Linked Life Data

18698839

Source:http://linkedlifedata.com/resource/pubmed/id/18698839

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
9
pubmed:dateCreated
2008-9-22
pubmed:abstractText
Fingerprints are molecular bit string representations and are among the most popular descriptors for similarity searching. In key-type fingerprints, each bit position monitors the presence or absence of a prespecified chemical or structural feature. In contrast to hashed fingerprints, this keyed design makes it possible to evaluate individual bit positions and the associated structural features during similarity searching. Bit silencing is introduced as a systematic approach to assess the contribution of each bit in a fingerprint to similarity search performance. From the resulting bit contribution profile, a bit position-dependent weight vector is derived that determines the relative weight of each bit on the basis of its individual contribution. By merging this weight vector with the Tanimoto coefficient, compound class-directed similarity metrics are obtained that further increase fingerprint search calculations compared to conventional calculations of Tanimoto similarity.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Sep
pubmed:issn
1549-9596
pubmed:author
pubmed:issnType
Print
pubmed:volume
48
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1754-9
pubmed:meshHeading
pubmed:year
2008
pubmed:articleTitle
Bit silencing in fingerprints enables the derivation of compound class-directed similarity metrics.
pubmed:affiliation
Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology & Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Dahlmannstrasse 2, D-53113 Bonn, Germany.
pubmed:publicationType
Journal Article