Gene Selection of DNA Microarrays

Optimal gene selection in DNA Microarrays is a complex problem proved to be NP-hard. Therefore, we need efficient automated approaches to tackle it. Metaheuristics algorithms have proved to be adequate tools for this matter, since they are capable of solving the feature selection accurately and efficiently for the large dimensions needed in Biology.

References and Supporting Material

• J. García-Nieto, E. Alba Parallel Multi-Swarm Optimizer for Gene Selection in DNA Microarray.Applied Intelligence, 37(2):255-266, 2012 DOI: http://dx.doi.org/10.1007/s10489-011-0325-9
• J. García-Nieto, E. Alba, L. Jourdan, E-G. Talbi. Sensitivity and Specifity Based Multiobjective Approach for Feature Selection: Application to Cancer Diagnosis. Information Processing Letters, 109(16):887-896. 31 July 2009, DOI: http://dx.doi.org/10.1016/j.ipl.2009.03.029
• J. García-Nieto, E. Alba. Swarm Intelligence Approach for Accurate Gene Selection in DNA Microarrays ERCIM-NEW Special Theme: Computational Biology. 82, pp. 26-28, 2010

• José García-Nieto, Enrique Alba, and Javier Apolloni. Hybrid DE-SVM Approach for Feature Selection: Application to Gene Expression Datasets. In Proceedings of the 2nd. IEEE International Symposium on Logistics and Industrial Informatics (LINDI 2009)Linz, pp.-1-6 Austria. 10-12 Sep. 2009
• E. G. Talbi, L. Jourdan, J. García-Nieto and E. Alba. Comparison of population based metaheuristics for feature selection: Application to microarray data classification. In Proceedings of the 6th ACS/IEEE International Conference on Computer Systems and Applications (AICCSA-08), pp. 45-52, Doha, Qatar, 2008.
• E. Alba, J. García-Nieto, L. Jourdan and E. G. Talbi. Gene Selection in Cancer Classification using PSO/SVM and GA/SVM Hybrid Algorithms, In Proceedings of the IEEE Congress on Evolutionary Computation (CEC'2007), pp. 284-290, Singapore, 27 Sep, 2007. DOI: 10.1109/CEC.2007.4424483
• J. García-Nieto, L. Jourdan, E. Alba and E. G. Talbi. A Comparison of PSO and GA Approaches for Gene Selection and Classification of Microarray Data, In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO’07), London, UK, 2007.
• E. Alba, J. García-Nieto y G. Luque, Algoritmos Basados en Cúmulos de Partículas para el Análisis de Microarrays de ADN. En las Actas del V congreso sobre Metaheurísticas, Algoritmos Evolutivos y Bioinspirados (MAEB'07), pp. 419-426, Tenerife, España, Febrero, 2007.(BibTeX)