A bayesian decision fusion approach for microRNA target prediction
Yue,Dong1; Liu,Hui2; Lu,Ming Zhu1; Chen,Philip3; Chen,Yidong4; Huang,Yufei1,4
Source Publication2010 ACM International Conference on Bioinformatics and Computational Biology, ACM-BCB 2010
AbstractMicroRNAs (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. Copyright © 2010 ACM.
KeywordBayesian network MicroRNA target prediction
URLView the original
Scopus ID2-s2.0-77958029420
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Document TypeConference paper
CollectionUniversity of Macau
Corresponding AuthorYue,Dong
Affiliation1.Department of ECE,University of Texas,San Antonio,United States
2.SIEE,China University of Mining and Technology,China
3.Science and Technology,University of Macau,China
4.Greehey Children's Cancer Research Institute,University of Texas Health Science Center,San Antonio,United States
Recommended Citation
GB/T 7714
Yue,Dong,Liu,Hui,Lu,Ming Zhu,et al. A bayesian decision fusion approach for microRNA target prediction[C],2010:214-221.
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