Linked Life Data

21682902

Source:http://linkedlifedata.com/resource/pubmed/id/21682902

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:dateCreated
2011-7-21
pubmed:abstractText
Intrinsically disordered proteins play important roles in various cellular activities and their prevalence was implicated in a number of human diseases. The knowledge of the content of the intrinsic disorder in proteins is useful for a variety of studies including estimation of the abundance of disorder in protein families, classes, and complete proteomes, and for the analysis of disorder-related protein functions. The above investigations currently utilize the disorder content derived from the per-residue disorder predictions. We show that these predictions may over-or under-predict the overall amount of disorder, which motivates development of novel tools for direct and accurate sequence-based prediction of the disorder content.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:issn
1471-2105
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
12
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
245
pubmed:dateRevised
2011-11-14
pubmed:meshHeading
pubmed:year
2011
pubmed:articleTitle
In-silico prediction of disorder content using hybrid sequence representation.
pubmed:affiliation
Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta T6G 2V4, Canada.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't, Research Support, N.I.H., Extramural