| Geogle: context mining tool for the correlation between gene expression and the phenotypic distinction | |
| Yu, Yao1,2; Tu, Kang1; Zheng, Siyuan1; Li, Yun1; Ding, Guohui1; Ping, Jie4; Hao, Pei1,3; Li, Yixue1,2,3,4,5 | |
| 刊名 | Bmc bioinformatics
 |
| 2009-08-25 | |
| 卷号 | 10页码:7 |
| ISSN号 | 1471-2105 |
| DOI | 10.1186/1471-2105-10-264 |
| 通讯作者 | Hao, pei(phao@sibs.ac.cn) |
| 英文摘要 | Background: in the post-genomic era, the development of high-throughput gene expression detection technology provides huge amounts of experimental data, which challenges the traditional pipelines for data processing and analyzing in scientific researches. results: in our work, we integrated gene expression information from gene expression omnibus (geo), biomedical ontology from medical subject headings (mesh) and signaling pathway knowledge from sigpathway entries to develop a context mining tool for gene expression analysis - geogle. geogle offers a rapid and convenient way for searching relevant experimental datasets, pathways and biological terms according to multiple types of queries: including biomedical vocabularies, gds ids, gene ids, pathway names and signature list. moreover, geogle summarizes the signature genes from a subset of gdses and estimates the correlation between gene expression and the phenotypic distinction with an integrated p value. conclusion: this approach performing global searching of expression data may expand the traditional way of collecting heterogeneous gene expression experiment data. geogle is a novel tool that provides researchers a quantitative way to understand the correlation between gene expression and phenotypic distinction through meta-analysis of gene expression datasets from different experiments, as well as the biological meaning behind. the web site and user guide of geogle are available at: http://omics.biosino.org:14000/kweb/workflow.jsp?id=00020 |
| WOS关键词 | LARGE-SCALE METAANALYSIS ; MICROARRAY DATA ; OMNIBUS GEO ; CANCER ; PROFILES ; DATABASE ; PATHWAYS |
| WOS研究方向 | Biochemistry & Molecular Biology ; Biotechnology & Applied Microbiology ; Mathematical & Computational Biology |
| WOS类目 | Biochemical Research Methods ; Biotechnology & Applied Microbiology ; Mathematical & Computational Biology |
| 语种 | 英语 |
| 出版者 | BIOMED CENTRAL LTD |
| WOS记录号 | WOS:000270274400002 |
| 内容类型 | 期刊论文 |
| URI标识 | http://www.corc.org.cn/handle/1471x/2394473 |
| 专题 | 中国科学院大学 |
| 通讯作者 | Hao, Pei |
| 作者单位 | 1.Chinese Acad Sci, Shanghai Inst Biol Sci, Key Lab Syst Biol, Shanghai 200031, Peoples R China 2.Chinese Acad Sci, Grad Sch, Shanghai 200031, Peoples R China 3.Shanghai Ctr Bioinformat Technol, Shanghai 200235, Peoples R China 4.Shanghai Jiao Tong Univ, Coll Life Sci & Biotechnol, Shanghai 200240, Peoples R China 5.Shanghai Tongji Univ, Coll Life Sci & Biotechnol, Shanghai 200331, Peoples R China |
| 推荐引用方式 GB/T 7714 | Yu, Yao,Tu, Kang,Zheng, Siyuan,et al. Geogle: context mining tool for the correlation between gene expression and the phenotypic distinction[J]. Bmc bioinformatics,2009,10:7. |
| APA | Yu, Yao.,Tu, Kang.,Zheng, Siyuan.,Li, Yun.,Ding, Guohui.,...&Li, Yixue.(2009).Geogle: context mining tool for the correlation between gene expression and the phenotypic distinction.Bmc bioinformatics,10,7. |
| MLA | Yu, Yao,et al."Geogle: context mining tool for the correlation between gene expression and the phenotypic distinction".Bmc bioinformatics 10(2009):7. |
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