Integration of statistical models and visualization tools to characterize microRNA networks influencing cancer

Kristin R. Delfino, Sandra L. Rodriguez-Zas

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Few consistent biomarkers of cancer survival have been reported. The identification of reliable expression biomarkers requires the simultaneous consideration of microRNAs (miRNA), and associated transcription factors (TFs) and target genes. A novel approach that integrates multivariate survival analysis, feature selection and regulatory network visualization was used to identify reliable biomarkers of ovarian cancer. Expression (799 miRNA and 17,814 TF and target genes) and clinical information on 272 patients diagnosed with ovarian cancer was analyzed. Overall survival was associated (P-value < 0.05) with 16 miRNA, 49 TF and 801 target genes. Among the miRNA, 11 have been associated with ovarian cancer in previous studies and 2 have been associated with other cancers.

Original languageEnglish (US)
Title of host publication2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2011
Pages969-971
Number of pages3
DOIs
StatePublished - 2011
Event2011 IEEE International Conference onBioinformatics and Biomedicine Workshops, BIBMW 2011 - Atlanta, GA, United States
Duration: Nov 12 2011Nov 15 2011

Publication series

Name2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2011

Other

Other2011 IEEE International Conference onBioinformatics and Biomedicine Workshops, BIBMW 2011
Country/TerritoryUnited States
CityAtlanta, GA
Period11/12/1111/15/11

Keywords

  • biomarkers
  • microRNA
  • ovarian cancer
  • systems biology
  • target genes
  • transcription factors

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management

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