Identifying valid solutions for the inference of regulatory networks

In this paper, we address the problem of finding gene regulatory networks from experimental DNA microarray data. The problem often is multi-modal and therefore appropriate optimization strategies become necessary. We propose to use a clustering based niching evolutionary algorithm to maintain diversity in the optimization population to prevent premature convergence and to raise the probability of finding the global optimum by identifying multiple alternative networks than standard algorithms. With this set of alternatives, the identification of the true solution has then to be addressed in a second post-processing step.