Linked Life Data

16275084

Source:http://linkedlifedata.com/resource/pubmed/id/16275084

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2
pubmed:dateCreated
2005-11-25
pubmed:abstractText
In the present report, the use of the atom-based linear indices for finding functions that discriminate between the tyrosinase inhibitor compounds and inactive ones is presented. In this sense, discriminant models were applied and globally good classifications of 93.51% and 92.46% were observed for non-stochastic and stochastic linear indices best models, respectively, in the training set. The external prediction sets had accuracies of 91.67% and 89.44%. In addition, these fitted models were used in the screening of new cycloartane compounds isolated from herbal plants. A good behavior is shown between the theoretical and experimental results. These results provide a tool that can be used in the identification of new tyrosinase inhibitor compounds.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Jan
pubmed:issn
0960-894X
pubmed:author
pubmed:issnType
Print
pubmed:day
15
pubmed:volume
16
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
324-30
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
2006
pubmed:articleTitle
New tyrosinase inhibitors selected by atomic linear indices-based classification models.
pubmed:affiliation
Department of Pharmacy, Faculty of Chemistry-Pharmacy, Central University of Las Villas, Santa Clara, 54830 Villa Clara, Cuba.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't