GenProSeq

DOI: 10.18129/B9.bioc.GenProSeq    

This is the development version of GenProSeq; for the stable release version, see GenProSeq.

Generating Protein Sequences with Deep Generative Models

Bioconductor version: Development (3.16)

Generative modeling for protein engineering is key to solving fundamental problems in synthetic biology, medicine, and material science. Machine learning has enabled us to generate useful protein sequences on a variety of scales. Generative models are machine learning methods which seek to model the distribution underlying the data, allowing for the generation of novel samples with similar properties to those on which the model was trained. Generative models of proteins can learn biologically meaningful representations helpful for a variety of downstream tasks. Furthermore, they can learn to generate protein sequences that have not been observed before and to assign higher probability to protein sequences that satisfy desired criteria. In this package, common deep generative models for protein sequences, such as variational autoencoder (VAE), generative adversarial networks (GAN), and autoregressive models are available. In the VAE and GAN, the Word2vec is used for embedding. The transformer encoder is applied to protein sequences for the autoregressive model.

Author: Dongmin Jung [cre, aut]

Maintainer: Dongmin Jung <dmdmjung at gmail.com>

Citation (from within R, enter citation("GenProSeq")):

Installation

To install this package, start R (version "4.2") and enter:

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("GenProSeq")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("GenProSeq")

 

HTML R Script GenProSeq
PDF   Reference Manual
Text   NEWS

Details

biocViews Proteomics, Software
Version 1.1.0
In Bioconductor since BioC 3.15 (R-4.2) (< 6 months)
License Artistic-2.0
Depends keras, mclust, R (>= 4.2)
Imports tensorflow, word2vec, DeepPINCS, ttgsea, CatEncoders, reticulate, stats
LinkingTo
Suggests knitr, testthat, rmarkdown
SystemRequirements
Enhances
URL
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report  

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package GenProSeq_1.1.0.tar.gz
Windows Binary GenProSeq_1.1.0.zip
macOS 10.13 (High Sierra) GenProSeq_1.1.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/GenProSeq
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/GenProSeq
Package Short Url https://bioconductor.org/packages/GenProSeq/
Package Downloads Report Download Stats

Documentation »

Bioconductor

R / CRAN packages and documentation

Support »

Please read the posting guide. Post questions about Bioconductor to one of the following locations: