Functional combination strategy for prioritization of human miRNA target |
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Authors: | Jing Li Yunpeng Zhang Yingying Wang Chunlong Zhang Qiuyu Wang Xinrui Shi Chunquan Li Ruijie Zhang Xia Li |
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Institution: | 1. College of Bioinformatics Science and Technology, Harbin Medical University, 194 Xuefu Road, Harbin 150081, China;2. Research Center for Biomedical Information Technology, Shenzhen Institutes of Advanced Technologies, Chinese Academy of Sciences, Xueyuan Road, Shenzhen 518055, China |
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Abstract: | MicroRNAs (miRNAs) are a class of non-coding RNAs known to play important regulatory roles through targets, which can affect human cell proliferation, differentiation, and metabolism. Overlaps between different miRNA target prediction algorithms (MTPAs) are small, which limit the understanding of miRNA's biological functions. However, the overlaps increase on functional levels, such as Gene Ontology (GO), Protein–Protein Interaction Network (PPIN) and pathways. Here, we performed prioritization on existing predicted target sets for each miRNA by considering all the possible combinations of 7 functional levels. After analyzing the results of both single and multiple functional levels, we found that functional combination strategies including pathways and GO performed better in the prioritization of human miRNA target. The combination which performed best was “Pathway + GO BP + GO MF + GO CC + Target + PPIN”. For the prioritized result of this combination, the valid target had top ranking, and our method performed better than the MTPAs after comparison adopting the validated ranking levels. Top genes in ranking lists generated by this strategy were either validated by experiments or share same functions with the corresponding miRNA/its validated genes in disease related biological processes. |
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