To screen the effective software for analysing gene interactions from Kashin-Beck disease genome profiling pathway and network, according to the tool of GeneMANIA. (2015)

• Record Type: Journal Article
• Authors: Wang, Sen; Wang, Weizhuo; Zhao, Junjie; Zhang, Feng; He, Shulan; Guo, Xiong
• Is Part Of: International journal of data mining and bioinformatics. Volume 12:Number 1(2015)
• Page Start: 100
• Page End: 114
• Publication Date: 2015
• Subjects: KBD -- Kashin-Beck disease -- chondrocytic pathways -- chondrocyte -- bioinformatics -- gene microarrays -- network analysis -- pathway analysis -- data mining -- cartilage -- software -- gene interactions -- genome profiling -- significant genes -- gene expression data -- osteochondropathy -- bone disease; Data mining -- Periodicals; Bioinformatics -- Periodicals; 006.312
• Languages: English
• ISSNs: 1748-5673

Abstract

In order to screen the more effective software for the pathway and network analysis of Kashin-Beck disease, gene microarrays, TranscriptomeBrowser, MetaCore and GeneMANIA were used for analysis. Three significant chondrocytic pathways and one network were screened by TranscriptomeBrowser; one significant pathway and one network were identified by MetaCore. BAX, APAF1, CASP6, BCL2, VEGF, SOCS3, BAK, TGFBI, TNFAIP6, TNFRSF11B and THBS1 were significant genes associated with the biological function of chondrocyte or cartilage involved in the TranscriptomeBrowser or MetaCore results. The interactions between the significant genes and their adjacent genes were searched and classified in GeneMANIA. In pathway analysis results, TranscriptomeBrowser is superior to get the interaction of pathway and co-expression compared with MetaCore; MetaCore is superior to get the interaction of physical interaction compared with TranscriptomeBrowser. In network analysis results, TranscriptomeBrowser contains more interaction message of co-localisation, MetaCore contains more interaction message of co-expression.