Real-World Applications of Evolutionary Computing, EvoWorkshops 2000: EvoIASP, EvoSCONDI, EvoTel, EvoSTIM, EvoROB, and EvoFlight
Spatio-Temporal Registration of the Expression Patterns of Drosophila Segmentation Genes
Proceedings of the Seventh International Conference on Intelligent Systems for Molecular Biology
Real-Time Imaging - Special issue: Imaging in bioinformatics part II
Evolutionary techniques for image processing a large dataset of early Drosophila gene expression
EURASIP Journal on Applied Signal Processing
Experimental determination of intrinsic drosophila embryo coordinates by evolutionary computation
PRIB'13 Proceedings of the 8th IAPR international conference on Pattern Recognition in Bioinformatics
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It is well known, that organism of animal, consisting of many billions cells, is formed by consequent divisions of the only cell - zygote. In so doing, embryo cells are permanently communicating by means of biochemical signals. As a result, proper genes were being activated at proper time in proper cells of the embryo.Modern confocal microscopes being equipped by lasers and computers give possibility to trace-through the cell fate of early embryo for such a classical model object, as fruit fly Drosophila melanogaster. By this approach, it is possible to retrace the detailed dynamics of activity of genes-controllers of development with the resolution on the level of individual nuclei for each of 4-6 thousand cells, composing early fly embryo. The final result of this analysis will be the quantitative atlas of Drosophila genes action (expression): http://www.iephb.nw.ru/spirov/atlas. To achieve this aim we need to receive statistically authentic summary picture of detailed pattern dynamics proceeding from a large number of scanned embryos. This presupposes the elaboration of the methods of preprocessing, elastic deformation, registration and interpolation of the confocal-microscopy images of embryos.For this purpose we apply modern heuristic methods of optimization to the processing of our images. Namely classic GA approach is used for finding a suitable elastic deformation, for registering the images and for finding a Fourier interpolation of concentration (gene-expression) surfaces. All GA programs considered are the developments of "evolution strategies program" from EO-0.8.5 C++ library (Merelo).