{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,15]],"date-time":"2026-04-15T20:22:24Z","timestamp":1776284544621,"version":"3.50.1"},"reference-count":46,"publisher":"EDP Sciences","issue":"1","license":[{"start":{"date-parts":[[2019,2,15]],"date-time":"2019-02-15T00:00:00Z","timestamp":1550188800000},"content-version":"vor","delay-in-days":45,"URL":"https:\/\/www.edpsciences.org\/en\/authors\/copyright-and-licensing"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["RAIRO-Oper. Res."],"accepted":{"date-parts":[[2018,7,7]]},"published-print":{"date-parts":[[2019,1]]},"abstract":"<jats:p>Gene expression data (DNA microarray) enable researchers to simultaneously measure the levels of expression of several thousand genes. These levels of expression are very important in the classification of different types of tumors. In this work, we are interested in gene selection, which is an essential step in the data pre-processing for cancer classification. This selection makes it possible to represent a small subset of genes from a large set, and to eliminate the redundant, irrelevant or noisy genes. The combinatorial nature of the selection problem requires the development of specific techniques such as filters and Wrappers, or hybrids combining several optimization processes. In this context, we propose two hybrid approaches (RBPSO-1NN and FBPSO-SVM) for the gene selection problem, based on the combination of the filter methods (the Fisher criterion and the ReliefF algorithm), the BPSO metaheuristic algorithms and the Backward algorithm using the classifiers (SVM and 1NN) for the evaluation of the relevance of the candidate subsets. In order to verify the performance of our methods, we have tested them on eight well-known microarray datasets of high dimensions varying from 2308 to 11225 genes. The experiments carried out on the different datasets show that our methods prove to be very competitive with the existing works.<\/jats:p>","DOI":"10.1051\/ro\/2018059","type":"journal-article","created":{"date-parts":[[2018,7,10]],"date-time":"2018-07-10T18:44:20Z","timestamp":1531248260000},"page":"269-288","source":"Crossref","is-referenced-by-count":7,"title":["Gene selection <i>via<\/i> BPSO and Backward generation for cancer classification"],"prefix":"10.1051","volume":"53","author":[{"given":"Ahmed","family":"Bir-Jmel","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sidi","family":"Mohamed Douiri","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Souad","family":"Elbernoussi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"250","published-online":{"date-parts":[[2019,2,15]]},"reference":[{"key":"R1","first-page":"221","volume":"87","author":"Agarwal","year":"2017","journal-title":"Proc. Nat. Acad. Sci. India Sec. A: Phys. Sci."},{"key":"R2","doi-asserted-by":"crossref","unstructured":"Alba E., Garcia-Nieto J., Jourdan L. and Talbi E.G., Gene selection in cancer classification using PSO\/SVM and GA\/SVM hybrid algorithms. In: IEEE Congress on Evolutionary Computation, 2007. CEC 2007. IEEE (2007, September) 284\u2013290.","DOI":"10.1109\/CEC.2007.4424483"},{"key":"R3","doi-asserted-by":"crossref","first-page":"503","DOI":"10.1038\/35000501","volume":"403","author":"Alizadeh","year":"2000","journal-title":"Nature"},{"key":"R4","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1016\/S0304-3975(97)00115-1","volume":"209","author":"Amaldi","year":"1998","journal-title":"Theor. Comput. Sci."},{"key":"R5","doi-asserted-by":"crossref","first-page":"922","DOI":"10.1016\/j.asoc.2015.10.037","volume":"38","author":"Apolloni","year":"2016","journal-title":"Appl. Soft Comput."},{"key":"R6","doi-asserted-by":"crossref","first-page":"773","DOI":"10.1016\/j.asoc.2014.08.032","volume":"24","author":"Chen","year":"2014","journal-title":"Appl. Soft Comput."