TY - JOUR AU - Armañanzas, Rubén AU - Inza, Iñaki AU - Santana, Roberto AU - Saeys, Yvan AU - Flores, Jose Luis AU - Lozano, Jose Antonio AU - Peer, Yves Van de AU - Blanco, Rosa AU - Robles, Víctor AU - Bielza, Concha AU - Larrañaga, Pedro PY - 2008 DA - 2008/09/11 TI - A review of estimation of distribution algorithms in bioinformatics JO - BioData Mining SP - 6 VL - 1 IS - 1 AB - Evolutionary search algorithms have become an essential asset in the algorithmic toolbox for solving high-dimensional optimization problems in across a broad range of bioinformatics problems. Genetic algorithms, the most well-known and representative evolutionary search technique, have been the subject of the major part of such applications. Estimation of distribution algorithms (EDAs) offer a novel evolutionary paradigm that constitutes a natural and attractive alternative to genetic algorithms. They make use of a probabilistic model, learnt from the promising solutions, to guide the search process. In this paper, we set out a basic taxonomy of EDA techniques, underlining the nature and complexity of the probabilistic model of each EDA variant. We review a set of innovative works that make use of EDA techniques to solve challenging bioinformatics problems, emphasizing the EDA paradigm's potential for further research in this domain. SN - 1756-0381 UR - https://doi.org/10.1186/1756-0381-1-6 DO - 10.1186/1756-0381-1-6 ID - Armañanzas2008 ER -