STarMir: a web server for prediction of microRNA binding sites.
STarMir: a web server for prediction of microRNA binding sites.
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DOI：
10.1093/nar/gku376
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发表时间：
2014-07
影响因子：
14.9
通讯作者：
Ding Y
中科院分区：
文献类型：
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作者：
Rennie W;Liu C;Carmack CS;Wolenc A;Kanoria S;Lu J;Long D;Ding Y
STarMir web server predicts microRNA (miRNA) binding sites on a target ribonucleic acid (RNA). STarMir is an implementation of logistic prediction models developed with miRNA binding data from crosslinking immunoprecipitation (CLIP) studies (Liu,C., Mallick, B., Long, D., Rennie, W.A., Wolenc, A., Carmack, C.S. and Ding, Y. (2013). CLIP-based prediction of mammalian microRNA binding sites. Nucleic Acids Res., 41(14), e138). In both intra-dataset and inter-dataset validations, the models showed major improvements over established algorithms in predictions of both seed and seedless sites. General applicability of the models was indicated by good performance in cross-species validations. The input data for STarMir is processed by the web server to perform prediction of miRNA binding sites, compute comprehensive sequence, thermodynamic and target structure features and a logistic probability as a measure of confidence for each predicted site. For each of seed and seedless sites and for all three regions of a mRNA (3′ UTR, CDS and 5′ UTR), STarMir output includes the computed binding site features, the logistic probability and a publication-quality diagram of the predicted miRNA:target hybrid. The prediction results are available through both an interactive viewer and downloadable text files. As an application module of the Sfold RNA package (http://sfold.wadsworth.org), STarMir is freely available to all at http://sfold.wadsworth.org/starmir.html.
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影响因子：
64.5
作者：
Hafner M;Landthaler M;Burger L;Khorshid M;Hausser J;Berninger P;Rothballer A;Ascano M Jr;Jungkamp AC;Munschauer M;Ulrich A;Wardle GS;Dewell S;Zavolan M;Tuschl T
通讯作者：
Tuschl T
影响因子：
14.9
作者：
Ding, Y;Chan, CY;Lawrence, CE
通讯作者：
Lawrence, CE
影响因子：
7
作者：
Siepel, A;Bejerano, G;Haussler, D
通讯作者：
Haussler, D
影响因子：
16.8
作者：
Long, Dang;Lee, Rosalind;Ding, Ye
通讯作者：
Ding, Ye
影响因子：
16.8
作者：
通讯作者：
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