Package: PredCRG 1.0.2

PredCRG: Computational Prediction of Proteins Encoded by Circadian Genes

A computational model for predicting proteins encoded by circadian genes. The support vector machine has been employed with Laplace kernel for prediction of circadian proteins, where compositional, transitional and physico-chemical features were utilized as numeric features. User can predict for the test dataset using the proposed computational model. Besides, the user can also build their own training model using their training dataset, followed by prediction for the test set.

Authors:Prabina Kumar Meher <[email protected]>

PredCRG_1.0.2.tar.gz
PredCRG_1.0.2.zip(r-4.5)PredCRG_1.0.2.zip(r-4.4)PredCRG_1.0.2.zip(r-4.3)
PredCRG_1.0.2.tgz(r-4.4-any)PredCRG_1.0.2.tgz(r-4.3-any)
PredCRG_1.0.2.tar.gz(r-4.5-noble)PredCRG_1.0.2.tar.gz(r-4.4-noble)
PredCRG_1.0.2.tgz(r-4.4-emscripten)PredCRG_1.0.2.tgz(r-4.3-emscripten)
PredCRG.pdf |PredCRG.html
PredCRG/json (API)

# Install 'PredCRG' in R:
install.packages('PredCRG', repos = c('https://prabinameher.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • PredCRG_data - Training dataset of the PredCRG model.
  • model1 - Trained model with the Q1 dataset.
  • model2 - Trained model with the Q2 dataset.
  • model3 - Trained model with the Q3 dataset.
  • model4 - Trained model with the Q4 dataset.
  • test - Test dataset.

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 136 downloads 1 mentions 3 exports 27 dependencies

Last updated 4 years agofrom:359bbf52e8. Checks:OK: 5 WARNING: 1 NOTE: 1. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 01 2024
R-4.5-winNOTENov 01 2024
R-4.5-linuxWARNINGNov 01 2024
R-4.4-winOKNov 01 2024
R-4.4-macOKNov 01 2024
R-4.3-winOKNov 01 2024
R-4.3-macOKNov 01 2024

Exports:PredCRGPredCRG_EncPredCRG_training

Dependencies:askpassBiocGenericsBiostringsclasscrayoncurle1071genericsGenomeInfoDbGenomeInfoDbDatahttrIRangesjsonlitekernlabMASSmimeopensslPeptidesprotrproxyR6RcppS4VectorssysUCSC.utilsXVectorzlibbioc