{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T16:19:56Z","timestamp":1742919596184,"version":"3.40.3"},"publisher-location":"Cham","reference-count":25,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030298586"},{"type":"electronic","value":"9783030298593"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-3-030-29859-3_10","type":"book-chapter","created":{"date-parts":[[2019,8,26]],"date-time":"2019-08-26T16:03:53Z","timestamp":1566835433000},"page":"111-122","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Evolutionary Algorithm for Pathways Detection in GWAS Studies"],"prefix":"10.1007","author":[{"given":"Fidel","family":"D\u00edez D\u00edaz","sequence":"first","affiliation":[]},{"given":"Fernando","family":"S\u00e1nchez Lasheras","sequence":"additional","affiliation":[]},{"given":"Francisco Javier","family":"de Cos Juez","sequence":"additional","affiliation":[]},{"given":"Vicente","family":"Mart\u00edn S\u00e1nchez","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,8,26]]},"reference":[{"key":"10_CR1","series-title":"Advances in Intelligent Systems and Computing","doi-asserted-by":"publisher","first-page":"419","DOI":"10.1007\/978-3-319-67180-2_41","volume-title":"International Joint Conference SOCO\u201917-CISIS\u201917-ICEUTE\u201917 Le\u00f3n, Spain, September 6\u20138, 2017, Proceeding","author":"C Gonzalez-Donquiles","year":"2018","unstructured":"Gonzalez-Donquiles, C., et al.: PoDA algorithm: predictive pathways in colorectal cancer. In: P\u00e9rez Garc\u00eda, H., Alfonso-Cend\u00f3n, J., S\u00e1nchez Gonz\u00e1lez, L., Quinti\u00e1n, H., Corchado, E. (eds.) SOCO\/CISIS\/ICEUTE -2017. AISC, vol. 649, pp. 419\u2013427. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-67180-2_41"},{"key":"10_CR2","series-title":"Advances in Intelligent Systems and Computing","doi-asserted-by":"publisher","first-page":"400","DOI":"10.1007\/978-3-319-67180-2_39","volume-title":"International Joint Conference SOCO\u201917-CISIS\u201917-ICEUTE\u201917 Le\u00f3n, Spain, September 6\u20138, 2017, Proceeding","author":"D\u00c1 Guti\u00e9rrez","year":"2018","unstructured":"Guti\u00e9rrez, D.\u00c1., et al.: A multiregressive approach for SNPs identification in prostate cancer. In: P\u00e9rez Garc\u00eda, H., Alfonso-Cend\u00f3n, J., S\u00e1nchez Gonz\u00e1lez, L., Quinti\u00e1n, H., Corchado, E. (eds.) SOCO\/CISIS\/ICEUTE -2017. AISC, vol. 649, pp. 400\u2013409. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-67180-2_39"},{"key":"10_CR3","doi-asserted-by":"publisher","first-page":"356","DOI":"10.1038\/nrg2344","volume":"9","author":"M McCarthy","year":"2008","unstructured":"McCarthy, M., Abecasis, G., Cardon, L., et al.: Genome-wide association studies for complex traits: consensus, uncertainty and challenges. Nat. Rev. Genet. 9, 356\u2013369 (2008). https:\/\/doi.org\/10.1038\/nrg2344","journal-title":"Nat. Rev. Genet."},{"key":"10_CR4","doi-asserted-by":"publisher","first-page":"445","DOI":"10.1093\/bioinformatics\/btp713","volume":"26","author":"J Moore","year":"2010","unstructured":"Moore, J., Asselbergs, F., Williams, S.: Bioinformatics challenges for genome-wide association studies. Bioinformatics 26, 445\u2013455 (2010). https:\/\/doi.org\/10.1093\/bioinformatics\/btp713","journal-title":"Bioinformatics"},{"key":"10_CR5","doi-asserted-by":"publisher","first-page":"7","DOI":"10.1016\/j.ajhg.2011.11.029","volume":"90","author":"P Visscher","year":"2012","unstructured":"Visscher, P., Brown, M., McCarthy, M., Yang, J.: Five years of GWAS discovery. Am. J. Hum. Genet. 90, 7\u201324 (2012). https:\/\/doi.org\/10.1016\/j.ajhg.2011.11.029","journal-title":"Am. J. Hum. Genet."},{"key":"10_CR6","doi-asserted-by":"publisher","first-page":"e201604000013","DOI":"10.19185\/matters.201604000013","volume":"2","author":"Y Fan","year":"2016","unstructured":"Fan, Y., Song, Y.: Finding the missing heritability of genome-wide association study using genotype imputation. Matters 2, e201604000013 (2016). https:\/\/doi.org\/10.19185\/matters.201604000013","journal-title":"Matters"},{"key":"10_CR7","doi-asserted-by":"publisher","first-page":"383","DOI":"10.3389\/fphys.2015.00383","volume":"6","author":"M Garc\u00eda-Campos","year":"2015","unstructured":"Garc\u00eda-Campos, M., Espinal-Enr\u00edquez, J., Hern\u00e1ndez-Lemus, E.: Pathway analysis: state of the art. Front. Physiol. 6, 383 (2015). https:\/\/doi.org\/10.3389\/fphys.2015.00383","journal-title":"Front. Physiol."