A bayesian decision fusion approach for microRNA target prediction

Dong Yue, Hui Liu, Ming Zhu Lu, Philip Chen, Yidong Chen, Yufei Huang

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

5 Scopus citations

Abstract

MicroRNAs (miRNAs) are 19-25 nucleotides non-coding RNAs known to have important post-transcriptional regulatory functions. The computational target prediction algorithm is vital to effective experimental testing. However, since different existing algorithms rely on different features and classifiers, there is a poor agreement among the results of different algorithms. To benefit from the advantages of different algorithms, we proposed an algorithm called BCmicrO that combines the prediction of different algorithms with Bayesian Network. BCmicrO was evaluated using the training data and the proteomic data. The results show that BCmicrO improves both the sensitivity and the specificity of each individual algorithm.

Original languageEnglish (US)
Title of host publication2010 ACM International Conference on Bioinformatics and Computational Biology, ACM-BCB 2010
Pages214-221
Number of pages8
DOIs
StatePublished - 2010
Event2010 ACM International Conference on Bioinformatics and Computational Biology, ACM-BCB 2010 - Niagara Falls, NY, United States
Duration: Aug 2 2010Aug 4 2010

Publication series

Name2010 ACM International Conference on Bioinformatics and Computational Biology, ACM-BCB 2010

Other

Other2010 ACM International Conference on Bioinformatics and Computational Biology, ACM-BCB 2010
CountryUnited States
CityNiagara Falls, NY
Period8/2/108/4/10

Keywords

  • Bayesian network
  • MicroRNA target prediction

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Information Management

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