Linked Life Data

11055370

Source:http://linkedlifedata.com/resource/pubmed/id/11055370

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:dateCreated
2001-1-11
pubmed:abstractText
Complex segregation analysis and linkage methods are mathematical techniques for the genetic dissection of complex diseases. They are used to delineate complex modes of familial transmission and to localize putative disease susceptibility loci to specific chromosomal locations. The computational problem of Bayesian linkage and segregation analysis is one of integration in high-dimensional spaces. In this paper, three available techniques for Bayesian linkage and segregation analysis are discussed: Markov Chain Monte Carlo (MCMC), importance sampling, and exact calculation. The contribution of each to the overall integration will be explicitly discussed.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:issn
0741-0395
pubmed:author
pubmed:issnType
Print
pubmed:volume
19 Suppl 1
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
S50-6
pubmed:dateRevised
2010-11-18
pubmed:meshHeading
pubmed:year
2000
pubmed:articleTitle
Bayesian linkage and segregation analysis: factoring the problem.
pubmed:affiliation
Psychology Research Laboratory, Mailman Research Center, McLean Hospital, Belmont, Massachusetts 02478, USA. steven_matthysse@harvard.edu
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S.