Linked Life Data

14551445

Source:http://linkedlifedata.com/resource/pubmed/id/14551445

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
Pt 6
pubmed:dateCreated
2003-10-10
pubmed:abstractText
High-throughput protein crystallography requires the automation of multiple steps used in the protein structure determination. One crucial step is to find and monitor the crystal quality on the basis of its diffraction pattern. It is often time-consuming to scan protein crystals when selecting a good candidate for exposure. The use of neural networks for this purpose is explored. A dynamic neural network algorithm to achieve a fast convergence and high-speed image recognition has been developed. On the test set a 96% success rate in identifying properly the quality of the crystal has been achieved.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Nov
pubmed:issn
0909-0495
pubmed:author
pubmed:issnType
Print
pubmed:day
1
pubmed:volume
10
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
445-9
pubmed:dateRevised
2007-11-14
pubmed:meshHeading
pubmed:year
2003
pubmed:articleTitle
Application of a neural network in high-throughput protein crystallography.
pubmed:affiliation
Brookhaven National Laboratory, Upton, NY 11973, USA.
pubmed:publicationType
Journal Article, Comparative Study, Research Support, U.S. Gov't, P.H.S., Research Support, U.S. Gov't, Non-P.H.S., Evaluation Studies, Validation Studies