Nowadays, given the new microarray technology, a huge amount of data on gene expression is available. In order to understand the genetic expression process more completely, we need to know the control structure of the genetic expression. We present a new scheme for a genetic algorithm that shows promising results when modelling boolean networks. We can effectively and quickly obtain good approximations of the underlying control structures, given very little information on the possible trajectories.
http://www.lbd.dcc.ufmg.br:8080/colecoes/wob/2002/014.pdf
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