Статья

KOBAS 2.0: a web server for annotation and identification of enriched pathways and diseases

Chen XieCenter for Bioinformatics, State Key Laboratory of Protein and Plant Gene Research, College of Life Sciences, Peking University, Beijing, ChinaXizeng MaoComputational Systems Biology Lab, Department of Biochemistry and Molecular Biology, and Institute of Bioinformatics, University of Georgia, USA,Jiaju HuangCenter for Bioinformatics, State Key Laboratory of Protein and Plant Gene Research, College of Life Sciences, Peking University, Beijing, China,Yang DingCenter for Bioinformatics, State Key Laboratory of Protein and Plant Gene Research, College of Life Sciences, Peking University, Beijing, China,Jianmin WuCancer Research Program, Garvan Institute of Medical Research, 384 Victoria Street, Darlinghurst, NSW, Australia andShan DongCenter for Bioinformatics, State Key Laboratory of Protein and Plant Gene Research, College of Life Sciences, Peking University, Beijing, China,Lei KongCenter for Bioinformatics, State Key Laboratory of Protein and Plant Gene Research, College of Life Sciences, Peking University, Beijing, China,Ge GaoCenter for Bioinformatics, State Key Laboratory of Protein and Plant Gene Research, College of Life Sciences, Peking University, Beijing, China,Chuan‐Yun LiLaboratory of Bioinformatics and Genomic Medicine, Institute of Molecular Medicine, Peking University, Beijing, ChinaLiping WeiCenter for Bioinformatics, State Key Laboratory of Protein and Plant Gene Research, College of Life Sciences, Peking University, Beijing, China,

2011en

ABI

Аннотация

High-throughput experimental technologies often identify dozens to hundreds of genes related to, or changed in, a biological or pathological process. From these genes one wants to identify biological pathways that may be involved and diseases that may be implicated. Here, we report a web server, KOBAS 2.0, which annotates an input set of genes with putative pathways and disease relationships based on mapping to genes with known annotations. It allows for both ID mapping and cross-species sequence similarity mapping. It then performs statistical tests to identify statistically significantly enriched pathways and diseases. KOBAS 2.0 incorporates knowledge across 1327 species from 5 pathway databases (KEGG PATHWAY, PID, BioCyc, Reactome and Panther) and 5 human disease databases (OMIM, KEGG DISEASE, FunDO, GAD and NHGRI GWAS Catalog). KOBAS 2.0 can be accessed at http://kobas.cbi.pku.edu.cn.

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Идентификаторы

DOI: 10.1093/nar/gkr483

Цитирования и источники

Цитирований: 3Использованных источников: 0

Показатели — AkademScholar