期刊文献+

iBIG:An Integrative Network Tool for Supporting Human Disease Mechanism Studies

iBIG:An Integrative Network Tool for Supporting Human Disease Mechanism Studies
原文传递
导出
摘要 Understanding the mechanism of complex human diseases is a major scientitic challenge. Towards this end, we developed a web-based network tool named iBIG (stands for integrative BioloGy), which incorporates a variety of information on gene interaction and regulation. The generated network can be annotated with various types of information and visualized directly online. In addition to the gene networks based on physical and pathway interactions, networks at a functional level can also be constructed. Furthermore, a supplementary R package is provided to process microarray data and generate a list of important genes to be used as input for iBIG. To demonstrate its usefulness, we collected 54 microarrays on common human diseases including cancer, neurolog- ical disorders, infectious diseases and other common diseases. We processed the microarray data with our R package and constructed a network of functional modules perturbed in common human diseases. Networks at the functional level in combination with gene networks may provide new insight into the mechanism of human diseases, iBIG is freely available at http://lei.big.ac.cn/ibig. Understanding the mechanism of complex human diseases is a major scientitic challenge. Towards this end, we developed a web-based network tool named iBIG (stands for integrative BioloGy), which incorporates a variety of information on gene interaction and regulation. The generated network can be annotated with various types of information and visualized directly online. In addition to the gene networks based on physical and pathway interactions, networks at a functional level can also be constructed. Furthermore, a supplementary R package is provided to process microarray data and generate a list of important genes to be used as input for iBIG. To demonstrate its usefulness, we collected 54 microarrays on common human diseases including cancer, neurolog- ical disorders, infectious diseases and other common diseases. We processed the microarray data with our R package and constructed a network of functional modules perturbed in common human diseases. Networks at the functional level in combination with gene networks may provide new insight into the mechanism of human diseases, iBIG is freely available at http://lei.big.ac.cn/ibig.
出处 《Genomics, Proteomics & Bioinformatics》 SCIE CAS CSCD 2013年第3期166-171,共6页 基因组蛋白质组与生物信息学报(英文版)
基金 supported by research grants from National Institute of Health to YD(Grant No. GM79383 and GM67168) Natural Science Foundation of China to HL(Grant No.30870474) Scientific Research Foundation for the Returned Overseas Chinese Scholars, State Education Ministry to HL
关键词 NETWORK Functional module Disease mechanism MICROARRAY Web server Network Functional module Disease mechanism Microarray Web server
  • 相关文献

参考文献31

  • 1Chen X, Chen M, Ning K. BNArray: an R package for constructing gene regulatory networks from microarray data by using Bayesian network. Bioinformatics 2006;22:29524.
  • 2Langfelder P, Horvath S. WGCNA: an R package for weighted correlation network analysis. BMC Bioinformatics 2008;9: 559.
  • 3Martin A, Ochagavia ME, Rabasa LC, Miranda J, Fernandez-de- Cossio J, Bringas R. BisoGenet: a new tool for gene network building, visualization and analysis. BMC Bioinformatics 2010;11:91.
  • 4Gao J, Ade AS, Tarcea VG, Weymouth TE, Mirel BR, Jagadish HV, et al. Integrating and annotating the interactome using the MiMI plugin for cytoscape. Bioinformatics 2009;25:137- 8.
  • 5Hernandez-Toro J, Prieto C, De las Rivas J. APID2NET: unified interactome graphic analyzer. Bioinformatics 2007;23:2495- 7.
  • 6Cerami EG, Gross BE, Demir E, Rodchenkov I, Babur O, Anwar N, et al. Pathway commons, a web resource for biological pathway data. Nucleic Acids Res 2011;39:D685 -90.
  • 7Hao T, Ma HW, Zhao XM, Goryanin I. Compartmentalization of the Edinburgh Human Metabolic Network. BMC Bioinfor- matics 2010; 11:393.
  • 8Keshava Prasad TS, Goel R, Kandasamy K, Keerthikumar S, Kumar S, Mathivanan S, et al. Human protein reference database 2009 update. Nucleic Acids Res 2009;37:D767- 72.
  • 9Xenarios I, Salwinski L, Duan X J, Higney P, Kim SM, Eisenberg D. DIP, the Database of Interacting Proteins: a research tool for studying cellular networks of protein interactions. Nucleic Acids Res 2002;30:303-5.
  • 10Ceol A, Chatr Aryamontri A, Licata L, Peluso D, Briganti L, et al. MINT, the molecular interaction database: 2009 update. Nucleic Acids Res 2010;38:D532 -9.

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部