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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 S., et al. (2019) <doi:10.1093/bib/bby065>.
| Version: | 1.1.6 |
| Depends: | R (≥ 2.10) |
| Imports: | seqinr (≥ 2.1-3), e1071 (≥ 1.0), parallel (≥ 2.1.0), caret (≥ 6.0-71) |
| Published: | 2024-09-28 |
| DOI: | 10.32614/CRAN.package.LncFinder |
| Author: | Siyu Han [aut, cre], Ying Li [aut], Yanchun Liang [aut] |
| Maintainer: | Siyu Han <siyu.han at tum.de> |
| License: | GPL-3 |
| URL: | https://lncfinder.osubmi.org/ |
| NeedsCompilation: | no |
| Citation: | LncFinder citation info |
| Materials: | README NEWS |
| CRAN checks: | LncFinder results |
| Reference manual: | LncFinder.pdf |
| Package source: | LncFinder_1.1.6.tar.gz |
| Windows binaries: | r-devel: LncFinder_1.1.6.zip, r-release: LncFinder_1.1.6.zip, r-oldrel: LncFinder_1.1.6.zip |
| macOS binaries: | r-release (arm64): LncFinder_1.1.6.tgz, r-oldrel (arm64): LncFinder_1.1.6.tgz, r-release (x86_64): LncFinder_1.1.6.tgz, r-oldrel (x86_64): LncFinder_1.1.6.tgz |
| Old sources: | LncFinder archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.