SLiMDisc (Short Linear Motif Discovery) is a python-based method to find shared motifs in proteins with little or no primary sequence similarity from a group of proteins with a common attribute - be it biological function, subcellular location or a common interaction partner. The method builds on the basic pattern discovery abilities of the TEIRESIAS algorithm, applying a number of filters to the returned motifs to upweight those present in evolutionarily distant sequences and downweight those primarily arising due to common evolutionary descent. A key feature of this method is that it requires no pre-filtering of the dataset for evolutionarily conserved sequences and does not suffer from the potential loss of information (and SLiMs) incurred by arbitrarily retaining a single representative of any given group of homologous proteins. Furthermore, a number of filtering options are provided, giving the user a great deal of control over the type of motif returned.
Manual
Download
SLiMDisc
Install
pdf
doc
Version 1.6
zip
html
pdf
Datasets
ELM datasets
HPRD Interaction datasets
LPxTG bacterial anchor
Extracellular matrix
Hematopeoitic Activity
Integrin Binding
Ó
2006 Norman Davey. All Rights Reserved.