Reactome与基因本体论：数据资源的数字融合
Reactome and the Gene Ontology: digital convergence of data resources.
作者信息
Good Benjamin M, Van Auken Kimberly, Hill David P, Mi Huaiyu, Carbon Seth, Balhoff James P, Albou Laurent-Philippe, Thomas Paul D, Mungall Christopher J, Blake Judith A, D'Eustachio Peter
机构信息
Division of Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA.
Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, USA.
出版信息
Bioinformatics. 2021 Oct 11;37(19):3343-3348. doi: 10.1093/bioinformatics/btab325.
MOTIVATION
Gene Ontology Causal Activity Models (GO-CAMs) assemble individual associations of gene products with cellular components, molecular functions and biological processes into causally linked activity flow models. Pathway databases such as the Reactome Knowledgebase create detailed molecular process descriptions of reactions and assemble them, based on sharing of entities between individual reactions into pathway descriptions.
RESULTS
To convert the rich content of Reactome into GO-CAMs, we have developed a software tool, Pathways2GO, to convert the entire set of normal human Reactome pathways into GO-CAMs. This conversion yields standard GO annotations from Reactome content and supports enhanced quality control for both Reactome and GO, yielding a nearly seamless conversion between these two resources for the bioinformatics community.
SUPPLEMENTARY INFORMATION
Supplementary data are available at Bioinformatics online.
动机
基因本体因果活动模型（GO-CAMs）将基因产物与细胞成分组成组成细胞的各个部分、分子功能和生物过程的个体关联整合到因果联系的活动流模型中。诸如Reactome知识库之类的通路数据库创建反应的详细分子过程描述，并基于各个反应之间的实体共享将它们组装成通路描述。
结果
为了将Reactome的丰富内容转换为GO-CAMs，我们开发了一个软件工具Pathways2GO，将整套正常人类Reactome通路转换为GO-CAMs。这种转换从Reactome内容中产生标准的GO注释，并支持对Reactome和GO进行增强的质量控制，为生物信息学社区在这两种资源之间实现了几乎无缝的转换。
补充信息
补充数据可在《生物信息学》在线获取。
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