@article{6b1652af3f574658888b1659ec076ce4,
title = "A Bayesian decision fusion approach for microRNA target prediction.",
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. All the related materials including genome-wide prediction of human targets and a web-based tool are available at http://compgenomics.utsa.edu/gene/gene_1.php.",
author = "Dong Yue and Maozu Guo and Yidong Chen and Yufei Huang",
note = "Funding Information: ICRST.2010 022). The authors wish to acknowledge computational support provided by the UTSA Computational Systems Biology Core Facility (NIH RCMI grant 5G12RR013646-12). This article has been published as part of BMC Bioinformatics Volume 13 Supplement 17, 2012: Eleventh International Conference on Bioinformatics (InCoB2012): Bioinformatics. The full contents of the supplement are available online at http://www.biomedcentral.com/bmcbioinformatics/ supplements/13/S17 Funding Information: Y. Huang is supported by National Institute of Health (R01 CA096512, 5G12RR013646-12), and Qatar National Research Fund (09-874-3-235). M. Guo is supported by Natural Science Foundation of China (60932008 and 61172098) and Fundamental Research Funds for the Central Universities (HIT.",
year = "2012",
doi = "10.1186/1471-2164-13-s8-s13",
language = "English (US)",
volume = "13 Suppl 8",
journal = "Research in Microbiology",
issn = "0923-2508",
publisher = "Elsevier Masson SAS",
}