Introduction

Experimental spatial proteomics, i.e. the high-throughput assignment of proteins to sub-cellular compartments based on quantitative proteomics data, promises to shed new light on many biological processes given adequate computational tools.Here we present pRoloc, a complete infrastructure to support and guide the sound analysis of quantitative mass-spectrometry-based spatial proteomics data. It provides functionality for unsupervised and supervised machine learning for data exploration and protein classification and novelty detection to identify new putative sub-cellular clusters. The software builds upon existing infrastructure for data management and data processing.

Publications

  1. Mass-spectrometry-based spatial proteomics data analysis using pRoloc and pRolocdata.
    Cite this
    Gatto L, Breckels LM, Wieczorek S, Burger T, Lilley KS, 2014-05-01 - Bioinformatics (Oxford, England)

Credits

  1. Laurent Gatto
    Developer

    Computational Proteomics Unit and Cambridge Centre for Proteomics, Department of Biochemistry, France

  2. Lisa M Breckels
    Developer

  3. Samuel Wieczorek
    Developer

  4. Thomas Burger
    Developer

  5. Kathryn S Lilley
    Investigator

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Summary
AccessionBT000216
Tool TypeApplication
Category
PlatformsLinux/Unix
TechnologiesR
User InterfaceTerminal Command Line
Download Count0
Submitted ByKathryn S Lilley