NetceRNA: An algorithm for construction of phenotype-specific regulation networks via competing endogenous RNAs

Mario Flores, Yufei Huang, Yidong Chen

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

Abstract

By using the competing endogenous RNA (ceRNA) concept, we implemented a web-based application TraceRNA. TraceRNA allows us to interactively construct a regulation network for a specific phenotype by using a disease-specific transcriptome data. In this work, we further extend the TraceRNA with a novel algorithm implementation where we examined the microRNA expression derived from same disease type. The proposed algorithm, NetceRNA, finds an optimized network representation under a certain phenotype context by iteratively perturbing the network and measuring the network configuration change with respect to the original ceRNA network. The resulting algorithm outputs an improved network together with a ranked list of genes and miRNAs which are characteristic of the specific phenotype. To illustrate the utility of NetceRNA, gene expression and microRNA expression data of breast cancer study from The Cancer Genome Atlas (TCGA) were used.

Original languageEnglish (US)
Title of host publication2013 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2013 - Proceedings
Pages24-27
Number of pages4
DOIs
StatePublished - Dec 1 2013
Event2013 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2013 - Houston, TX, United States
Duration: Nov 17 2013Nov 19 2013

Publication series

NameProceedings - IEEE International Workshop on Genomic Signal Processing and Statistics
ISSN (Print)2150-3001
ISSN (Electronic)2150-301X

Other

Other2013 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2013
CountryUnited States
CityHouston, TX
Period11/17/1311/19/13

Keywords

  • ceRNAs
  • gene regulatory network
  • microRNAs

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology (miscellaneous)
  • Computational Theory and Mathematics
  • Signal Processing
  • Biomedical Engineering

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