Consortium for Viral Systems Biology Data Management and Bioinformatics Core

病毒系统生物学数据管理和生物信息学核心联盟

• 批准号: 10579083
• 负责人: ANDREW I SU
• 金额: $ 7.5万
• 依托单位: SCRIPPS RESEARCH INSTITUTE, THE
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-02-01 至 2023-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10579083
• 关键词: Algorithms; B-Lymphocytes; Bioinformatics; Biological; Clinical; Clinical Data; Collaborations; Collection; Communities; Computer software; Data; Data Provenance; Data Set; Ebola Hemorrhagic Fever; Ensure; FAIR principles; Foundations; Generations; Individual; Investigation; Laboratories; Lassa Fever; Metadata; Methods; Mission; Modeling; Output; Patients; Phylogenetic Analysis; Reproducibility; Research Personnel; Resources; Sampling; Scientist; Solid; System; Systems Biology; T cell receptor repertoire sequencing; Technology; Trees; Update; Viral; Work; analysis pipeline; cohort; data management; data modeling; data portal; data resource; data streams; data tools; high throughput technology; innovation; open innovation; predictive modeling; skills; success; tool; web site

Project Summary / Abstract  Our  Center  seeks  to  use high-throughput profiling technologies to develop predictive models of Lassa fever  and  Ebola  virus disease at a systems biology level. The success of this mission is dependent on the unique  cohorts and innovative profiling methods, the combination of which will result in a unique and powerful data  set. In this context, the overall mission of the Data Management and Bioinformatics Core (DMBC) is to ensure  that  the  Center  utilizes  best  practices  for  data  provenance,  analysis,  management,  and  dissemination  throughout the data lifecycle. To accomplish this mission, we will promote the robust collection and analysis  of the primary data, develop a framework for reproducible workflows that can be used across the Center, and  maximize dissemination and reuse of Center-generated data and tools.  Our mission will be accomplished through the completion of three Specific Aims. Aim 1 focuses on accurately  capturing  clinical  and  laboratory  data,  and  then  reproducibly  processing  them  using  robust workflow tools.  This aim describes a key, foundational function that is critical for the success of the Center. Aim 2 focuses on  dissemination  of  Center-generated  resources  according  to  FAIR  principles  -  Findable,  Accessible,  Interoperable, and Reusable. This work will ensure that the impact of our Center extends beyond our team’s  stated  analysis  plan,  and  it  leverages  our  extensive  work  building  tools  for  effective  data  and  software  dissemination.  Aim  3  focuses  on  directly  engaging the community in collaborations with a variety of groups  with  complementary  skills  and  assets.  This  work  leverages  the  principle that collaborative platforms enable  discoveries that would not be possible through individual investigations.  Overall, we believe that this plan for the DMBC offers a broad and solid foundation on which our Center’s data  generation, data modeling, and biological discovery activities can build.

项目摘要/摘要