LncFinder: Long Non-Coding RNA Identification Based on Features of Sequence, EIIP and Secondary Structure

Functions for predicting sequences are mRNAs or long non-coding RNAs. Default models are trained on human, mouse and wheat datasets by employing SVM. Features are based on intrinsic composition of sequence, EIIP value (electron-ion interaction pseudopotential) and secondary structure. The model can also be built on users' own data.

Version: 1.0.0
Depends: R (≥ 3.2.3), seqinr (≥ 3.1-3), e1071 (≥ 1.6-7), caret (≥ 6.0-71), parallel (≥ 3.1.0)
Published: 2017-02-06
Author: Han Siyu [aut, cre], Li Ying [aut], Liang Yanchun [aut]
Maintainer: Han Siyu <hansy15 at mails.jlu.edu.cn>
License: GPL-3
NeedsCompilation: no
CRAN checks: LncFinder results


Reference manual: LncFinder.pdf
Package source: LncFinder_1.0.0.tar.gz
Windows binaries: r-devel: LncFinder_1.0.0.zip, r-release: LncFinder_1.0.0.zip, r-oldrel: LncFinder_1.0.0.zip
OS X El Capitan binaries: r-release: LncFinder_1.0.0.tgz
OS X Mavericks binaries: r-oldrel: LncFinder_1.0.0.tgz


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