16595078

Source:http://linkedlifedata.com/resource/pubmed/id/16595078

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Predicate	Object
rdf:type	pubmed:Citation
lifeskim:mentions	umls-concept:C0025663, umls-concept:C0038951, umls-concept:C1328866, umls-concept:C1517888
pubmed:issue	5
pubmed:dateCreated	2006-4-5
pubmed:abstractText	Data mining methods are gaining more interest as potential tools in mapping and identification of complex disease loci. The methods are well suited to large numbers of genetic marker loci produced by high-throughput laboratory analyses, but also might be useful for clarifying the phenotype definitions prior to more traditional mapping analyses. Here, the current data mining-based methods for linkage disequilibrium mapping and phenotype analyses are reviewed.
pubmed:language	eng
pubmed:journal	http://linkedlifedata.com/resource/pubmed/journal/101202210
pubmed:citationSubset	IM
pubmed:status	MEDLINE
pubmed:month	Mar
pubmed:issn	1479-7364
pubmed:author	pubmed-author:OnkamoPäiviP, pubmed-author:ToivonenHannuH
pubmed:issnType	Electronic
pubmed:volume	2
pubmed:owner	NLM
pubmed:authorsComplete	Y
pubmed:pagination	336-40
pubmed:dateRevised	2007-2-14
pubmed:meshHeading	pubmed-meshheading:16595078-Chromosome Mapping, pubmed-meshheading:16595078-Gene Frequency, pubmed-meshheading:16595078-Humans, pubmed-meshheading:16595078-Linkage Disequilibrium, pubmed-meshheading:16595078-Software
pubmed:year	2006
pubmed:articleTitle	A survey of data mining methods for linkage disequilibrium mapping.
pubmed:affiliation	Department of Biological and Environmental Sciences, FI-00014, University of Helsinki, Finland. paivi.onkamo@helsinki.fi
pubmed:publicationType	Journal Article, Review