课题基金 / 基金详情

LINKING DISEASE-RELATED GENE TO THE IGTC KNOCKOUT DATABASE

LINKING DISEASE-RELATED GENE TO THE IGTC KNOCKOUT DATABASE
将疾病相关基因与 IGTC 基因敲除数据库关联
批准号:
7723508
负责人:
THOMAS E FERRIN
金额:
$2.87万
依托单位国家:
美国
项目类别:
财政年份:
2008
资助国家:
美国
项目状态:
已结题
起止时间:
2008-07-01 至 2009-06-30

项目摘要

项目成果

THOMAS E FERRIN的其他基金

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中文摘要
翻译
这个子项目是许多研究子项目中的一个 由NIH/NCRR资助的中心赠款提供的资源。子项目和 研究者(PI)可能从另一个NIH来源获得了主要资金, 因此可以在其他CRISP条目中表示。列出的机构是 研究中心,而研究中心不一定是研究者所在的机构。 作为小鼠胚胎中基因敲除注释的一部分, 干细胞,BayGenomics(www.baygenomics.ucsf.edu)提供链接 人类基因的直系同源物是 关联的. 这是通过使用医学主题来实现的。 与描述基因的PubMed摘要链接的标题(MeSH) 有问题。 一个名为Meshlinker的工具用于浏览结果 在BayGenomics网站上。 这种功能对于基因来说 在BayGenomics数据库中被淘汰,但尚未移植 国际基因陷阱联盟数据库(www.genetrap.org)。 最初,我的研究项目是创建一个 IGTC网站的Meshlinker。 这包括:设计一个 修改了Meshlinker的数据库模式,使其与 BayGenomics和IGTC数据库之间的差异,加载 数据本身,以允许在IGTC上进行功能齐全的数据挖掘 现场,并将装载过程集成到IGTC管道中, 允许将来自动运行。 进一步的方向将包括 将MeSH以外的医学术语本体与敲除 基因,并利用这些联系来询问有趣的生物学 问题.
英文摘要
This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. As part of its annotation of genes knocked out in mouse embryonic stem cells, BayGenomics (www.baygenomics.ucsf.edu) provides links to medical terms with which the human orthologs of the genes are associated. This is accomplished by using the Medical Subject Headings (MeSH) linked with PubMed abstracts that describe the gene in question. A tool called Meshlinker is used to browse the results on the BayGenomics site. This functionality is in place for genes knocked out in the BayGenomics database but has not yet been ported to the International Gene Trap Consortium database (www.genetrap.org). Initially, my research project is to create an implementation of Meshlinker for the IGTC web site. This involves: designing a modified database schema for Meshlinker to correspond with the differences between the BayGenomics and IGTC databases, load the data itself to allow for fully functional data mining on the IGTC site, and integrate the loading process into the IGTC pipeline to allow for future automated runs. Further direction will include linking medical terminology ontologies other than MeSH to knocked-out genes and using these linkages to ask interesting biological questions.
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