biogram - N-Gram Analysis of Biological Sequences

Tools for extraction and analysis of various n-grams (k-mers) derived from biological sequences (proteins or nucleic acids). Contains QuiPT (quick permutation test) for fast feature-filtering of the n-gram data.

Last updated 3 months ago

biological-sequencesngram-analysis

7.67 score 10 stars 3 packages 87 scripts 288 downloads

AmyloGram - Prediction of Amyloid Proteins

Predicts amyloid proteins using random forests trained on the n-gram encoded peptides. The implemented algorithm can be accessed from both the command line and shiny-based GUI.

Last updated 5 years ago

4.60 score 9 stars 11 scripts 199 downloads

AmpGram - Prediction of Antimicrobial Peptides

Predicts antimicrobial peptides using random forests trained on the n-gram encoded peptides (10.3390/ijms21124310). The implemented algorithm can be accessed from both the command line and shiny-based GUI. The AmpGram model is too large for CRAN and it has to be downloaded separately from the repository: <https://github.com/michbur/AmpGramModel>.

Last updated 3 years ago

4.38 score 4 stars 5 scripts 223 downloads

CancerGram - Prediction of Anticancer Peptides

Predicts anticancer peptides using random forests trained on the n-gram encoded peptides. The implemented algorithm can be accessed from both the command line and shiny-based GUI. The CancerGram model is too large for CRAN and it has to be downloaded separately from the repository: <https://github.com/BioGenies/CancerGramModel>. For more information see: Burdukiewicz et al. (2020) <doi:10.3390/pharmaceutics12111045>.

Last updated 4 years ago

anticancer-peptidesbioinformaticsk-mern-grampeptide-identificationrandom-forests

3.90 score 4 stars 3 scripts 196 downloads

signalHsmm - Predict Presence of Signal Peptides

Predicts the presence of signal peptides in eukaryotic protein using hidden semi-Markov models. The implemented algorithm can be accessed from both the command line and GUI.

Last updated 5 years ago

3.48 score 2 stars 7 scripts 141 downloads

bcv - Cross-Validation for the SVD (Bi-Cross-Validation)

Methods for choosing the rank of an SVD (singular value decomposition) approximation via cross validation. The package provides both Gabriel-style "block" holdouts and Wold-style "speckled" holdouts. It also includes an implementation of the SVDImpute algorithm. For more information about Bi-cross-validation, see Owen & Perry's 2009 AoAS article (at <arXiv:0908.2062>) and Perry's 2009 PhD thesis (at <arXiv:0909.3052>).

Last updated 2 years ago

3.20 score 1 stars 16 scripts 308 downloads