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Screening for cancer associated MiRNAs through co-gene, co-function and co-pathway analysis

  • Xue Xiao
  • , Dongguo Li
  • , Lei Gao
  • , Xia Li
  • , Qianghu Wang
  • , Shaojun Zhang
  • , Zhicheng Liu

Research output: Contribution to journalArticlepeer-review

Abstract

MicroRNAs (miRNAs) though present themselves as a group of non-coding small RNAs play critical roles in many biological and pathological processes. Among which the regulation of human cancer is one of the most excited potentiality. The goal of this study is to obtain miRNAs robustly associated with cancer by screening all of the possible miRNAs/cancer pairs in three consecutive steps. First, in co-gene analysis, gene set enrichment analysis is carried out for all miRNA/cancer pairs. Second, in co-function analysis, information theoretic similarity on GO is calculated for miRNA/cancer pairs screened from the former step. Third, in co-pathway analysis, pathway enrichment analysis is performed for miRNA/cancer pairs screened from the second step. In this study, we totally included 776 miRNAs and 25 cancer types. As a result, 94 miRNAs were identified with robust association with 17 types of cancer. Meanwhile, 83 pathways with relevance to both miRNAs and cancer were also singled out. This framework provides an effective way to narrow down miRNAs for cancer and to pinpoint corresponding pathways.

Original languageEnglish (US)
Pages (from-to)624-630
Number of pages7
JournalComputers in Biology and Medicine
Volume42
Issue number5
DOIs
StatePublished - May 2012

Keywords

  • Cancer
  • Enrichment analysis
  • MicroRNA
  • Semantic similarity

ASJC Scopus subject areas

  • Computer Science Applications
  • Health Informatics

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