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Temporal classification of Drosophila segmentation gene expression patterns by the multi-valued neural
 

Summary: Temporal classification of Drosophila segmentation gene
expression patterns by the multi-valued neural
recognition method
Igor Aizenberg a
, Ekaterina Myasnikova b,*, Maria Samsonova b
, John Reinitz c
a
Neural Networks Technologies (NNT) Ltd., 155 Bialik st., Ramat-Gan 52523, Israel
b
Institute of High Performance Computing and Data Bases, 118 Fontanka emb., St. Petersburg 198005, Russia
c
Department of Applied Mathematics and Statistics, The University at Stony Brook, Stony Brook, NY 11794-3600, USA
Received 17 May 2001; received in revised form 29 June 2001; accepted 20 November 2001
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

  

Source: Aizenberg, Igor - College of Science, Technology, Engineering, and Mathematics, Texas A&M University at Texarkana

 

Collections: Computer Technologies and Information Sciences