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We apply constraints and global optimization to the problem of restricting overlapping of gene predictions for prokaryotic genomes. We investigate existing heuristic methods and show how they may be expressed using Constraint Handling Rules. Furthermore, we integrate existing methods in a global optimization procedure expressed as probabilistic model in the PRISM language. This approach yields an optimal (highest scoring) subset of predictions that satisfy the constraints. Experimental results indicate accuracy comparable to the heuristic approaches.