title: Temporal classification of Drosophila segmentation gene expression patterns by the multi-valued neural recognition method.
abstract: 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.
authors.affiliation: Neural Networks Technologies (NNT) Ltd., Ramat-Gan, Israel. igora@netvision.net.il
authors.forename: Igor
authors.initials: I
authors.lastname: Aizenberg
authors.forename: Ekaterina
authors.initials: E
authors.lastname: Myasnikova
authors.forename: Maria
authors.initials: M
authors.lastname: Samsonova
authors.forename: John
authors.initials: J
authors.lastname: Reinitz
mesh_terms: D000818:Animals; D004330:Drosophila / Q000196:embryology* / Q000235:genetics*; D018507:Gene Expression Regulation, Developmental / Q000502:physiology*; D018613:Microscopy, Confocal; D016571:Neural Networks, Computer; D010363:Pattern Recognition, Automated; D013997:Time Factors