Affiliations:
Institute for High Performance Computing and Data
Bases 120, Fontanka emb., office 7, St. Petersburg, 198005 Russia
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Department of Applied Mathematics & Statistics and
The Center for Developmental Genetics, State University of New York at Stony
Brook, NY 11794-3600 Stony Brook, USA E-mail:
[email protected]
Abstract:
We apply the fast redundant dyadic wavelet transform to the spatial
registration of two-dimensional gene expression patterns of 736 Drosophila
melanogaster embryos. This method is superior to the Fourier transform or
windowed Fourier transform because of its ability to reduce noise and is of
high resolution. In registration of the dataset we use two cost functions based
on computing the Euclidean or Mahalanobis distance. The algorithm shows a high
level of accuracy. For early temporal classes the cost function based on
Mahalanobis distance gives better results. We have reported a method for
construction of an integrated dataset elsewhere. In this paper the method is
extended to the two-dimensional case. The procedure for data assembly provides
for the preservation of some aspects of the nuclear structure of a
two-dimensional gene expression pattern. It is based on creating an averaged
model that reproduces the spatial distribution of nuclei over the embryo image.
The average concentrations of each protein in each averaged nucleus are
computed from the series of embryos of the same age.
