Source:http://linkedlifedata.com/resource/pubmed/id/16995724
Switch to
| Predicate | Object |
|---|---|
| rdf:type | |
| lifeskim:mentions | |
| pubmed:issue |
5
|
| pubmed:dateCreated |
2006-9-25
|
| pubmed:abstractText |
A novel method termed MolBlaster is introduced for the evaluation of molecular similarity relationships on the basis of randomly generated fragment populations. Our motivation has been to develop a similarity method that does not depend on the use of predefined structural or property descriptors. Fragment profiles of molecules are generated by random deletion of bonds in connectivity tables and quantitatively compared using entropy-based metrics. In test calculations, MolBlaster accurately reproduced a structural key-based similarity ranking of druglike molecules.
|
| pubmed:language |
eng
|
| pubmed:journal | |
| pubmed:citationSubset |
IM
|
| pubmed:status |
MEDLINE
|
| pubmed:issn |
1549-9596
|
| pubmed:author | |
| pubmed:issnType |
Print
|
| pubmed:volume |
46
|
| pubmed:owner |
NLM
|
| pubmed:authorsComplete |
Y
|
| pubmed:pagination |
1937-44
|
| pubmed:meshHeading | |
| pubmed:articleTitle |
Assessment of molecular similarity from the analysis of randomly generated structural fragment populations.
|
| pubmed:affiliation |
Department of Life Science Informatics, B-IT, Rheinische Friedrich-Wilhelms-Universität, Dahlmannstrasse 2, D-53113 Bonn, Germany.
|
| pubmed:publicationType |
Journal Article
|