},{"key":"R7","doi-asserted-by":"crossref","unstructured":"Chiang Y.M., Chiang H.M. and Lin S.Y., The application of ant colony optimization for gene selection in microarray-based cancer classification. In: International Conference on Machine Learning and Cybernetics, 2008. IEEE (2008) 4001\u20134006.","DOI":"10.1109\/ICMLC.2008.4621102"},{"key":"R8","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1016\/j.compbiolchem.2007.09.005","volume":"32","author":"Chuang","year":"2008","journal-title":"Comput. Biol. Chem."},{"key":"R9","doi-asserted-by":"crossref","first-page":"1689","DOI":"10.1089\/cmb.2007.0211","volume":"16","author":"Chuang","year":"2009","journal-title":"J. Comput. Biol."},{"key":"R10","first-page":"273","volume":"20","author":"Cortes","year":"1995","journal-title":"Mach. Learn."},{"key":"R11","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1109\/TIT.1967.1053964","volume":"13","author":"Cover","year":"1967","journal-title":"IEEE Trans. Info. Theory"},{"key":"R12","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1016\/j.ygeno.2017.07.010","volume":"110","author":"Dashtban","year":"2018","journal-title":"Genomics"},{"key":"R13","doi-asserted-by":"crossref","unstructured":"Fix E. and Hodges J.L., Discriminatory Analysis-Nonparametric Discrimination: Consistency Properties. California Univ Berkeley, Berkeley (1951).","DOI":"10.1037\/e471672008-001"},{"key":"R14","doi-asserted-by":"crossref","first-page":"531","DOI":"10.1126\/science.286.5439.531","volume":"286","author":"Golub","year":"1999","journal-title":"Science"},{"key":"R15","unstructured":"Guermeur Y., SVM multiclasses, th\u00e9orie et applications. Habilitation \u00e0 diriger des recherches. UHP (2007)."},{"key":"R16","unstructured":"Gu Q., Li Z. and Han J.Generalized fisher score for feature selection. Preprint arXiv: 1202.3725 (2012)."},{"key":"R17","unstructured":"Hsu C.W., Chang C.C. and Lin C.J., A practical guide to support vector classification. Available at: http:\/\/www.csie.ntu.edu.tw\/ cjlin\/ papers\/guide\/guide.pdf (2003)."},{"key":"R18","unstructured":"Huang H.Y. and Lin C.J., Linear and kernel classification: when to use which? In: Proc. of the 2016 SIAM International Conference on Data Mining. Society for Industrial and Applied Mathematics (2016) 216\u2013224."},{"key":"R19","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1186\/1472-6947-6-27","volume":"6","author":"Jafari","year":"2006","journal-title":"BMC Med. Info. Decis. Mak."},{"key":"R20","unstructured":"Kennedy J. and Eberhart R., PSO optimization. In: Proc. IEEE Int. Conf. Neural Networks. IEEE Service Center, Piscataway, NJ 4 (1995) 1941\u20131948."},{"key":"R21","doi-asserted-by":"crossref","unstructured":"Kennedy J. and Eberhart R.C., A discrete binary version of the particle swarm algorithm. In: Systems, Man, and Cybernetics, 1997. IEEE International Conference on Computational Cybernetics and Simulation. IEEE 5 (1997) 4104\u20134108.","DOI":"10.1109\/ICSMC.1997.637339"},{"key":"R22","unstructured":"Kira K. and Rendell L.A., A practical approach to feature selection. In: Proc. of the Ninth International Workshop on Machine Learning. Morgan Kaufmann Publishers Inc., San Francisco (1992) 249\u2013256."},{"key":"R23","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1016\/S0004-3702(97)00043-X","volume":"97","author":"Kohavi","year":"1997","journal-title":"Artif. Intell."},{"key":"R24","unstructured":"Kononenko I., Estimating attributes: analysis and extensions of RELIEFIn: European Conference on Machine Learning. Springer, Berlin, Heidelberg (1994) 171\u2013182."},{"key":"R25","first-page":"1048","volume":"2","author":"Kumari","year":"2011","journal-title":"Int. J. Comput. Sci. Inf. Technol."},{"key":"R26","doi-asserted-by":"crossref","first-page":"331","DOI":"10.1016\/j.neucom.2016.08.089","volume":"218","author":"Lai","year":"2016","journal-title":"Neurocomputing"},{"key":"R27","doi-asserted-by":"crossref","first-page":"208","DOI":"10.1016\/j.asoc.2009.11.010","volume":"11","author":"Lee","year":"2011","journal-title":"Appl. Soft Comput."},{"key":"R28","doi-asserted-by":"crossref","first-page":"231","DOI":"10.1016\/S1672-6529(13)60219-X","volume":"10","author":"Li","year":"2013","journal-title":"J. Bionic Eng."