for Ensemble Analysis in Cancer Research
    • 批准号:
      10398904
    • 项目类别:
    • 资助金额:
      $39.74万
    • 财政年份:
      2021
    • 负责人:
      Lydia E. Kavraki
    • 依托单位:
    NLM Training Program in Biomedical Informatics & Data Science for Predoctoral and Postdoctoral Fellows
    • 批准号:
      9526234
    • 项目类别:
    • 资助金额:
      $9.8万
    • 财政年份:
      2017
    • 负责人:
      Lydia E. Kavraki
    • 依托单位:
    海外基金