{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T14:40:43Z","timestamp":1740148843376,"version":"3.37.3"},"reference-count":24,"publisher":"Wiley","license":[{"start":{"date-parts":[[2009,8,12]],"date-time":"2009-08-12T00:00:00Z","timestamp":1250035200000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Journal of Artificial Evolution and Applications"],"published-print":{"date-parts":[[2009,8,12]]},"abstract":"<jats:p>Discovering the models explaining the hidden relationship between genetic material and tumor pathologies is one of the most important open challenges in biology and medicine. Given the large amount of data made available by the DNA Microarray technique, Machine Learning is becoming a popular tool for this kind of investigations. In the last few years, we have been particularly involved in the study of Genetic Programming for mining large sets of biomedical data. In this paper, we present a comparison between four variants of Genetic Programming for the classification of two different oncologic datasets: the first one contains data from healthy colon tissues and colon tissues affected by cancer; the second one contains data from patients affected by two kinds of leukemia (acute myeloid leukemia and acute lymphoblastic leukemia). We report experimental results obtained using two different fitness criteria: the receiver operating characteristic and the percentage of correctly classified instances. These results, and their comparison with the ones obtained by three nonevolutionary Machine Learning methods (Support Vector Machines, MultiBoosting, and Random Forests) on the same data, seem to hint that Genetic Programming is a promising technique for this kind of classification.<\/jats:p>","DOI":"10.1155\/2009\/848532","type":"journal-article","created":{"date-parts":[[2009,8,12]],"date-time":"2009-08-12T15:00:03Z","timestamp":1250089203000},"page":"1-13","source":"Crossref","is-referenced-by-count":4,"title":["Classification of Oncologic Data with Genetic Programming"],"prefix":"10.1155","volume":"2009","author":[{"given":"Leonardo","family":"Vanneschi","sequence":"first","affiliation":[{"name":"Department of Informatics, Systems and Communication (D.I.S.Co.), University of Milano-Bicocca, 20126 Milan, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1131-3830","authenticated-orcid":true,"given":"Francesco","family":"Archetti","sequence":"additional","affiliation":[{"name":"Department of Informatics, Systems and Communication (D.I.S.Co.), University of Milano-Bicocca, 20126 Milan, Italy"},{"name":"Consorzio Milano Ricerche, 20126 Milan, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8793-1451","authenticated-orcid":true,"given":"Mauro","family":"Castelli","sequence":"additional","affiliation":[{"name":"Department of Informatics, Systems and Communication (D.I.S.Co.), University of Milano-Bicocca, 20126 Milan, Italy"}]},{"given":"Ilaria","family":"Giordani","sequence":"additional","affiliation":[{"name":"Department of Informatics, Systems and Communication (D.I.S.Co.), University of Milano-Bicocca, 20126 Milan, Italy"}]}],"member":"311","reference":[{"year":"2000","key":"1"},{"year":"1992","key":"12"},{"key":"2","doi-asserted-by":"publisher","DOI":"10.1016\/S0306-4379(02)00072-8"},{"year":"1994","key":"5"},{"key":"3","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.96.12.6745"},{"key":"6","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btg296"},{"key":"8","doi-asserted-by":"publisher","DOI":"10.1023\/A:1012487302797"},{"key":"9","doi-asserted-by":"publisher","DOI":"10.1089\/106652700750050961"},{"year":"1975","key":"24"},{"year":"1989","key":"25"},{"key":"10","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/bti419"},{"key":"14","series-title":"Lecture Notes in Artificial Intelligence","volume-title":"Symbolic discriminant analysis for mining gene expression patterns","volume":"2167","year":"2001"},{"key":"15","doi-asserted-by":"publisher","DOI":"10.1593\/neo.07121"},{"key":"17","doi-asserted-by":"publisher","DOI":"10.1016\/j.artmed.2005.06.002"},{"journal-title":"Science","first-page":"531","year":"1999","key":"4"},{"key":"29","doi-asserted-by":"publisher","DOI":"10.1023\/B:GENP.0000030195.77571.f9"},{"issue":"4","key":"22","doi-asserted-by":"crossref","first-page":"283","DOI":"10.1016\/S0001-2998(78)80014-2","volume":"8","year":"1978","journal-title":"Seminars in Nuclear Medicine"},{"issue":"4","key":"23","doi-asserted-by":"crossref","first-page":"561","DOI":"10.1093\/clinchem\/39.4.561","volume":"39","year":"1993","journal-title":"Clinical Chemistry"},{"year":"1998","key":"18"},{"volume-title":"Fast training of support vector machines using sequential minimal optimization","year":"1998","key":"19"},{"issue":"1","key":"21","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1006\/jcss.1997.1504","volume":"55","year":"1997","journal-title":"Journal of Computer and System Sciences"},{"key":"20","doi-asserted-by":"publisher","DOI":"10.1023\/A:1007659514849"},{"year":"1984","key":"27"},{"key":"26","doi-asserted-by":"publisher","DOI":"10.1023\/A:1010933404324"}],"container-title":["Journal of Artificial Evolution and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/archive\/2009\/848532.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/archive\/2009\/848532.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/archive\/2009\/848532.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,12,8]],"date-time":"2020-12-08T19:00:25Z","timestamp":1607454025000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.hindawi.com\/journals\/jaea\/2009\/848532\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2009,8,12]]},"references-count":24,"alternative-id":["848532","848532"],"URL":"https:\/\/doi.org\/10.1155\/2009\/848532","relation":{},"ISSN":["1687-6229","1687-6237"],"issn-type":[{"type":"print","value":"1687-6229"},{"type":"electronic","value":"1687-6237"}],"subject":[],"published":{"date-parts":[[2009,8,12]]}}}