Linked Life Data

11818457

Source:http://linkedlifedata.com/resource/pubmed/id/11818457

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2
pubmed:dateCreated
2002-1-30
pubmed:abstractText
Recent technological advances in biomedical research, such as genome sequences and DNA microarrays, have dramatically increased the size of relevant databases. A major challenge is the extraction of a limited number of parameters from these databases that can differentiate and diagnose complex biological states. In a model of cardiac transplantation investigating immunosuppression by inhibition of CD40 ligand costimulation, we have applied a combination of cluster algorithms and self-organizing maps to analyze a panel of 60 candidate genes. Dendrograms generated by cluster analysis distinguished different molecular bases of rejection. Using self-organizing maps, we identified nine genes (CD4, CCR3, CCR5, LT beta, MIP-1 alpha, MIP-2, CD8 alpha, IP-10, and RANTES), each with a unique profile of transcriptional expression, that reproduce the differentiation of states of rejection in dendrograms. Using histology and immunohistochemistry, we correlated differential regulation of CD4 and CD8 at the levels of mRNA and protein. Our strategy of data reduction successfully decreased the number of genes to nine, which are sufficient to differentiate distinct states of rejection in our experimental protocol.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Feb
pubmed:issn
0741-5400
pubmed:author
pubmed:issnType
Print
pubmed:volume
71
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
348-58
pubmed:dateRevised
2007-11-14
pubmed:meshHeading
pubmed:year
2002
pubmed:articleTitle
Molecular profiles of allograft rejection following inhibition of CD40 ligand costimulation differentiated by cluster analysis.
pubmed:affiliation
Laboratory of Molecular Immunology, Department of Medicine, Brigham & Women's Hospital, Harvard Medical School, Boston, Massachusetts 02115, USA.
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S., Research Support, Non-U.S. Gov't