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pRoloc: A unifying bioinformatics framework for spatial proteomics
Version 1.16.1
This package implements pattern recognition techniques on quantitiative mass spectrometry data to infer protein sub-cellular localisation.
Getting started
Package overview
A transfer learning algorithm for spatial proteomics
HUPO 2011 poster: pRoloc -- A unifying bioinformatics framework for organelle proteomics
HUPO 2014 poster: A state-of-the-art machine learning pipeline for the analysis of spatial proteomics data
Machine learning techniques available in pRoloc
pRoloc tutorial
Annotating spatial proteomics data
Browse package contents
Package details |
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| Author | Laurent Gatto and Lisa M. Breckels with contributions from Thomas Burger and Samuel Wieczorek |
| Bioconductor views | Classification Clustering MassSpectrometry Proteomics QualityControl |
| Maintainer | Laurent Gatto <[email protected]> |
| License | GPL-2 |
| Version | 1.16.1 |
| URL | https://github.com/lgatto/pRoloc |
| Package repository | View on Bioconductor |
| Installation |
Install the latest version of this package by entering the following in R:
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