},{"key":"R29","doi-asserted-by":"crossref","first-page":"1039","DOI":"10.1007\/s00500-007-0272-x","volume":"12","author":"Li","year":"2008","journal-title":"Soft Comput."},{"key":"R30","unstructured":"Liu H. and Motoda H., Feature selection for knowledge discovery and data mining. In Vol. 454. Springer Science Business Media (2012)."},{"key":"R31","first-page":"1","volume":"2","author":"Mishra","year":"2011","journal-title":"Int. J. Sci. Eng. Res."},{"key":"R32","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1186\/1748-7188-8-15","volume":"8","author":"Mohamad","year":"2013","journal-title":"Algorithm Mol. Biol."},{"key":"R33","doi-asserted-by":"crossref","unstructured":"Pati S.K., Das A.K., Ghosh A., Gene selection using multi-objective genetic algorithm integrating cellular automata and rough set theory. In: International Conference on Swarm, Evolutionary, and Memetic Computing. Springer, Cham (2013) 144\u2013155.","DOI":"10.1007\/978-3-319-03756-1_13"},{"key":"R34","doi-asserted-by":"crossref","first-page":"5022","DOI":"10.1073\/pnas.91.11.5022","volume":"91","author":"Pease","year":"1994","journal-title":"Proc. Nat. Acad. Sci."},{"key":"R35","unstructured":"Platt J.C., Cristianini N. and Shawe-Taylor J., Large margin DAGs for multiclass classification. In: Proc. of Advances in neural information processing systems (2000) 547\u2013553."},{"key":"R36","doi-asserted-by":"crossref","first-page":"231","DOI":"10.1016\/j.ygeno.2016.05.001","volume":"107","author":"Sharbaf","year":"2016","journal-title":"Genomics"},{"key":"R37","first-page":"1034","volume":"46","author":"Shreem","year":"2012","journal-title":"J. Theor. Appl. Inf. Technol."},{"key":"R38","unstructured":"Statnikov A., Aliferis C. and Tsamardinos I., Gems: Gene Expression Model Selector. Available at: http:\/\/www.gems-system.org (2005)."},{"key":"R39","doi-asserted-by":"crossref","first-page":"1024","DOI":"10.1016\/j.neucom.2015.05.022","volume":"168","author":"Tabakhi","year":"2015","journal-title":"Neurocomputing"},{"key":"R40","doi-asserted-by":"crossref","unstructured":"Wang Z., Neuro-fuzzy modeling for microarray cancer gene expression data. First year transfer report. University of Oxford (2005).","DOI":"10.1109\/ISEFS.2006.251144"},{"key":"R41","first-page":"9721713","volume":"2016","author":"Wang","year":"2016","journal-title":"BioMed Res. Int."},{"key":"R42","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s10115-007-0114-2","volume":"14","author":"Wu","year":"2008","journal-title":"Knowl. Info. Syst."},{"key":"R43","doi-asserted-by":"crossref","first-page":"2584","DOI":"10.1109\/JPROC.2012.2188013","volume":"100","author":"Yuan","year":"2012","journal-title":"Proc. IEEE"},{"key":"R44","doi-asserted-by":"crossref","first-page":"200","DOI":"10.1016\/S1672-0229(08)60050-9","volume":"7","author":"Yu","year":"2009","journal-title":"Genomics Proteomics Bioinf."},{"key":"R45","first-page":"184","volume":"3","author":"Zhao","year":"2011","journal-title":"Int. J. Adv. Comput. Technol."},{"key":"R46","doi-asserted-by":"crossref","first-page":"1274","DOI":"10.1016\/j.engappai.2012.12.009","volume":"26","author":"Zibakhsh","year":"2013","journal-title":"Eng. App. Artif. Intell."}],"container-title":["RAIRO - Operations Research"],"original-title":[],"link":[{"URL":"https:\/\/www.rairo-ro.org\/10.1051\/ro\/2018059\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,3,20]],"date-time":"2020-03-20T07:57:15Z","timestamp":1584691035000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.rairo-ro.org\/10.1051\/ro\/2018059"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,1]]},"references-count":46,"journal-issue":{"issue":"1"},"alternative-id":["ro170173"],"URL":"https:\/\/doi.org\/10.1051\/ro\/2018059","relation":{},"ISSN":["0399-0559","1290-3868"],"issn-type":[{"value":"0399-0559","type":"print"},{"value":"1290-3868","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,1]]}}}