Linked Life Data

17646296

Source:http://linkedlifedata.com/resource/pubmed/id/17646296

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
13
pubmed:dateCreated
2007-7-24
pubmed:abstractText
Accurate prediction of RNA secondary structure from the base sequence is an unsolved computational challenge. The accuracy of predictions made by free energy minimization is limited by the quality of the energy parameters in the underlying free energy model. The most widely used model, the Turner99 model, has hundreds of parameters, and so a robust parameter estimation scheme should efficiently handle large data sets with thousands of structures. Moreover, the estimation scheme should also be trained using available experimental free energy data in addition to structural data.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Jul
pubmed:issn
1367-4811
pubmed:author
pubmed:issnType
Electronic
pubmed:day
1
pubmed:volume
23
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
i19-28
pubmed:dateRevised
2009-11-4
pubmed:meshHeading
pubmed:year
2007
pubmed:articleTitle
Efficient parameter estimation for RNA secondary structure prediction.
pubmed:affiliation
Department of Computer Science, University of British Columbia, Vancouver BC V6T 1Z4, Canada. andrones@cs.ubc.ca
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't, Research Support, N.I.H., Extramural