https://github.com/michbur/amylogram

Prediction of amyloid proteins
https://github.com/michbur/amylogram

Last synced: 9 days ago
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Prediction of amyloid proteins

• Host: GitHub
• URL: https://github.com/michbur/amylogram
• Owner: michbur
• Created: 2016-09-21T10:43:57.000Z (about 8 years ago)
• Default Branch: master
• Last Pushed: 2020-05-21T19:42:02.000Z (over 4 years ago)
• Last Synced: 2024-10-23T15:32:13.273Z (26 days ago)
• Language: R
• Homepage:
• Size: 1.47 MB
• Stars: 9
• Watchers: 4
• Forks: 1
• Open Issues: 2
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGELOG

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README

        
[![published in: Scientific Reports](https://img.shields.io/badge/published%20in-Scientific%20Reports-green.svg)](https://doi.org/10.1038/s41598-017-13210-9)

[![CRAN_Status_Badge](http://www.r-pkg.org/badges/version/AmyloGram)](https://cran.r-project.org/package=AmyloGram)

[![Downloads](http://cranlogs.r-pkg.org/badges/AmyloGram)](https://cran.r-project.org/package=AmyloGram)

[![Build Status](https://api.travis-ci.org/michbur/AmyloGram.png)](https://travis-ci.org/michbur/AmyloGram)



Predict amyloid proteins

-------------------------

AmyloGram predicts amyloid proteins using n-gram encoding and random forests. It can be also accessed as a web-based service http://www.smorfland.uni.wroc.pl/shiny/AmyloGram/. 

Local instance of AmyloGram

------------------------

AmyloGram can be used installed from CRAN as the R package:

```R

install.packages("AmyloGram")

```

You can install the latest development version of the package:

```R

source("https://raw.githubusercontent.com/r-lib/remotes/master/install-github.R")$value("michbur/AmyloGram")

```

After installation GUI can be accessed locally:

```R

library(AmyloGram)

AmyloGram_gui()

```

Predictions might be also made in the batch mode:

```R

data(AmyloGram_model)

data(pep424)

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

```