BioGRID: An open resource for biological interactions and network analysis

BioGRID：生物相互作用和网络分析的开放资源

• 批准号: 10299336
• 负责人: KARA DOLINSKI
• 金额: $ 94.26万
• 依托单位: SINAI HEALTH SYSTEM
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-05-15 至 2026-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10299336
• 关键词: Algorithms; Alleles; Animal Model; Architecture; Archives; Area; Back; Behavior; Binding; Biological; Biological Process; Biomedical Research; COVID-19; CRISPR screen; Cells; Chemical Agents; Chemicals; Clustered Regularly Interspaced Short Palindromic Repeats; Collaborations; Collection; Communities; Complex; Computer software; Data; Data Set; Databases; Development; Discipline; Disease; Drug Interactions; Engineering; Funding; Future; Gene Proteins; Generations; Genes; Genetic; Genome; Health; Human; Human Development; International; Intuition; Knowledge; Literature; Malignant Neoplasms; Maps; Methods; Mission; Molecular; Organism; Orthologous Gene; Pathway Analysis; Phenotype; Post-Translational Protein Processing; Process; Property; Protein Structure Initiative; Proteins; Proteome; Publications; Records; Research; Research Personnel; Resources; Services; Software Tools; Source; System; Technology; Tissues; Translating; Translational Research; Ubiquitin; United States National Institutes of Health; Visualization; base; biological systems; data pipeline; data tools; experimental study; functional genomics; fundamental research; gene function; genome-wide; human disease; improved; interest; knowledge graph; large datasets; model organisms databases; multicatalytic endopeptidase complex; new therapeutic target; novel; open source; pathogen; protein complex; protein function; repository; software development; statistics; technological innovation; text searching; tool; web site

Complex physical and genetic interaction networks determine the properties of all biological systems and underlie human development, health and disease. Decades of biological experiments have identified myriad molecular processes that underpin specific biological processes, described in the primary biomedical literature. More recent technological innovations combined with complete genome sequence information have led to the development of a wide variety high-throughput (HTP) methods to generate physical and genetic interaction data on an unprecedented scale. Because human interaction networks are often directly analogous to networks in more tractable model organisms, it is essential that the hundreds of thousands of biological interactions discovered across the major model organisms, as well as humans, are archived in a well- annotated manner that provides a means for rigorous analysis and computation. To capture, integrate, and interrogate this wealth of data from both the literature and HTP datasets, we developed the BioGRID database as an open repository for physical and genetic interactions (www.thebiogrid.org). BioGRID contains over 2,000,000 total interactions from 75,760 publications. In 2020, BioGRID averaged 151,735 page views, 19,407 unique visitors and 7,537 file downloads per month. Our recently released Open Repository for CRISPR Screens (ORCS), averages 8,725 page views, 1,646 unique visitors, and 268 downloads per month. In addition, the extensive BioGRID data compendium is widely disseminated by many partner databases, meta- databases, and software tools. Here, we propose to markedly enhance the data content, the database architecture, and the user interface of BioGRID. We will expand the amount and types of data available through BioGRID, with a particular focus on translating knowledge from model organism networks to humans using ortholog mapping and a novel framework for mapping phenotypes and diseases across species. We will significantly expand CRISPR-based genetic interactions, chemical and drug interactions, and post-translational modifications, which we will integrate with our core physical and genetic interactions and organize around focused curation efforts around particular biological themes. Use of text-mining algorithms and AI methods will be extended to enhance curation rates and coverage of the proteome. User access to the large datasets in BioGRID will be facilitated by data-rich interfaces, user-defined search and display parameters, and multiple methods of visualization. All software will continue to be open source and engineered toward compatibility and will be complementary with other database and software development efforts. The BioGRID will provide interaction data and software tools to model organism databases and other interested parties without restriction. The BioGRID resource will enable the biomedical research community to access validated biological interaction datasets across model organisms and humans for hypothesis generation and network analysis, and thereby further the general mission of the NIH.

复杂的物理和遗传相互作用网络决定了所有生物系统和 是人类发展、健康和疾病的基础。数十年的生物实验已经发现了无数 主要生物医学文献中描述的支撑特定生物过程的分子过程。 最近的技术创新与完整的基因组序列信息相结合，导致了 开发多种高通量（HTP）方法来产生物理和遗传相互作用 数据规模空前。因为人类交互网络通常直接类似于 在更容易处理的模型生物体中，数十万个生物体的网络至关重要 在主要模式生物以及人类中发现的相互作用都被存档在一个完整的数据库中。 带注释的方式，提供了严格分析和计算的手段。捕获、整合和 询问来自文献和 HTP 数据集的大量数据，我们开发了 BioGRID 数据库 作为物理和遗传相互作用的开放存储库（www.thebiogrid.org）。 BioGRID 包含超过 来自 75,760 份出版物的总共 2,000,000 次互动。 2020 年，BioGRID 平均页面浏览量为 151,735 次，19,407 次 每月独立访客数和 7,537 次文件下载。我们最近发布的 CRISPR 开放存储库 Screens (ORCS)，平均每月页面浏览量为 8,725 次，独立访问者数为 1,646 人，下载量为 268 次。在 此外，广泛的 BioGRID 数据纲要被许多合作伙伴数据库、元数据广泛传播 数据库和软件工具。在这里，我们建议显着增强数据内容、数据库 BioGRID 的架构和用户界面。我们将扩大可用数据的数量和类型 通过 BioGRID，特别注重将知识从模式生物网络转化为人类 使用直向同源图谱和新框架来绘制跨物种的表型和疾病。我们将 显着扩展基于 CRISPR 的遗传相互作用、化学和药物相互作用以及翻译后 修改，我们将与我们的核心物理和遗传相互作用相结合，并围绕 围绕特定的生物主题集中策展工作。文本挖掘算法和人工智能方法的使用将 扩展以提高蛋白质组的管理率和覆盖范围。用户访问大型数据集 BioGRID 将通过数据丰富的界面、用户定义的搜索和显示参数以及多个 可视化方法。所有软件将继续开源并以兼容性和设计为目标 将与其他数据库和软件开发工作相辅相成。 BioGRID 将提供 交互数据和软件工具来模拟生物体数据库和其他感兴趣的各方，而无需 限制。 BioGRID 资源将使生物医学研究界能够访问经过验证的 模型生物和人类之间的生物相互作用数据集，用于假设生成和网络 分析，从而进一步实现 NIH 的总体使命。