The impact of focused Gene Ontology curation of specific mammalian systems.
The impact of focused Gene Ontology curation of specific mammalian systems.
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DOI：
10.1371/journal.pone.0027541
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发表时间：
2011
期刊：
影响因子：
3.7
通讯作者：
Lovering RC
中科院分区：
文献类型：
--
作者：
Alam-Faruque Y;Huntley RP;Khodiyar VK;Camon EB;Dimmer EC;Sawford T;Martin MJ;O'Donovan C;Talmud PJ;Scambler P;Apweiler R;Lovering RC
基因本体论(GO)资源提供动态受控词汇表，以提供信息丰富的资源，以帮助对来自所有分类组的基因产品的功能属性和亚细胞位置进行一致的描述(www.genontology.org)。以系统为重点的项目，如肾脏和心血管GO注释倡议，旨在提供与特定器官发育和功能有关的蛋白质的详细GO数据。这些项目支持对新的实验数据的快速评估，并帮助产生新的生物学见解，以帮助减轻人类疾病。本文描述了肾脏和心血管研究界对GO数据的改进，并证明了在过去三年中创建的以心血管为重点的GO注释导致了微阵列解释的明显改进。对心血管微阵列数据集的重新分析证实了继续改进人类蛋白质组注释的必要性。GO注记数据可从以下网址免费获得：ftp://ftp.geneontology.org/pub/go/gene-associations/
The Gene Ontology (GO) resource provides dynamic controlled vocabularies to provide an information-rich resource to aid in the consistent description of the functional attributes and subcellular locations of gene products from all taxonomic groups (www.geneontology.org). System-focused projects, such as the Renal and Cardiovascular GO Annotation Initiatives, aim to provide detailed GO data for proteins implicated in specific organ development and function. Such projects support the rapid evaluation of new experimental data and aid in the generation of novel biological insights to help alleviate human disease. This paper describes the improvement of GO data for renal and cardiovascular research communities and demonstrates that the cardiovascular-focused GO annotations, created over the past three years, have led to an evident improvement of microarray interpretation. The reanalysis of cardiovascular microarray datasets confirms the need to continue to improve the annotation of the human proteome. GO annotation data is freely available from: ftp://ftp.geneontology.org/pub/go/gene-associations/
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影响因子：
4.3
作者：
Reference Genome Group of the Gene Ontology Consortium
通讯作者：
Reference Genome Group of the Gene Ontology Consortium
影响因子：
7
作者：
Ashburner, M;Ball, CA;Yoon, J
通讯作者：
Yoon, J
影响因子：
7.8
作者：
Grigoryev, Dmitry N.;Mathai, Stephen C.;Hassoun, Paul M.
通讯作者：
Hassoun, Paul M.
Profcom：用于分析从高通量数据识别的基因组复杂功能的Web工具。
影响因子：
14.9
作者：
Antonov, Alexey V.;Schmidt, Thorsten;Wang, Yu;Mewes, Hans W.
通讯作者：
Mewes, Hans W.
影响因子：
3
作者：
Lee JA;Sinkovits RS;Mock D;Rab EL;Cai J;Yang P;Saunders B;Hsueh RC;Choi S;Subramaniam S;Scheuermann RH;Alliance for Cellular Signaling
通讯作者：
Alliance for Cellular Signaling