A semi-supervised Bayesian approach for simultaneous protein sub-cellular localisation assignment and novelty detection.
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. H...
Main Authors: | Oliver M Crook, Aikaterini Geladaki, Daniel J H Nightingale, Owen L Vennard, Kathryn S Lilley, Laurent Gatto, Paul D W Kirk |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2020-11-01
|
Series: | PLoS Computational Biology |
Online Access: | https://doi.org/10.1371/journal.pcbi.1008288 |
Similar Items
-
Combining LOPIT with differential ultracentrifugation for high-resolution spatial proteomics
by: Aikaterini Geladaki, et al.
Published: (2019-01-01) -
A Bayesian semi-parametric model for thermal proteome profiling
by: Siqi Fang, et al.
Published: (2021-06-01) -
A Bayesian mixture modelling approach for spatial proteomics.
by: Oliver M Crook, et al.
Published: (2018-11-01) -
Inferring differential subcellular localisation in comparative spatial proteomics using BANDLE
by: Oliver M. Crook, et al.
Published: (2022-10-01) -
A Bioconductor workflow for the Bayesian analysis of spatial proteomics [version 1; peer review: 1 approved, 2 approved with reservations]
by: Oliver M. Crook, et al.
Published: (2019-04-01)