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Exploiting publicly available biological and biochemical information for the discovery of novel short linear motifs
- Source :
- PLoS ONE, Vol 6, Iss 7, p e22270 (2011), PLoS ONE
- Publication Year :
- 2011
- Publisher :
- Public Library of Science (PLoS), 2011.
-
Abstract
- The function of proteins is often mediated by short linear segments of their amino acid sequence, called Short Linear Motifs or SLiMs, the identification of which can provide important information about a protein function. However, the short length of the motifs and their variable degree of conservation makes their identification hard since it is difficult to correctly estimate the statistical significance of their occurrence. Consequently, only a small fraction of them have been discovered so far. We describe here an approach for the discovery of SLiMs based on their occurrence in evolutionarily unrelated proteins belonging to the same biological, signalling or metabolic pathway and give specific examples of its effectiveness in both rediscovering known motifs and in discovering novel ones. An automatic implementation of the procedure, available for download, allows significant motifs to be identified, automatically annotated with functional, evolutionary and structural information and organized in a database that can be inspected and queried. An instance of the database populated with pre-computed data on seven organisms is accessible through a publicly available server and we believe it constitutes by itself a useful resource for the life sciences (http://www.biocomputing.it/modipath).
- Subjects :
- Amino Acid Motifs
lcsh:Medicine
Biological Data Management
Computational biology
Biology
Short length
Conserved sequence
Evolution, Molecular
Metabolic Networks
Mice
User-Computer Interface
Animals
Data Mining
Humans
Short linear motif
Databases, Protein
lcsh:Science
Conserved Sequence
Genetics
Internet
Bioinformatics (Computational Biology)
Multidisciplinary
lcsh:R
Computational Biology
Proteins
A protein
Molecular Sequence Annotation
Signaling Networks
Rats
Variable (computer science)
ComputingMethodologies_PATTERNRECOGNITION
Bioinformatik (beräkningsbiologi)
Identification (biology)
lcsh:Q
Function (biology)
Research Article
Subjects
Details
- Language :
- English
- ISSN :
- 19326203
- Volume :
- 6
- Issue :
- 7
- Database :
- OpenAIRE
- Journal :
- PLoS ONE
- Accession number :
- edsair.doi.dedup.....3c484e9f1b0182c37f4efcd62ff72c66