Discovery of inflammatory bowel disease-associated miRNAs using a novel bipartite clustering approach.

摘要: Multidimensional data mining from an integrated environment of different sources is frequently performed in computational system biology. The molecular mechanism the analysis a complex network gene-miRNA can aid to diagnosis and treatment associated diseases. In this work, we mainly focus on finding inflammatory bowel disease (IBD) microRNAs (miRNAs) by biclustering miRNA-target interactions aided known IBD risk genes their miRNAs collected several sources. We rank attributing dataset size connectivity miRNA regulatory modules biclusters. search association some top-ranking related also discovered diseases evaluate similarity those IBD. According literature, our results show significance or ratio supports ranking method where top 20 has approximately tenfold attachment genes. From disease-associated found that 71% attached more than 0.75 scores successfully identify scoring formula method. This be promising approach for isolating similar types