Combinatorial Optimization Models for Finding Genetic Signatures from Gene Expression Datasets (original) (raw)
References
Tamayo, P., Ramaswamy, S. (2003) Micro-array data analysis: cancer genomics and molecular pattern recognition, in (Ladanyi, M., Gerald, W., eds.),Expression Profiling of Human Tumors: Diagnostic and Research Applications. Humana Press, Totowa, NJ. Google Scholar
Brazma, A., Vilo, J. (2000) Gene expression data analysis.FEBS Letts 480, 17–24. ArticleCAS Google Scholar
Brown, M. P., Grundy, W. N., Lin, D., et al. (2000) Knowledge-based analysis of micro-array gene expression data by using support vector machines.Proc Natl Acad Sci U S A 97, 62–267. Google Scholar
Eisen, M., Spellman, P., Brown, P., et al. (1998) Cluster analysis and display of genome-wide expression patterns.Proc Natl Acad Sci U S A 95, 14863–14868. ArticlePubMedCAS Google Scholar
Moscato, P., Mendes, A., Berretta, R. Benchmarking (2007) a memetic algorithm for ordering microarray data.BioSystems 88 (I-2), 56–75. ArticlePubMedCAS Google Scholar
Brown, V., Ossadtchi, A., Khan, A., et al. (2002) High-throughput imaging of brain gene expression.Genome Res 12, 244–254. ArticlePubMedCAS Google Scholar
Berretta R., Mendes, A., Moscato, P. (2005) Integer programming models and algorithms for molecular classification of cancer from microarray data. Proceedings of the 28th Australasian Computer Science Conference, in (V. Estivill-Castro, ed.),Conferences in Research and Practice in Information Technology 38, 361–370. Google Scholar
Moscato P., Berretta R., Hourani M., et al. (2005) Genes related with Alzheimer's disease: a comparison of evolutionary search, statistical and integer programming approaches. Proceedings of EvoBIO2005: 3rd European Workshop on Evolutionary Bioinformatics, in (Rothlauf, F., et al. eds.),Lecture Notes in Computer Science 3449, 84–94. Google Scholar
Pardalos, P. M., Resende, M. G. C. (2002)Handbook of Applied Optimization. Oxford University Press, New York. Google Scholar
Sun, M., Xiong, M. (2003) A mathematical programming approach for gene selection and tissue classification.Bioinformatics 19, 1243–1251. ArticlePubMedCAS Google Scholar
Merz, P. (2003) Analysis of gene expression profiles: an application of memetic algorithms to the minimum sum-of-squares clustering problem.BioSystems 72, 99–109. ArticlePubMedCAS Google Scholar
Lee, S., Kim, Y., Moon, B. (2003) Finding the optimal gene order in displaying micro-array data. Proceedings of GECCO2003: Genetic and Evolutionary Computation Conference, in (Cantu-Paz, E., et al., eds),Lecture Notes in Computer Science 2724, 2215–2226. Google Scholar
Cotta, C., Moscato, P. (2003) A memetic-aided approach to hierarchical clustering from distance matrices: application to phylogeny and gene expression clustering.Biosystems 72, 75–97. ArticlePubMedCAS Google Scholar
Greenberg, H., Hart, W., Lancia, G. (2004) Opportunities for combinatorial optimization in computational biology.INFORMS J Comput 16, 211–231. Article Google Scholar
Rizzi, R., Bafna, V., Istrail, S., et al. (2002) Practical algorithms and fixed-parameter tractability for the single individual SNP haplotyping problem. Proc. 2nd Annual Workshop on Algorithms in Bioinformatics (WABI), in (Guigo, R., Gusfield, D., eds.),Lecture Notes in Computer Science 2452, 29–43. Google Scholar
Moscato, P., Cotta, C. (2003) A gentle introduction to memetic algorithms. in (Glover, F., Kochenberger, G., eds.),Handbook of Metaheuristics. Kluwer Academic Publishers, Boston. Google Scholar
Glover, F., Laguna, M. (1997)Tabu Search. Kluwer Academic Publishers, Norwell, MA. Google Scholar
Davies, S., Russell, S. (1994)_NP_-completeness of searches for smallest possible feature sets, in (Greiner, R., Subramanian, D., eds.),AAAI Symposium on Intelligent Relevance. New Orleans, AAAI Press. Google Scholar
Cotta, C., Moscato, P. (2003) The_k_-FEATURE SET Problem is_W_[2]-Complete.J Comput Syst Sci 67, 686–690. Article Google Scholar
Cotta, C., Sloper, C., Moscato, P. (2004) Evolutionary search of thresholds for robust feature selection: application to the analysis of microarray data, in (Raidl, G., et al. eds.),Applications of Evolutionary Computing Lecture Notes in Computer Science. 3005, 21–30. Google Scholar
Fayyad, U., Irani, K. (1993) Multi-interval discretization of continuous-valued attributes for classification learning.Proceedings of the 13th International Joint Conference on Artificial Intelligence. 1022–1029. Google Scholar