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SLiMSearch: a webserver for finding novel occurrences of short linear motifs in proteins, incorporating sequence context

SLiMSearch: a webserver for finding novel occurrences of short linear motifs in proteins, incorporating sequence context
SLiMSearch: a webserver for finding novel occurrences of short linear motifs in proteins, incorporating sequence context
Short, linear motifs (SLiMs) play a critical role in many biological processes. The SLiMSearch (Short, Linear Motif Search) webserver is a flexible tool that enables researchers to identify novel occurrences of predefined SLiMs in sets of proteins. Numerous masking options give the user great control over the contextual information to be included in the analyses, including evolutionary filtering and protein structural disorder. User-friendly output and visualizations of motif context allow the user to quickly gain insight into the validity of a putatively functional motif occurrence. Users can search motifs against the human proteome, or submit their own datasets of UniProt proteins, in which case motif support within the dataset is statistically assessed for over- and under-representation, accounting for evolutionary relationships between input proteins. SLiMSearch is freely available as open source Python modules and all webserver results are available for download. The SLiMSearch server is available at: http://bioware.ucd.ie/slimsearch.html
50-61
Springer
Davey, Norman E.
bdaded6d-ac23-4a43-b347-3113159dfb70
Haslam, Niall J.
4d7841cd-9f43-4c28-9643-60ab86e7061f
Shields, Denis C.
57ffee4f-0277-4b3d-9c7a-8c328637d8e6
Edwards, Richard J.
9d25e74f-dc0d-455a-832c-5f363d864c43
Dijkstra, Tjeerd M.H.
Tsivtsivadze, Evgeni
Marchiori, Elena
Heskes, Tom
Davey, Norman E.
bdaded6d-ac23-4a43-b347-3113159dfb70
Haslam, Niall J.
4d7841cd-9f43-4c28-9643-60ab86e7061f
Shields, Denis C.
57ffee4f-0277-4b3d-9c7a-8c328637d8e6
Edwards, Richard J.
9d25e74f-dc0d-455a-832c-5f363d864c43
Dijkstra, Tjeerd M.H.
Tsivtsivadze, Evgeni
Marchiori, Elena
Heskes, Tom

Davey, Norman E., Haslam, Niall J., Shields, Denis C. and Edwards, Richard J. (2010) SLiMSearch: a webserver for finding novel occurrences of short linear motifs in proteins, incorporating sequence context. Dijkstra, Tjeerd M.H., Tsivtsivadze, Evgeni, Marchiori, Elena and Heskes, Tom (eds.) In Pattern Recognition in Bioinformatics. vol. 6282, Springer. pp. 50-61 . (doi:10.1007/978-3-642-16001-1).

Record type: Conference or Workshop Item (Paper)

Abstract

Short, linear motifs (SLiMs) play a critical role in many biological processes. The SLiMSearch (Short, Linear Motif Search) webserver is a flexible tool that enables researchers to identify novel occurrences of predefined SLiMs in sets of proteins. Numerous masking options give the user great control over the contextual information to be included in the analyses, including evolutionary filtering and protein structural disorder. User-friendly output and visualizations of motif context allow the user to quickly gain insight into the validity of a putatively functional motif occurrence. Users can search motifs against the human proteome, or submit their own datasets of UniProt proteins, in which case motif support within the dataset is statistically assessed for over- and under-representation, accounting for evolutionary relationships between input proteins. SLiMSearch is freely available as open source Python modules and all webserver results are available for download. The SLiMSearch server is available at: http://bioware.ucd.ie/slimsearch.html

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More information

Published date: 2010
Venue - Dates: Second IAPR International Workshop (PRIB 2007), Singapore, Singapore, 2007-10-01 - 2007-10-02

Identifiers

Local EPrints ID: 166213
URI: http://eprints.soton.ac.uk/id/eprint/166213
PURE UUID: a57eaaf5-28e7-413c-89a2-ef7f417ce8e3

Catalogue record

Date deposited: 26 Oct 2010 08:00
Last modified: 14 Mar 2024 02:12

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Contributors

Author: Norman E. Davey
Author: Niall J. Haslam
Author: Denis C. Shields
Author: Richard J. Edwards
Editor: Tjeerd M.H. Dijkstra
Editor: Evgeni Tsivtsivadze
Editor: Elena Marchiori
Editor: Tom Heskes

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