About
triplet-SVM classifier

This program is developed for predicting a query sequence
with hairpin structure as a real miRNA precursor or
not. The triplet-SVM classifier analyzes the triplet elements of the query
and predicts it using a SVM classifier. The SVM classifier is previously
trained based on the triplet element features of a set of real miRNA precursors and a set of pseudo-miRNA
hairpins.
triplet-SVM classifier was written by Chenghai Xue and is free to all.
Install
and Use

1. Download the package to
anywhere in your computer
2. Uncompress the file: tar -zxvf
triplet-svm-classifier.tar.gz
3. Read Readme.txt before running the programs
triplet-SVM classifier runs directly on Linux
with Perl compiler.
Note: this
package need the third-party softwares,
namely RNAfold and Libsvm
packages.
RNAfold can be downloaded
from http://www.tbi.univie.ac.at/~ivo/RNA/
Libsvm can be
downloaded from http://www.csie.ntu.edu.tw/~cjlin/libsvm/oldfiles/,
the 2.36 version is used in our work and we recommend this version. (The
homepage of Libsvm is http://www.csie.ntu.edu.tw/~cjlin/libsvm/).
And both softwares should be compiled in local PC.
Download

The package is free for all
users but without any warranty.
Please contact
Chenghai Xue at chenghaixue@gmail.com for the download.
triplet-SVM classifier contains
all source codes for predicting candidate hairpins.
Material contains all results in our
submitted paper.
Citation

If you use triplet-SVM classifier, please cite us in the
following way:
Chenghai Xue, Fei
Li, Tao He, Guoping Liu, Yanda Li, Xuegong Zhang, Classification of real and
pseudo microRNA precursors using local structure-sequence features and
support vector machine, BMC Bioinformatics, 6: 310, 2005
Please contact mailto:chenghaixue@gmail.com
for any problem.
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