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A semi-supervised Bayesian approach for simultaneous protein sub-cellular localisation assignment an...

A semi-supervised Bayesian approach for simultaneous protein sub-cellular localisation assignment an...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_be2f8d51ad0b455b86c3fa544d4a23a9

A semi-supervised Bayesian approach for simultaneous protein sub-cellular localisation assignment and novelty detection

About this item

Full title

A semi-supervised Bayesian approach for simultaneous protein sub-cellular localisation assignment and novelty detection

Publisher

United States: Public Library of Science

Journal title

PLoS computational biology, 2020-11, Vol.16 (11), p.e1008288-e1008288

Language

English

Formats

Publication information

Publisher

United States: Public Library of Science

More information

Scope and Contents

Contents

The cell is compartmentalised into complex micro-environments allowing an array of specialised biological processes to be carried out in synchrony. Determining a protein's sub-cellular localisation to one or more of these compartments can therefore be a first step in determining its function. High-throughput and high-accuracy mass spectrometry-base...

Alternative Titles

Full title

A semi-supervised Bayesian approach for simultaneous protein sub-cellular localisation assignment and novelty detection

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_be2f8d51ad0b455b86c3fa544d4a23a9

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_be2f8d51ad0b455b86c3fa544d4a23a9

Other Identifiers

ISSN

1553-7358,1553-734X

E-ISSN

1553-7358

DOI

10.1371/journal.pcbi.1008288

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