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Biomedical Data Science Graduate Training at Stanford

Biomedical Data Science Graduate Training at Stanford
斯坦福大学生物医学数据科学研究生培训
批准号:
9901621
负责人:
SYLVIA KATINA PLEVRITIS
金额:
$30.84万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2016
资助国家:
美国
项目状态:
已结题
起止时间:
2016-04-01 至 2021-08-31

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中文摘要
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英文摘要
 DESCRIPTION (provided by applicant): The expanded ability to collect data at all scales-molecular, cellular, tissue, organism and population-has created unparalleled opportunities for biomedical discovery. These opportunities cross all areas of research from basic science to clinical care. In response to these tremendously exciting emerging challenges in data science, Stanford University announced the creation of a new Department of Biomedical Data Science (DBDS) to begin in fall of 2015. Fundamental to the DBDS is bringing together faculty in (1) informatics and computer science, and (2) biostatistics and mathematical modeling, who work closely with a broad range of (3) biomedical science collaborators to advance knowledge. The Stanford Biomedical Informatics (BMI) training program is focused on the creation of new methods for the organization, analysis and modeling of biomedical data and knowledge. The BMI program has been a small interdisciplinary program at Stanford for more than 33 years; nonetheless, it has produced many leaders in biomedical informatics and data science. The BMI program will now have its administrative home in the DBDS, and will become the epicenter for biomedical data science training at Stanford. We are able quickly to respond to the shortage of trained scientists in biomedical data science because of a flexible curriculum, an unusually fertile set of course offerings, and a plethora of research opportunities. In this proposal, we outline a plan to engage faculty broadly across the University to create scalable mechanisms for training the next generation of biomedical data scientists, and creating a pathway for "data science" within the BMI program that stresses statistical reasoning, machine learning and data mining of biomedical data.
期刊论文(23)
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科研奖励(0)
会议论文
DOI: 10.1142/9789813279827_0003
发表时间: 2018-08
期刊: Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
影响因子: --
作者: [D. Ding;C. Simpson;S. Pfohl;Dave C. Kale;Kenneth Jung;N. Shah]
通讯作者: D. Ding;C. Simpson;S. Pfohl;Dave C. Kale;Kenneth Jung;N. Shah
DOI: 10.1038/s41467-021-22328-4
发表时间: 2021-04-01
期刊: Nature communications
影响因子: 16.6
作者: [Fries JA, Steinberg E, Khattar S, Fleming SL, Posada J, Callahan A, Shah NH]
通讯作者: Shah NH
Outgroup Machine Learning Approach Identifies Single Nucleotide Variants in Noncoding DNA Associated with Autism Spectrum Disorder.
外群机器学习方法识别与自闭症谱系障碍相关的非编码 DNA 中的单核苷酸变异。
DOI: --
发表时间: 2019
期刊: Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
影响因子: --
作者: [Varma,Maya, Paskov,KelleyMarie, Jung,Jae-Yoon, SierraChrisman,Brianna, Stockham,NateTyler, Washington,PeterYigitcan, Wall,DennisPaul]
通讯作者: Wall,DennisPaul
Semantic workflows for benchmark challenges: Enhancing comparability, reusability and reproducibility.
应对基准挑战的语义工作流程:增强可比性、可重用性和可重复性。
DOI: --
发表时间: 2019
期刊: Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
影响因子: --
作者: [Srivastava,Arunima, Adusumilli,Ravali, Boyce,Hunter, Garijo,Daniel, Ratnakar,Varun, Mayani,Rajiv, Yu,Thomas, Machiraju,Raghu, Gil,Yolanda, Mallick,Parag]
通讯作者: Mallick,Parag
15
    Project 2 Human Tumor Analysis
    • 批准号:
      10729467
    • 项目类别:
    • 资助金额:
      $52.27万
    • 财政年份:
      2023
    • 负责人:
      SYLVIA KATINA PLEVRITIS
    • 依托单位:
    Administrative Core
    • 批准号:
      10729465
    • 项目类别:
    • 资助金额:
      $36.05万
    • 财政年份:
      2023
    • 负责人:
      SYLVIA KATINA PLEVRITIS
    • 依托单位:
    Data Analysis Core
    • 批准号:
      10531082
    • 项目类别:
    • 资助金额:
      $43.55万
    • 财政年份:
      2022
    • 负责人:
      SYLVIA KATINA PLEVRITIS
    • 依托单位:
    Data Analysis Core
    • 批准号:
      10709577
    • 项目类别:
    • 资助金额:
      $52.33万
    • 财政年份:
      2022
    • 负责人:
      SYLVIA KATINA PLEVRITIS
    • 依托单位:
    海外基金