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Support Vector Regression (SVR)

A version of SVM for regression was proposed in 1996 by Vladimir N. Vapnik, Harris Drucker, Christopher J. C. Burges, Linda Kaufman and Alexander J. Smola. This method is called support vector regression (SVR). The model produced by support vector classification (as described above) depends only on a subset of the training data, because the cost function for building the model does not care about training points that lie beyond the margin. [Source: Wikipedia ]

miRanda (microRNA.org)

Submitted by ChenLiang on Fri, 09/02/2016 - 21:59

The recent discoveries of microRNA (miRNA) genes and characterization of the first few target genes regulated by miRNAs in Caenorhabditis elegans and Drosophila melanogaster have set the stage for elucidation of a novel network of regulatory control. We present a computational method for whole-genome prediction of miRNA target genes. The method is validated using known examples.

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p-TAREF

Submitted by ChenLiang on Fri, 09/02/2016 - 21:59

miRNAs are ~21 nucleotide long small noncoding RNA molecules, formed endogenously in most of the eukaryotes, which mainly control their target genes post transcriptionally by interacting and silencing them. While a lot of tools has been developed for animal miRNA target system, plant miRNA target identification system has witnessed limited development. Most of them have been centered around exact complementarity match. Very few of them considered other factors like multiple target sites and role of flanking regions.

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