Literature DB >> 11867088

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

Igor Aizenberg1, Ekaterina Myasnikova, Maria Samsonova, John Reinitz.   

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.

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Year:  2002        PMID: 11867088     DOI: 10.1016/s0025-5564(01)00104-3

Source DB:  PubMed          Journal:  Math Biosci        ISSN: 0025-5564            Impact factor:   2.144


  1 in total

1.  Dynamical analysis of regulatory interactions in the gap gene system of Drosophila melanogaster.

Authors:  Johannes Jaeger; Maxim Blagov; David Kosman; Konstantin N Kozlov; Ekaterina Myasnikova; Svetlana Surkova; Carlos E Vanario-Alonso; Maria Samsonova; David H Sharp; John Reinitz
Journal:  Genetics       Date:  2004-08       Impact factor: 4.562

  1 in total

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