Linked Life Data

8744568

Source:http://linkedlifedata.com/resource/pubmed/id/8744568

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
1996-12-4
pubmed:abstractText
Ab initio quantum chemical calculations of molecular properties such as, e.g., torsional potential energies, require massive computational effort even for moderately sized molecules, if basis sets with a reasonable quality are employed. Using ab initio data on conformational properties of the cofactor (6R,1'R,2'S)-5,6,7,8-tetrahydrobiopterin, we demonstrate that error backpropagation networks can be established that efficiently approximate complicated functional relationships such as torsional potential energy surfaces of a flexible molecule. Our pilot simulations suggest that properly trained neural networks might provide an extremely compact storage medium for quantum chemically obtained information. Moreover, they are outstandingly comfortable tools when it comes to making use of the stored information. One possible application is demonstrated, namely, computation of relaxed torsional energy surfaces.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Feb
pubmed:issn
0263-7855
pubmed:author
pubmed:issnType
Print
pubmed:volume
14
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
12-8
pubmed:dateRevised
2000-12-18
pubmed:meshHeading
pubmed:year
1996
pubmed:articleTitle
Neural networks as a tool for compact representation of ab initio molecular potential energy surfaces.
pubmed:affiliation
Medizinisch-Chemisches Institut, Karl-Franzens-Universität Graz, Austria.
pubmed:publicationType
Journal Article