Gene Ontology Consortium

基因本体联盟

• 批准号: 9044807
• 负责人: Judith A Blake
• 金额: $ 383.55万
• 依托单位: JACKSON LABORATORY
• 依托单位国家: 美国
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-01-19 至 2017-03-01
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9044807
• 关键词: Adopted; Anatomy; Animal Model; Area; Back; Bioinformatics; Biological; Biological Process; Biology; Chemicals; Classification; Collaborations; Communities; Complex; Computer software; Computers; Databases; Development; Disease Outcome; Ensure; Environment; Galaxy; Gene Proteins; Genes; Genetic; Genome; Genomics; Guidelines; Health; Human; International; Java; Knowledge; Light; Literature; Maps; Molecular; Ontology; Organ; Organism; Pathway interactions; Phylogenetic Analysis; Plug-in; Practice Guidelines; Provider; Public Health; Quality Control; Research; Research Personnel; Resources; Role; Semantics; Services; Standardization; Structure; Students; System; Systems Biology; Technology; Terminology; Trees; Untranslated RNA; Web Ontology Language; Work; base; biological research; biomedical ontology; cell type; gene function; gene product; genome annotation; genomic data; information model; interest; model organisms databases; molecular domain; support tools; tool; web services

DESCRIPTION (provided by applicant): Our objective is to provide the scientific community with a consistent, robust information environment for describing, sharing, integrating and comparing the functional roles of genes, proteins and functional RNAs within and across all organisms. The Gene Ontology (GO) Consortium is an international collaboration of model organism database and genome annotation groups who have joined together to establish standards for describing gene products, to provide tools and support for the consistent application of these standards for functional annotations, and to contribute to a central bioinformatics resource to integrate and share these annotations to facilitate and enable biological research. The GO provides specific classifications consisting of well-defined, biologically descriptive terms for the domains of, molecular function, biological process and cellular component. The GO classifications are independent of a particular technology, an uncoupling of terminology from technology that encourages application of these semantic standards by organism annotation groups that utilize a wide range of technical environments. The GO has been widely adopted and used for representation of complex biological information for model organism genomes, and is increasingly used for the functional annotation of emerging genomes. With the increased use of the GO, the Consortium must actively work to ensure both the consistency and quality of annotations as well as accuracy of the ontologies so that these resources may be reliably used to draw inferences and make biological predictions. We will do so by focusing on six key aims: 1) We will provide experimental functional annotations for human and major model organisms; 2) We will extend the GO into emerging genome annotation communities and for key biological domains; 3) We will enable phylogenetically-based propagation of annotations; 4) We will develop a Common Annotation Framework; 5) We will maintain and upgrade the Gene Ontologies, and 6) We will provide annotations and ontologies to the broad genetics community, thus supporting experimental biologists, genome informaticists, and computational biologists who are using GO annotations and ontologies in their research.

描述（由申请人提供）：我们的目标是为科学界提供一个一致的，强大的信息环境，用于描述，共享，整合和比较基因，蛋白质和功能性RNA在所有生物体内和跨所有生物的功能作用。基因本体论（GO）联盟是模式生物数据库和基因组注释组的国际合作，他们共同建立了描述基因产物的标准，为这些标准在功能注释中的一致应用提供工具和支持，并为整合和共享这些注释的中央生物信息学资源做出贡献，以促进和实现生物学研究。GO提供了特定的分类，包括分子功能、生物过程和细胞组分领域的明确定义的生物学描述性术语。GO分类独立于特定的技术，术语与技术的解耦鼓励利用各种技术环境的生物体注释组应用这些语义标准。GO已被广泛采用并用于表示模式生物基因组的复杂生物信息，并且越来越多地用于新兴基因组的功能注释。随着GO使用的增加，联盟必须积极工作，以确保注释的一致性和质量以及本体的准确性，以便这些资源可以可靠地用于推断和进行生物学预测。我们将通过专注于六个关键目标来实现这一目标：1）我们将为人类和主要模式生物提供实验性功能注释; 2）我们将把GO扩展到新兴的基因组注释社区和关键的生物学领域; 3）我们将实现基于遗传学的注释传播; 4）我们将开发一个通用注释框架; 5）我们将维护和升级基因本体，6）我们将为广泛的遗传学社区提供注释和本体，从而支持在研究中使用GO注释和本体的实验生物学家，基因组信息学家和计算生物学家。