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 (3.18)
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("GenProSeq")):
Installation
To install this package, start R (version "4.3") 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")| GenProSeq | HTML | R Script |
| Reference Manual | ||
| NEWS | Text |
Details
| biocViews | Proteomics, Software |
| Version | 1.5.2 |
| In Bioconductor since | BioC 3.15 (R-4.2) (1.5 years) |
| License | Artistic-2.0 |
| Depends | keras, mclust, R (>= 4.2) |
| Imports | tensorflow, word2vec, DeepPINCS, ttgsea, CatEncoders, reticulate, stats |
| Linking To | |
| Suggests | ggseqlogo, VAExprs, stringdist, knitr, testthat, rmarkdown |
| System Requirements | |
| Enhances | |
| URL |
See More
| 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_1.5.2.tar.gz |
| Windows Binary | GenProSeq_1.5.2.zip |
| macOS Binary (x86_64) | GenProSeq_1.5.2.tgz |
| macOS Binary (arm64) | GenProSeq_1.5.2.tgz |
| Source Repository | git clone https://git.bioconductor.org/packages/GenProSeq |
| Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/GenProSeq |
| Bioc Package Browser | https://code.bioconductor.org/browse/GenProSeq/ |
| Package Short Url | https://bioconductor.org/packages/GenProSeq/ |
| Package Downloads Report | Download Stats |