Linked Life Data

15700414

Source:http://linkedlifedata.com/resource/pubmed/id/15700414

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
5
pubmed:dateCreated
2005-2-9
pubmed:abstractText
Pooled Genomic Indexing (PGI) is a novel method for physical mapping of clones onto known sequences. PGI is carried out by pooling arrayed clones and generating shotgun sequence reads from the pools. The shotgun sequences are compared to a reference sequence. In the simplest case, clones are placed on an array and are pooled by rows and columns. If a shotgun sequence from a row pool and another shotgun sequence from a column pool match the reference sequence at a close distance, they are both assigned to the clone at the intersection of the two pools. Accordingly, the clone is mapped onto the region of the reference sequence between the two matches. A probabilistic model for PGI is developed, and several pooling designs are described and analyzed, including transversal designs and designs from linear codes. The probabilistic model and the pooling schemes are validated in simulated experiments where 625 rat bacterial artificial chromosome (BAC) clones and 207 mouse BAC clones are mapped onto homologous human sequence.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:issn
1066-5277
pubmed:author
pubmed:issnType
Print
pubmed:volume
11
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1001-21
pubmed:dateRevised
2007-11-14
pubmed:meshHeading
pubmed:year
2004
pubmed:articleTitle
Pooled Genomic Indexing (PGI): analysis and design of experiments.
pubmed:affiliation
Département d'informatique et de recherche opérationnelle, Université de Montréal, CP 6128 succ. Centre-Ville, Montréal, QC H3C 3J7, Canada. csuros@iro.umontreal.ca
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S., Research Support, Non-U.S. Gov't