Linked Life Data

11867088

Source:http://linkedlifedata.com/resource/pubmed/id/11867088

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
2002-2-27
pubmed:abstractText
In order to reconstruct the establishment of the body pattern over time in Drosophila embryos, we have developed automated methods for detecting the age of an embryo on the basis of knowledge about its gene expression patterns. In this paper we perform temporal classification of confocal images of expression patterns of genes controlling segmentation by means of a neural network based on multi-valued neurons (MVN). MVN are artificial neural processing elements with complex-valued weights and high functionality, which proved to be efficient for solving the image recognition problems. The results obtained by this method confirm its efficiency for image recognition and indicate that the method can detect characteristic features of expression patterns which mark their development over time.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Mar
pubmed:issn
0025-5564
pubmed:author
pubmed:issnType
Print
pubmed:volume
176
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
145-59
pubmed:dateRevised
2009-11-11
pubmed:meshHeading
pubmed:year
2002
pubmed:articleTitle
Temporal classification of Drosophila segmentation gene expression patterns by the multi-valued neural recognition method.
pubmed:affiliation
Neural Networks Technologies (NNT) Ltd., Ramat-Gan, Israel. igora@netvision.net.il
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S., Research Support, Non-U.S. Gov't