Daniel Pasaila, Irina Mohorianu, Andrei Sucila, Stefan Pantiru, Liviu Ciortuz

We designed a new SVM for microRNA identification,whose novelty is two-folded: firstly many of its features incorporatethe base-pairing probabilities provided by McCaskill’s algorithm, and secondly the classification performanceis improved by using a certain similarity (“profile”-based) measure between the training and test microRNAsand a set of carefully chosen (“pivot”) RNA sequences.Comparisons with some of the best existing SVMs for microRNAidentification prove that our SVM obtains trulycompetitive results.

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author = "Daniel Pasail{u a}, Irina Mohorianu, Andrei Sucil{u a}, {c S}tefan Pan{c t}iru, Liviu Ciortuz",
title = "{Yet Another SVM for MiRNA Recognition: yasMiR}",
institution = "``Al.I.Cuza'' University of Ia{c s}i, 
                 Faculty of Computer Science",
year = "2010",
number = "TR 10-01",
note = "URL:http://www.infoiasi.ro/~tr/tr.pl.cgi"