Linked Life Data

10585497

Source:http://linkedlifedata.com/resource/pubmed/id/10585497

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
11
pubmed:dateCreated
2000-1-18
pubmed:abstractText
Analysis of residue correlation in over 2700 mouse heavy chains of the V(H) domains was carried out on three hierarchical levels. At the 'position' level, statistical analysis revealed 45 positions that conserve similar residues in almost all chains. At the 'fragment' level, the focus of investigation shifted to the study of combinations of amino acids in strands and loops. It was found that no more than 10 patterns were sufficient for describing strands and loops in the chains. At the 'sequence' level, we determined all possible combinations of these patterns and classified the mouse heavy chains. Comparison of the sequences in the eight classes revealed residues at the class-determining positions that were unique to each class. Because a strong correlation of residues was found, one only needs several residues to classify a sequence. It follows that no all residue alignment procedure is necessary to divide sequences into classes. An important corollary of our approach is the possibility of predicting residues in an incomplete sequence from a small sequence fragment. On the basis of our analysis of mouse heavy chains we hypothesize about the presently unknown mouse V(H) germline repertoire.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Nov
pubmed:issn
0269-2139
pubmed:author
pubmed:issnType
Print
pubmed:volume
12
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
919-25
pubmed:dateRevised
2010-2-23
pubmed:meshHeading
pubmed:year
1999
pubmed:articleTitle
Class-defining characteristics in the mouse heavy chains of variable domains.
pubmed:affiliation
Department of Mathematics, Rutgers University, Piscataway, NJ 08854, USA.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't