Pinned Repositories
AutoRT
AutoRT: Peptide retention time prediction using deep learning
deep_learning_in_proteomics
A list of tools on proteomics using deep learning
neoflow
NeoFlow: a proteogenomics pipeline for neoantigen discovery
OmicsEV
A tool for large scale omics datasets evaluation
PepQuery
PepQuery: a targeted peptide search engine
Customprodbj
Customized protein database construction
metaX
metaX: a flexible and comprehensive software for processing omics data.
PDV
PDV: an integrative proteomics data viewer
PGA
PGA: a tool for ProteoGenomics Analysis
proteoQC
proteoQC: an R package for proteomics data quality assessment.
wenbostar's Repositories
wenbostar/PDV
PDV: an integrative proteomics data viewer
wenbostar/metaX
metaX: a flexible and comprehensive software for processing omics data.
wenbostar/Customprodbj
Customized protein database construction
wenbostar/PGA
PGA: a tool for ProteoGenomics Analysis
wenbostar/proteoQC
proteoQC: an R package for proteomics data quality assessment.
wenbostar/alphapeptdeep_dia
wenbostar/IQuant
IQuant: An automated pipeline for quantitative proteomics based upon isobaric tags
wenbostar/alphapeptdeep
Deep learning framework for proteomics
wenbostar/alpharaw
An open-source Python package to unify raw MS data accession and storage.
wenbostar/ColabFold
Making Protein folding accessible to all via Google Colab!
wenbostar/compomics-utilities
Open source Java library for computational proteomics
wenbostar/DeepDIA
Using deep learning to generate in silico spectral libraries for data-independent acquisition analysis.
wenbostar/DeepLC
DeepLC: Retention time prediction for (modified) peptides using Deep Learning.
wenbostar/DeepLFQ
wenbostar/DeepPhos
wenbostar/ggpubr
'ggplot2' Based Publication Ready Plots
wenbostar/kBET
An R package to test for batch effects in high-dimensional single-cell RNA sequencing data.
wenbostar/moFF
A modest Feature Finder (moFF) to extract MS1 intensities from Thermo raw file
wenbostar/MusiteDeep
MusiteDeep provides a deep-learning method for general and kinase-specific phosphorylation site prediction. It is implemented by deep learning library Keras and Theano backend (the Keras2.0 and Tensorflow backend were also provided under folder MusiteDeep_Keras2.0). At present, MusiteDeep only provides prediction of human phosphorylation sites; however, it also provides customized model training that enables users to train other PTM prediction models by using their own training data sets based on either CPU or GPU.
wenbostar/MusiteDeep_web
This repository contains the stand-alone tool for MusiteDeep server
wenbostar/nf-skyline-dia-ms
wenbostar/pDeep
pDeep: Predicting MS/MS Spectra of Peptides with Deep Learning
wenbostar/pDeep2-docker
wenbostar/pepmap
wenbostar/PGA-docker
wenbostar/PGA_Annotation_Data
wenbostar/PredFull
Predicting Complete Tandem Mass Spectra
wenbostar/PredGly
wenbostar/prosit
Prosit offers high quality MS2 predicted spectra for any organism and protease as well as iRT prediction. When using Prosit is helpful for your research, please cite "Gessulat, Schmidt et al. 2019" DOI 10.1038/s41592-019-0426-7
wenbostar/wenbostar
Config files for my GitHub profile.