Long non-coding RNAs identification and analysis. Default models are trained with 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. This package can also extract other classic features and build new classifiers. Reference: Han SY., Liang YC., Li Y., et al. (2018) <doi:10.1093/bib/bby065>.
Version: | 1.1.5 |
Depends: | R (≥ 2.10) |
Imports: | seqinr (≥ 2.1-3), e1071 (≥ 1.0), parallel (≥ 2.1.0), caret (≥ 6.0-71) |
Published: | 2021-12-09 |
Author: | Siyu HAN [aut, cre], Ying LI [aut], Yanchun LIANG [aut] |
Maintainer: | Siyu HAN <hansy15 at mails.jlu.edu.cn> |
License: | GPL-3 |
URL: | https://bmbl.bmi.osumc.edu/lncfinder/ |
NeedsCompilation: | no |
Citation: | LncFinder citation info |
Materials: | README NEWS |
CRAN checks: | LncFinder results |
Reference manual: | LncFinder.pdf |
Package source: | LncFinder_1.1.5.tar.gz |
Windows binaries: | r-devel: LncFinder_1.1.5.zip, r-release: LncFinder_1.1.5.zip, r-oldrel: LncFinder_1.1.5.zip |
macOS binaries: | r-release (arm64): LncFinder_1.1.5.tgz, r-oldrel (arm64): LncFinder_1.1.5.tgz, r-release (x86_64): LncFinder_1.1.5.tgz, r-oldrel (x86_64): LncFinder_1.1.5.tgz |
Old sources: | LncFinder archive |
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