},{"key":"10_CR8","doi-asserted-by":"publisher","first-page":"e1608","DOI":"10.1002\/mpr.1608","volume":"27","author":"A Marees","year":"2018","unstructured":"Marees, A., de Kluiver, H., Stringer, S., et al.: A tutorial on conducting genome-wide association studies: quality control and statistical analysis. Int. J. Methods Psychiatr. Res. 27, e1608 (2018). https:\/\/doi.org\/10.1002\/mpr.1608","journal-title":"Int. J. Methods Psychiatr. Res."},{"key":"10_CR9","doi-asserted-by":"publisher","first-page":"68","DOI":"10.1016\/j.ecoleng.2012.12.015","volume":"53","author":"J Alonso Fern\u00e1ndez","year":"2013","unstructured":"Alonso Fern\u00e1ndez, J., D\u00edaz Mu\u00f1iz, C., Garcia Nieto, P., de Cos, J.F., S\u00e1nchez Lasheras, F., Roque\u00f1\u00ed, M.: Forecasting the cyanotoxins presence in fresh waters: a new model based on genetic algorithms combined with the MARS technique. Ecol. Eng. 53, 68\u201378 (2013). https:\/\/doi.org\/10.1016\/j.ecoleng.2012.12.015","journal-title":"Ecol. Eng."},{"key":"10_CR10","series-title":"Genetic and Evolutionary Computation","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1007\/978-0-387-49650-4_2","volume-title":"Genetic Programming Theory and Practice IV","author":"JH Moore","year":"2007","unstructured":"Moore, J.H., White, B.: Genome-wide genetic analysis using genetic programming: the critical need for expert knowledge. In: Riolo, R., Soule, T., Worzel, B. (eds.) Genetic Programming Theory and Practice IV. Genetic and Evolutionary Computation, pp. 11\u201328. Springer, Boston (2007). https:\/\/doi.org\/10.1007\/978-0-387-49650-4_2"},{"key":"10_CR11","doi-asserted-by":"publisher","first-page":"704","DOI":"10.1016\/j.cam.2016.08.012","volume":"311","author":"C Ord\u00f3\u00f1ez Gal\u00e1n","year":"2017","unstructured":"Ord\u00f3\u00f1ez Gal\u00e1n, C., S\u00e1nchez Lasheras, F., de Cos, J.F., Bernardo S\u00e1nchez, A.: Missing data imputation of questionnaires by means of genetic algorithms with different fitness functions. J. Comput. Appl. Math. 311, 704\u2013717 (2017). https:\/\/doi.org\/10.1016\/j.cam.2016.08.012","journal-title":"J. Comput. Appl. Math."},{"key":"10_CR12","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"547","DOI":"10.1007\/978-3-319-92639-1_46","volume-title":"13th International Conference, HAIS 2018, Oviedo, Spain, June 20-22, 2018","author":"JE S\u00e1nchez Lasheras","year":"2018","unstructured":"S\u00e1nchez Lasheras, J.E., et al.: Classification of prostate cancer patients and healthy individuals by means of a hybrid algorithm combining SVM and evolutionary algorithms. In: de Cos Juez, F.J., et al. (eds.) HAIS 2018. LNCS, pp. 547\u2013557. Springer, Heidelberg (2018). https:\/\/doi.org\/10.1007\/978-3-319-92639-1_46"},{"key":"10_CR13","doi-asserted-by":"publisher","first-page":"3539","DOI":"10.1016\/j.amc.2011.08.100","volume":"218","author":"A Su\u00e1rez S\u00e1nchez","year":"2011","unstructured":"Su\u00e1rez S\u00e1nchez, A., Riesgo Fern\u00e1ndez, P., S\u00e1nchez Lasheras, F., et al.: Prediction of work-related accidents according to working conditions using support vector machines. Appl. Math. Comput. 218, 3539\u20133552 (2011). https:\/\/doi.org\/10.1016\/j.amc.2011.08.100","journal-title":"Appl. Math. Comput."},{"key":"10_CR14","doi-asserted-by":"publisher","first-page":"88","DOI":"10.1016\/j.scitotenv.2012.04.068","volume":"430","author":"P Garc\u00eda Nieto","year":"2012","unstructured":"Garc\u00eda Nieto, P., Alonso Fern\u00e1ndez, J., S\u00e1nchez Lasheras, F., de Cos, J.F., D\u00edaz Mu\u00f1iz, C.: A new improved study of cyanotoxins presence from experimental cyanobacteria concentrations in the Trasona reservoir (Northern Spain) using the MARS technique. Sci. Total Environ. 430, 88\u201392 (2012). https:\/\/doi.org\/10.1016\/j.scitotenv.2012.04.068","journal-title":"Sci. Total Environ."},{"key":"10_CR15","doi-asserted-by":"publisher","first-page":"4770","DOI":"10.1016\/j.eswa.2013.02.032","volume":"40","author":"P Rosado","year":"2013","unstructured":"Rosado, P., Lequerica-Fern\u00e1ndez, P., Villalla\u00edn, L., et al.: Survival model in oral squamous cell carcinoma based on clinicopathological parameters, molecular markers and support vector machines. Expert Syst. Appl. 40, 4770\u20134776 (2013). https:\/\/doi.org\/10.1016\/j.eswa.2013.02.032","journal-title":"Expert Syst. Appl."},{"key":"10_CR16","doi-asserted-by":"publisher","first-page":"3457","DOI":"10.1007\/s11269-013-0358-4","volume":"27","author":"J Vil\u00e1n Vil\u00e1n","year":"2013","unstructured":"Vil\u00e1n Vil\u00e1n, J., Alonso Fern\u00e1ndez, J., Garc\u00eda Nieto, P., et al.: Support vector machines and multilayer perceptron networks used to evaluate the cyanotoxins presence from experimental cyanobacteria concentrations in the Trasona reservoir (Northern Spain). Water Resour. Manage. 