Linked Life Data

9769220

Source:http://linkedlifedata.com/resource/pubmed/id/9769220

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2
pubmed:dateCreated
1998-11-25
pubmed:abstractText
A new method is suggested here for topology prediction of helical transmembrane proteins. The method is based on the hypothesis that the localizations of the transmembrane segments and the topology are determined by the difference in the amino acid distributions in various structural parts of these proteins rather than by specific amino acid compositions of these parts. A hidden Markov model with special architecture was developed to search transmembrane topology corresponding to the maximum likelihood among all the possible topologies of a given protein. The prediction accuracy was tested on 158 proteins and was found to be higher than that found using prediction methods already available. The method successfully predicted all the transmembrane segments in 143 proteins out of the 158, and for 135 of these proteins both the membrane spanning regions and the topologies were predicted correctly. The observed level of accuracy is a strong argument in favor of our hypothesis.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Oct
pubmed:issn
0022-2836
pubmed:author
pubmed:copyrightInfo
Copyright 1998 Academic Press.
pubmed:issnType
Print
pubmed:day
23
pubmed:volume
283
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
489-506
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
1998
pubmed:articleTitle
Principles governing amino acid composition of integral membrane proteins: application to topology prediction.
pubmed:affiliation
Institute of Enzymology. Biological Research Center, Hungarian Academy of Sciences, H-1518 Budapest, Hungary.
pubmed:publicationType
Journal Article, Comparative Study, Research Support, Non-U.S. Gov't