Computational Omics and Biomedical Informatics Program (COBIP)

计算组学和生物医学信息学计划(COBIP)

基本信息

  • 批准号:
    10319196
  • 负责人:
  • 金额:
    $ 34.62万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2021
  • 资助国家:
    美国
  • 起止时间:
    2021-09-22 至 2026-07-31
  • 项目状态:
    未结题

项目摘要

PROJECT SUMMARY Despite the significant human health and disease burden in Africa, no biomedical data science graduate degree programmes in computational omics, clinical informatics and translational research are offered on the continent. To foster research training that will cultivate graduates able to respond with agility to future biomedical data science needs and develop innovative solutions to address African health challenges, formal interdisciplinary training in biomedical data science is needed. Such training opportunities should include: (i) Biomedical data science applied to data from multi-omics and other technologies, such as biomedical imaging, coupled with the ethical, legal and social Implications of these advances; (ii) Fundamental and advanced concepts in machine intelligence and computational paradigms for developing novel approaches for mining large-scale biomedical data; and (iii) Awareness, amongst graduates, of career opportunities within biomedical data science along with how the soft and hard skills gained in the training program could be transferred into a range of biotechnology/biomedical industries and research/professional careers. Motivated by these needs and leveraging the expertise in clinical and translational research as well as biomedical informatics at Oregon Health & Science University (OHSU), we propose to develop the “Computational Omics and Biomedical Informatics Program” (COBIP) at the University of Cape Town, South Africa. The program will introduce graduate degree programs to train African biomedical data scientists and faculty in rigorous fundamental data science, computational omics, clinical informatics and imaging data science. COBIP will lead to the development of solutions that address the African disease burden and are relevant to global health. Specifically, we aim to: 1) Develop an interdisciplinary data science training program focused on the health and healthcare needs and priorities of Africa; 2) Train faculty with relevant disciplinary backgrounds, from collaborating African institutions, in biomedical data science to support the development of the field across the continent; and 3) Establish COBIP as an international center of excellence in computational omics and biomedical informatics, distributed across African institutions as a collaborative network of faculty, researchers, and students focused on the African health priorities. COBIP will attract cohorts of trainees from diverse backgrounds including mathematics, statistics, informatics, computer sciences, engineering and biomedical sciences. COBIP will provide innovative educational infrastructure and research opportunities as well as links between clinicians, researchers and biomedical industries through placements and internships. COBIP, through its graduates, will have decisive impacts on African biomedical data science research and stimulate diagnostics, therapeutic selection and drug development to support improved human health and healthcare in Africa and globally.
项目摘要 尽管非洲的人类健康和疾病负担很重,但没有生物医学数据科学研究生学位 非洲大陆提供计算组学、临床信息学和转化研究方案。 促进研究培训,培养能够灵活应对未来生物医学数据的毕业生 科学需要和制定创新的解决方案,以应对非洲的健康挑战,正式的跨学科 需要进行生物医学数据科学方面的培训。这种培训机会应包括: 科学应用于多组学和其他技术的数据,如生物医学成像,再加上 这些进步的伦理、法律的和社会影响;(ii)机器的基本和先进概念 智能和计算范例,用于开发挖掘大规模生物医学的新方法 数据;(iii)毕业生对生物医学数据科学领域职业机会的认识,沿着 如何将在培训计划中获得的软技能和硬技能转化为一系列 生物技术/生物医学产业和研究/职业生涯。 受这些需求的激励,并利用临床和转化研究以及生物医学方面的专业知识, 信息学在俄勒冈州健康与科学大学(OHSU),我们建议开发“计算组学 南非开普敦大学生物医学信息学项目(COBIP)。该计划将 引入研究生学位课程,以严格的方式培训非洲生物医学数据科学家和教师 基础数据科学、计算组学、临床信息学和成像数据科学。COBIP将领导 我们的目标是制定解决非洲疾病负担并与全球卫生相关的解决方案。 具体来说,我们的目标是:1)开发一个跨学科的数据科学培训计划,重点是健康和 非洲的医疗保健需求和优先事项; 2)培训具有相关学科背景的教师, 合作非洲机构,在生物医学数据科学,以支持整个领域的发展, 3)建立COBIP作为计算组学的国际卓越中心, 生物医学信息学,分布在非洲机构作为一个合作网络的教师,研究人员, 学生们关注的是非洲的健康优先事项。 COBIP将吸引来自不同背景的学员,包括数学,统计学,信息学, 计算机科学、工程和生物医学科学。COBIP将提供创新的教育 基础设施和研究机会以及临床医生,研究人员和生物医学之间的联系 行业通过安置和实习。COBIP,通过其毕业生,将有决定性影响, 非洲生物医学数据科学研究和刺激诊断,治疗选择和药物开发 支持改善非洲和全球的人类健康和医疗保健。

