miRNA target prediction method based on the combination of multiple algorithms

Authors:
Lin Zhang;Hui Liu;Dong Yue;Hui He;Yufei Huang
Affiliations:
SIEE, China University of Mining and Technology, Xuzhou, China;SIEE, China University of Mining and Technology, Xuzhou, China;ECE, University of Texas at San Antonio;SIEE, China University of Mining and Technology, Xuzhou, China;ECE, University of Texas at San Antonio and GCCRI, University of Texas Health Science Center at San Antonio
Venue:
ICIC'10 Proceedings of the 6th international conference on Advanced intelligent computing theories and applications: intelligent computing
Year:
2010

Citing 2
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Abstract

MicroRNAs(miRNAs) are around 22 nucleotides known to have important post-transcriptional regulatory functions. The computational target prediction algorithms are important to instruct effective experimental tests. However, different existing algorithms rely on different features and different classifiers, there is a poor agreement between the results of different algorithms. To take full advantage of all the algorithms, we proposed an algorithm to combine the prediction of different algorithms based on decision fusion. This approach was evaluated and tested on the ground truth retrieved from proteomics data. The results show that this method improves the sensitivity, specificity and consistency of each individual algorithm.