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We analyze available DNA microarray time series that monitor gene expression along the developmental stages of
multicellular eukaryotes or in unicellular organisms subject to external perturbations. Using a translation- and scale-
invariant distance measure corresponding to least-rectangle regression to compare the gene expression profiles, we show that
peaks in the average distance values are noticeable and are localized around specific time points. These points systematically
coincide with the transition points between developmental phases or just follow perturbations. This approach can thus be used
to identify automatically, from microarray time series alone, the presence of external perturbations or the transition between
developmental stages in arbitrary cell systems. Moreover, our results show the existence of a striking similarity between the
gene expression responses to these
very different phenomena. Based on these findings, we set up an adapted clustering
method that uses the abovementioned distance measure and classifies the genes on the basis of their expression profiles within
each developmental stage or between perturbation phases. This method was applied to the development of
profiles representing each cluster were computed and their time evolution was analyzed using coupled linear and non-linear
differential equations. Different model structures and parameter identification and reduction schemes were tested. The models
so obtained were compared on the basis of their abilities to reproduce the data, to keep realistic gene expression levels when
extrapolated in time, to show the biologically expected robustness with respect to parameter variations, and to contain as few
parameters as possible. A family of non-linear models, constructed from the exponential of linear combinations of expression
levels, reached all the objectives. It defined networks with a mean number of connections equal to two, when restricted to the
embryonic time series, and equal to five for the full time series.
Marianne Rooman has completed her Ph.D in theoretical physics in 1984 and defended a thesis in structural bioinformatics in 1996 at the Universit?
Libre de Bruxelles (Belgium). She is Research Director at the Belgian Fund for Scientific Research. She has published more than 80 papers in
reputed journals in theoretical physics, structural bioinformatics and, more recently, in systems biology.
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