Linked Life Data

16388092

Source:http://linkedlifedata.com/resource/pubmed/id/16388092

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2
pubmed:dateCreated
2006-1-2
pubmed:abstractText
The rapid growth of different kinds of biological information allows a good opportunity to analyze the co-evolutionary characteristics in endocrine regulatory pathways. Data ranging from kinds of species' genome, gene sequence, protein structure, and expression profile of different organisms can reveal the inner co-evolutionary relationship of ligands, receptors, and other related molecules. In return, these co-evolutionary characteristics can help us determine uncharacterized ligands and receptors, annotate gene functions, highlight amino acid residues with biochemical significance, and identify regulated genes in the endocrine process. Encouraging examples in this field, although at their starting stage, have emerged. Here we focus on recent progress in endocrine-related co-evolution research from a methodological approach.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Nov
pubmed:issn
1355-008X
pubmed:author
pubmed:issnType
Print
pubmed:volume
28
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
187-92
pubmed:dateRevised
2010-6-24
pubmed:meshHeading
pubmed:year
2005
pubmed:articleTitle
Co-evolution analysis on endocrine research: a methodological approach.
pubmed:affiliation
State Key Laboratory of Genetic Engineering, Institute of Genetics, School of Life Sciences, Fudan University, Shanghai 200433, People's Republic of China.
pubmed:publicationType
Journal Article, Review