A study of microRNAs in silico and in vivo: bioinformatics approaches to microRNA discovery and target identification

被引:53
作者
Yousef, Malik [1 ,2 ]
Showe, Louise [3 ]
Showe, Michael [3 ]
机构
[1] Galilee Soc, Ctr Res & Dev, Inst Appl Res, IL-20200 Shefa Amr, Israel
[2] Al Qasemi Acad Coll, Baqa Algharbiya, Israel
[3] Wistar Inst Anat & Biol, Syst Biol Div, Philadelphia, PA 19104 USA
关键词
bioinformatics; machine learning; microRNA; microRNA target; SUPPORT VECTOR MACHINE; BINDING-SITES; PREDICTION; SEQUENCE; GENES; PRECURSORS; GENOMICS; DATABASE; MODEL; BAYES;
D O I
10.1111/j.1742-4658.2009.06933.x
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
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.
引用
收藏
页码:2150 / 2156
页数:7
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