项目成果

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WILLIAM R HERSH其他文献

WILLIAM R HERSH的其他文献

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{{ truncateString('WILLIAM R HERSH', 18)}}的其他基金

Attracting Talented and Diverse Students to Biomedical Informatics and Data Science Careers Through Short-Term Study at OHSU
通过在 OHSU 的短期学习吸引才华横溢、多元化的学生从事生物医学信息学和数据科学职业
  • 批准号:
    10630618
  • 财政年份:
    2022
  • 资助金额:
    $ 34.62万
  • 项目类别:
Attracting Talented and Diverse Students to Biomedical Informatics and Data Science Careers Through Short-Term Study at OHSU
通过在 OHSU 的短期学习吸引才华横溢、多元化的学生从事生物医学信息学和数据科学职业
  • 批准号:
    10701083
  • 财政年份:
    2022
  • 资助金额:
    $ 34.62万
  • 项目类别:
Computational Omics and Biomedical Informatics Program (COBIP)
计算组学和生物医学信息学计划(COBIP)
  • 批准号:
    10490403
  • 财政年份:
    2021
  • 资助金额:
    $ 34.62万
  • 项目类别:
Computational Omics and Biomedical Informatics Program (COBIP)
计算组学和生物医学信息学计划(COBIP)
  • 批准号:
    10676322
  • 财政年份:
    2021
  • 资助金额:
    $ 34.62万
  • 项目类别:
Research Training in Biomedical Informatics and Data Science at Oregon Health & Science University
俄勒冈健康中心生物医学信息学和数据科学研究培训
  • 批准号:
    9524502
  • 财政年份:
    2017
  • 资助金额:
    $ 34.62万
  • 项目类别:
Biomedical Informatics Research Training at Oregon Health & Science University
俄勒冈健康中心的生物医学信息学研究培训
  • 批准号:
    9369268
  • 财政年份:
    2016
  • 资助金额:
    $ 34.62万
  • 项目类别:
Semi-structured Information Retrieval in Clinical Text for Cohort Identification
用于队列识别的临床文本中的半结构化信息检索
  • 批准号:
    10450805
  • 财政年份:
    2014
  • 资助金额:
    $ 34.62万
  • 项目类别:
Semi-structured Information Retrieval in Clinical Text for Cohort Identification
用于队列识别的临床文本中的半结构化信息检索
  • 批准号:
    10207950
  • 财政年份:
    2014
  • 资助金额:
    $ 34.62万
  • 项目类别:
Semi-structured Information Retrieval in Clinical Text for Cohort Identification
用于队列识别的临床文本中的半结构化信息检索
  • 批准号:
    10879792
  • 财政年份:
    2014
  • 资助金额:
    $ 34.62万
  • 项目类别:
OHSU Summer Internship in Biomedical Informatics for College Undergraduates
OHSU 大学本科生生物医学信息学暑期实习
  • 批准号:
    8281433
  • 财政年份:
    2011
  • 资助金额:
    $ 34.62万
  • 项目类别:

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