期刊
FEBS JOURNAL
卷 276, 期 8, 页码 2150-2156出版社
WILEY
DOI: 10.1111/j.1742-4658.2009.06933.x
关键词
bioinformatics; machine learning; microRNA; microRNA target
资金
- NATIONAL CANCER INSTITUTE [P30CA010815] Funding Source: NIH RePORTER
The discovery that microRNAs (miRNAs) are synthesized as hairpin-containing precursors and share many features has stimulated the development of several computational approaches for identifying new miRNA genes in various animal species. Many of these approaches rely heavily on conservation of sequence within and between species, whereas others emphasize machine-learning methods to screen hairpin candidates for structural features shared with known miRNA precursors. The identification of animal miRNA targets is a particularly difficult problem because an exact match to the target sequence is not required. We discuss the most recently devised algorithms for miRNA and target discovery. We do not discuss plant miRNAs because their varying sizes and structural characteristics pose different problems of identification and target selection.
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