Linked Life Data

17520486

Source:http://linkedlifedata.com/resource/pubmed/id/17520486

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4
pubmed:dateCreated
2007-5-23
pubmed:abstractText
A novel alignment-free method for computing functional similarity of membrane proteins based on features of hydropathy distribution is presented. The features of hydropathy distribution are used to represent protein families as hydropathy profiles. The profiles statistically summarize the hydropathy distribution of member proteins. The summation is made by using hydropathy features that numerically represent structurally/functionally significant portions of protein sequences. The hydropathy profiles are numerical vectors that are points in a high dimensional 'hydropathy' space. Their similarities are identified by projection of the space onto principal axes. Here, the approach is applied to the secondary transporters. The analysis using the presented approach is validated by the standard classification of the secondary transporters. The presented analysis allows for prediction of function attributes for proteins of uncharacterized families of secondary transporters. The results obtained using the presented analysis may help to characterize unknown function attributes of secondary transporters. They also show that analysis of hydropathy distribution can be used for function prediction of membrane proteins.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:issn
0968-7688
pubmed:author
pubmed:issnType
Print
pubmed:volume
24
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
304-12
pubmed:dateRevised
2010-11-18
pubmed:meshHeading
pubmed:articleTitle
Using hydropathy features for function prediction of membrane proteins.
pubmed:affiliation
Institute of Microbiology, Academy of Sciences of the Czech Republic, Vídenská, Czech Republic. panek@biomed.cas.cz
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't