Open Access

Evolutionary Techniques for Image Processing a Large Dataset of Early Drosophila Gene Expression

EURASIP Journal on Advances in Signal Processing20032003:975423

DOI: 10.1155/S1110865703302069

Received: 10 July 2002

Published: 21 July 2003


Understanding how genetic networks act in embryonic development requires a detailed and statistically significant dataset integrating diverse observational results. The fruit fly (Drosophila melanogaster) is used as a model organism for studying developmental genetics. In recent years, several laboratories have systematically gathered confocal microscopy images of patterns of activity (expression) for genes governing early Drosophila development. Due to both the high variability between fruit fly embryos and diverse sources of observational errors, some new nontrivial procedures for processing and integrating the raw observations are required. Here we describe processing techniques based on genetic algorithms and discuss their efficacy in decreasing observational errors and illuminating the natural variability in gene expression patterns. The specific developmental problem studied is anteroposterior specification of the body plan.


image processing elastic deformations genetic algorithms observational errors variability fluctuations

Authors’ Affiliations

Department of Applied Mathematics and Statistics and The Center for Developmental Genetics, Stony Brook University
The Sechenov Institute of Evolutionary Physiology and Biochemistry, Russian Academy of Sciences
Mathematics Department, British Columbia Institute of Technology
Chemistry Department, University of British Columbia


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