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.


AmyloGram predicts presence of signal peptides in eukaryotic proteins using hidden semi-Markov models. The implemented algorithm can be accessed as a web-based service www.smorfland.uni.wroc.pl/AmyloGram

AmyloGram can be also used locally as the R package. It can be installed from CRAN using:

install.packages("AmyloGram")

You can install the latest development version of the code using the devtools R package.

 
library(devtools)
install_github("michbur/AmyloGram")

After installation GUI can be accessed locally:

library(AmyloGram)
AmyloGram_gui()

Predictions might be also made in the batch mode:

data(AmyloGram_model)
data(pep424)
predict(AmyloGram_model, pep424[1L:20])

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Reference manual

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install.packages("AmyloGram")

1.0 by Michal Burdukiewicz, 8 months ago


https://github.com/michbur/AmyloGram


Report a bug at https://github.com/michbur/AmyloGram/issues


Browse source code at https://github.com/cran/AmyloGram


Authors: Michal Burdukiewicz [cre, aut], Piotr Sobczyk [ctb], Stefan Roediger [ctb]


Documentation:   PDF Manual  


GPL-3 license


Imports biogram, ranger, seqinr, shiny

Suggests DT, ggplot2, knitr, markdown, rmarkdown


See at CRAN