27, 3457\u20133476 (2013). https:\/\/doi.org\/10.1007\/s11269-013-0358-4","journal-title":"Water Resour. Manage."},{"key":"10_CR17","doi-asserted-by":"publisher","first-page":"753","DOI":"10.1016\/j.scitotenv.2017.11.291","volume":"621","author":"P Garc\u00eda Nieto","year":"2018","unstructured":"Garc\u00eda Nieto, P., S\u00e1nchez Lasheras, F., Garc\u00eda-Gonzalo, E., de Cos, J.F.: PM10 concentration forecasting in the metropolitan area of Oviedo (Northern Spain) using models based on SVM, MLP, VARMA and ARIMA: a case study. Sci. Total Environ. 621, 753\u2013761 (2018). https:\/\/doi.org\/10.1016\/j.scitotenv.2017.11.291","journal-title":"Sci. Total Environ."},{"key":"10_CR18","unstructured":"R Core Team: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria (2018). https:\/\/www.R-project.org\/"},{"issue":"4","key":"10_CR19","doi-asserted-by":"publisher","first-page":"1","DOI":"10.18637\/jss.v053.i04","volume":"53","author":"L Scrucca","year":"2013","unstructured":"Scrucca, L.: GA: a package for genetic algorithms in R. J. Stat. Softw. 53(4), 1\u201337 (2013). https:\/\/www.jstatsoft.org\/v53\/i04\/","journal-title":"J. Stat. Softw."},{"issue":"3","key":"10_CR20","doi-asserted-by":"publisher","first-page":"227","DOI":"10.1007\/s00787-010-0087-7","volume":"19","author":"M Szumilas","year":"2010","unstructured":"Szumilas, M.: Explaining odds ratios. J. Can. Acad. Child Adolesc. Psychiatry 19(3), 227\u2013229 (2010)","journal-title":"J. Can. Acad. Child Adolesc. Psychiatry"},{"key":"10_CR21","doi-asserted-by":"publisher","first-page":"731","DOI":"10.21105\/joss.00731","volume":"3","author":"SD Turner","year":"2018","unstructured":"Turner, S.D.: qqman: an R package for visualizing GWAS results using Q-Q and Manhattan plots. J. Open Source Softw. 3, 731 (2018). https:\/\/doi.org\/10.21105\/joss.00731","journal-title":"J. Open Source Softw."},{"key":"10_CR22","doi-asserted-by":"publisher","first-page":"48","DOI":"10.1159\/000070907","volume":"3","author":"J Satagopan","year":"2003","unstructured":"Satagopan, J., Smith, A.: Statistical methods in genomics research. Heart Drug 3, 48\u201360 (2003). https:\/\/doi.org\/10.1159\/000070907","journal-title":"Heart Drug"},{"key":"10_CR23","volume-title":"Adaptation in Natural and Artificial Systems","author":"J Holland","year":"1975","unstructured":"Holland, J.: Adaptation in Natural and Artificial Systems. University of Michigan Press, Ann Arbor (1975)"},{"key":"10_CR24","unstructured":"\u00d6stensson, M.: Statistical methods for genome wide association studies. Chalmers University of Technology and the University of Gothenburg, G\u00f6teborg (2012)"},{"issue":"6","key":"10_CR25","doi-asserted-by":"publisher","first-page":"e1002101","DOI":"10.1371\/journal.pgen.1002101","volume":"7","author":"R Braun","year":"2011","unstructured":"Braun, R., Buetow, K.: Pathways of distinction analysis: a new technique for multi-SNP analysis of GWAS data. PLoS Genet. 7(6), e1002101 (2011). https:\/\/doi.org\/10.1371\/journal.pgen.1002101","journal-title":"PLoS Genet."}],"container-title":["Lecture Notes in Computer Science","Hybrid Artificial Intelligent Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-29859-3_10","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,12]],"date-time":"2024-03-12T18:08:56Z","timestamp":1710266936000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-29859-3_10"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030298586","9783030298593"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-29859-3_10","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"26 August 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"HAIS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Hybrid Artificial Intelligence Systems","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Le\u00f3n","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Spain","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 September 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6 September 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"hais2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/2019.haisconference.eu\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"easychair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"134","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"64","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"48% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"4","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}