Linked Life Data

21443196

Source:http://linkedlifedata.com/resource/pubmed/id/21443196

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
8
pubmed:dateCreated
2011-4-21
pubmed:abstractText
The systematic extraction of structure-activity relationship (SAR) information from large and diverse compound data sets depends on the application of computational analysis methods. Irrespective of the methodological details, the ultimate goal of large-scale SAR analysis is to identify most informative compounds and rationalize structural changes that determine SAR behavior. Such insights provide a basis for further chemical exploration. Herein we introduce the first graphical SAR analysis method that globally organizes large compound data sets on the basis of local structural relationships, hence providing an immediate access to important structural modifications and SAR determinants.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Apr
pubmed:issn
1520-4804
pubmed:author
pubmed:issnType
Electronic
pubmed:day
28
pubmed:volume
54
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
2944-51
pubmed:meshHeading
pubmed:year
2011
pubmed:articleTitle
Local structural changes, global data views: graphical substructure-activity relationship trailing.
pubmed:affiliation
Department of Life Science Informatics, Rheinische Friedrich-Wilhelms-Universita?t, Bonn, Germany.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't