Knowledge Management Center for Illuminating the Druggable Genome

阐明可药物基因组的知识管理中心

• 批准号: 10598542
• 负责人: Jeremy S Edwards
• 金额: $ 94.01万
• 依托单位: UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-01-03 至 2024-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10598542
• 关键词: Acceleration; Address; Adoption; Age; Alleles; Archives; Articulation; Basic Science; Biological Sciences; Biology; Biomedical Research; Chemistry; Code; Communities; Community Outreach; Computer software; Coupled; Data; Data Analytics; Data Element; Data Set; Databases; Dependence; Disease; Documentation; FAIR principles; Family; Feedback; Funding; Future; Generations; Genes; Genome; Genome Components; Genotype; Goals; Grant; Healthcare; Human; Informatics; International; Internet; Knowledge; Knowledge Management; Knowledge Management Center; Life; Link; Machine Learning; Manuals; Maps; Medicine; Metadata; Methods; Modeling; Mutation; Non-Human Protein; Ontology; Pathway interactions; Performance; Phase; Phenotype; Process; Protein Isoforms; Proteins; Proteome; Public Domains; Publications; Reagent; Research Domain Criteria; Resources; Scientist; Series; Services; Source; Structure; System; Translational Research; Trees; United States National Institutes of Health; Update; Work; analytical method; base; computer science; data ecosystem; data integration; data resource; design; disease classification; experience; gender difference; genome resource; health data; improved; interest; knowledge base; knowledge graph; knowledgebase; member; novel; online community; outreach; programs; public repository; repository; therapeutic protein; tool; web site; Acceleration; Address; Adoption; Age; Alleles; Archives; Articulation; Basic Science; Biological Sciences; Biology; Biomedical Research; Chemistry; Code; Communities; Community Outreach; Computer software; Coupled; Data; Data Analytics; Data Element; Data Set; Databases; Dependence; Disease; Documentation; FAIR principles; Family; Feedback; Funding; Future; Generations; Genes; Genome; Genome Components; Genotype; Goals; Grant; Healthcare; Human; Informatics; International; Internet; Knowledge; Knowledge Management; Knowledge Management Center; Life; Link; Machine Learning; Manuals; Maps; Medicine; Metadata; Methods; Modeling; Mutation; Non-Human Protein; Ontology; Pathway interactions; Performance; Phase; Phenotype; Process; Protein Isoforms; Proteins; Proteome; Public Domains; Publications; Reagent; Research Domain Criteria; Resources; Scientist; Series; Services; Source; Structure; System; Translational Research; Trees; United States National Institutes of Health; Update; Work; analytical method; base; computer science; data ecosystem; data integration; data resource; design; disease classification; experience; gender difference; genome resource; health data; improved; interest; knowledge base; knowledge graph; knowledgebase; member; novel; online community; outreach; programs; public repository; repository; therapeutic protein; tool; web site

The main goal of the Knowledge Management Center (KMC) for the Illuminating the Druggable Genome (IDG) program is to aggregate, update and articulate protein-centric data, information and knowledge for the entire human proteome with emphasis on understudied proteins from the 3 families that are the focus of the IDG (“IDG List”). The long-term objective of the KMC is to encourage and support biomedical research aimed at understudied proteins by providing an extensive resource of data, information, knowledge, methods and reagents for the entire human proteome, and to support the growing online community focused on understudied proteins. With focus on the IDG List and human proteins, the KMC will enable support for expanded coverage for non-human proteins of therapeutic interest and other associated human health data, in order to catalyze novel biomedical discoveries. To support the overall IDG objective, and to maintain, update and improve these integrated resources, the KMC draws upon expertise from multiple knowledge domains, specifically biology, chemistry and medicine, as well as computer science, graphic design and web programming. Specifically, for the Phase 2 of the IDG KMC we propose 4 Aims:1. Create an automated workflow that captures relevant public data for the entire proteome and manual annotations for the IDG list. The KMC knowledge management system will be built around knowledge graphs, focused on five major branches of the target knowledge tree, tkt: Genotype, Phenotype, Expression, Structure & Function, and Interactions & Pathways, respectively. Aim 2: Design, develop and implement a protein knowledgebase with Data Analytics support. Our protein-centric biomedical knowledge base, TCKB (Target Central Knowledgebase) will be comprised of the data, knowledge and information container, together with its codebase and software pipelines. TCKB will be the repository for experimental, processed and computed data and reagents originating from the IDG DRGCs (Data and Resource Generation Centers). We will provide informatics and modeling support for DRGC activities. Aim 3: We will expand, improve and maintain Pharos. Particularly “knowledge packages,” support automated data summaries for Protein Dossiers, and actively seek feedback from our community. Aim 4. Outreach to scientific community. We will support a series of activities that will leverage TCKB, Pharos and other IDG resources to increase adoption of IDG work, while observing FAIR (findable, accessible, interoperable, reusable) principles for our knowledgebase, portal and pipelines. The KMC will engage in community outreach by leading tutorials and feedback sessions and dissemination of the Pharos system. To meet its goals, the KMC will coordinate all core activities in close coordination with the IDG Steering Committee and IDG Project Scientists (PS), and include members of the IDG Consortium (IDG- C), other NIH Common Fund programs, NIH Commons, as well as other initiatives.

知识管理中心（KMC）的主要目标是照明可毒基因组（IDG） 程序是汇总，更新和表达以蛋白质为中心的数据，信息和知识 人类蛋白质组，重点是从三个家族中理解的蛋白质，这是IDG的重点 （“ IDG列表”）。 KMC的长期目标是鼓励和支持针对的生物医学研究 通过提供大量数据，信息，知识，方法和 整个人类蛋白质组的试剂，并支持不断增长的在线社区专注于 研究的蛋白质。 KMC专注于IDG列表和人类蛋白质，将支持 扩大治疗兴趣非人类蛋白质和其他相关人类健康数据的覆盖范围， 为了催化新颖的生物医学发现。支持总体IDG目标，并维护，更新 并改善这些集成资源，KMC借鉴了来自多个知识领域的专业知识， 特别是生物学，化学和医学以及计算机科学，图形设计和网络 编程。特别是，对于IDG KMC的第2阶段，我们提出了4个目标：1。创建一个自动化 捕获整个蛋白质组和IDG列表的手动注释相关的公共数据的工作流程。 KMC知识管理系统将围绕知识图构建，重点是五个主要 目标知识树的分支，TKT：基因型，表型，表达，结构和功能，以及 互动与途径。目标2：设计，开发和实施蛋白质知识库 数据分析支持。我们以蛋白质为中心的生物医学知识库TCKB（目标中心） 知识库）将完成数据，知识和信息容器以及其数据容器 代码库和软件管道。 TCKB将是实验，处理和计算数据的存储库 以及源自IDG DRGC（数据和资源生成中心）的试剂。我们将提供 信息和建模对DRGC活动的支持。 AIM 3：我们将扩展，改进和维护Pharos。 特别是“知识包”，支持蛋白质档案的自动数据摘要，并积极寻求 来自我们社区的反馈。目标4。向科学界进行宣传。我们将支持一系列活动 这将利用TCKB，PHARO和其他IDG资源来增加IDG工作的采用，同时观察 公平的（可访问，可访问，可互操作，可重复使用的）原理，用于我们的知识库，门户和管道。 KMC将通过领导教程和反馈会议和传播 法拉斯系统。为了实现其目标，KMC将与 IDG指导委员会和IDG项目科学家（PS），包括IDG财团的成员（IDG- c），其他NIH共同基金计划，NIH Commons以及其他倡议。