Proteomics

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Prediction of protein complexes in Trypanosoma brucei by protein correlation profiling mass spectrometry and machine learning


ABSTRACT: A disproportionate number of predicted proteins from the genome sequence of the protozoan parasite Trypanosoma brucei, an important human and animal pathogen, are hypothetical proteins of unknown function. This work describes a protein correlation profiling mass spectrometry approach, using two size exclusion and one ion exchange chromatography systems, to derive sets of predicted protein complexes in this organism by hierarchical clustering and machine learning methods. We provide examples of both potential new subunits of known protein complexes and of novel trypanosome complexes of suggested function, contributing to improving the functional annotation of the trypanosome proteome. These hypothesis-generating proteomic data are provided in an open access online data visualisation environment (http://134.36.66.166:8083/complex_explorer)

INSTRUMENT(S): Q Exactive

ORGANISM(S): Trypanosoma Brucei

SUBMITTER: Thomas Crozier  

LAB HEAD: Angus Lamond

PROVIDER: PXD005968 | Pride | 2018-04-13

REPOSITORIES: Pride

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Prediction of Protein Complexes in <i>Trypanosoma brucei</i> by Protein Correlation Profiling Mass Spectrometry and Machine Learning.

Crozier Thomas W M TWM   Tinti Michele M   Larance Mark M   Lamond Angus I AI   Ferguson Michael A J MAJ  

Molecular & cellular proteomics : MCP 20171017 12


A disproportionate number of predicted proteins from the genome sequence of the protozoan parasite <i>Trypanosoma brucei</i>, an important human and animal pathogen, are hypothetical proteins of unknown function. This paper describes a protein correlation profiling mass spectrometry approach, using two size exclusion and one ion exchange chromatography systems, to derive sets of predicted protein complexes in this organism by hierarchical clustering and machine learning methods. These hypothesis  ...[more]

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