{"file_date_updated":"2020-07-14T12:45:45Z","ddc":["570"],"project":[{"_id":"25B07788-B435-11E9-9278-68D0E5697425","name":"Limits to selection in biology and in evolutionary computation","grant_number":"250152","call_identifier":"FP7"}],"publist_id":"4174","year":"2013","ec_funded":1,"citation":{"short":"N.H. Barton, T. Paixao, in:, Proceedings of the 15th Annual Conference on Genetic and Evolutionary Computation, ACM, 2013, pp. 1573–1580.","apa":"Barton, N. H., &#38; Paixao, T. (2013). Can quantitative and population genetics help us understand evolutionary computation? In <i>Proceedings of the 15th annual conference on Genetic and evolutionary computation</i> (pp. 1573–1580). Amsterdam, Netherlands: ACM. <a href=\"https://doi.org/10.1145/2463372.2463568\">https://doi.org/10.1145/2463372.2463568</a>","ista":"Barton NH, Paixao T. 2013. Can quantitative and population genetics help us understand evolutionary computation? Proceedings of the 15th annual conference on Genetic and evolutionary computation. GECCO: Genetic and evolutionary computation conference, 1573–1580.","chicago":"Barton, Nicholas H, and Tiago Paixao. “Can Quantitative and Population Genetics Help Us Understand Evolutionary Computation?” In <i>Proceedings of the 15th Annual Conference on Genetic and Evolutionary Computation</i>, 1573–80. ACM, 2013. <a href=\"https://doi.org/10.1145/2463372.2463568\">https://doi.org/10.1145/2463372.2463568</a>.","ama":"Barton NH, Paixao T. Can quantitative and population genetics help us understand evolutionary computation? In: <i>Proceedings of the 15th Annual Conference on Genetic and Evolutionary Computation</i>. ACM; 2013:1573-1580. doi:<a href=\"https://doi.org/10.1145/2463372.2463568\">10.1145/2463372.2463568</a>","ieee":"N. H. Barton and T. Paixao, “Can quantitative and population genetics help us understand evolutionary computation?,” in <i>Proceedings of the 15th annual conference on Genetic and evolutionary computation</i>, Amsterdam, Netherlands, 2013, pp. 1573–1580.","mla":"Barton, Nicholas H., and Tiago Paixao. “Can Quantitative and Population Genetics Help Us Understand Evolutionary Computation?” <i>Proceedings of the 15th Annual Conference on Genetic and Evolutionary Computation</i>, ACM, 2013, pp. 1573–80, doi:<a href=\"https://doi.org/10.1145/2463372.2463568\">10.1145/2463372.2463568</a>."},"conference":{"end_date":"2013-07-10","location":"Amsterdam, Netherlands","start_date":"2013-07-06","name":"GECCO: Genetic and evolutionary computation conference"},"language":[{"iso":"eng"}],"pubrep_id":"564","_id":"2718","doi":"10.1145/2463372.2463568","page":"1573 - 1580","publication":"Proceedings of the 15th annual conference on Genetic and evolutionary computation","author":[{"id":"4880FE40-F248-11E8-B48F-1D18A9856A87","full_name":"Barton, Nicholas H","last_name":"Barton","first_name":"Nicholas H","orcid":"0000-0002-8548-5240"},{"orcid":"0000-0003-2361-3953","last_name":"Paixao","first_name":"Tiago","full_name":"Paixao, Tiago","id":"2C5658E6-F248-11E8-B48F-1D18A9856A87"}],"has_accepted_license":"1","quality_controlled":"1","title":"Can quantitative and population genetics help us understand evolutionary computation?","status":"public","oa":1,"oa_version":"Submitted Version","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_created":"2018-12-11T11:59:14Z","publisher":"ACM","scopus_import":1,"date_published":"2013-07-01T00:00:00Z","publication_status":"published","department":[{"_id":"NiBa"},{"_id":"CaGu"}],"abstract":[{"lang":"eng","text":"Even though both population and quantitative genetics, and evolutionary computation, deal with the same questions, they have developed largely independently of each other. I review key results from each field, emphasising those that apply independently of the (usually unknown) relation between genotype and phenotype. The infinitesimal model provides a simple framework for predicting the response of complex traits to selection, which in biology has proved remarkably successful. This allows one to choose the schedule of population sizes and selection intensities that will maximise the response to selection, given that the total number of individuals realised, C = ∑t Nt, is constrained. This argument shows that for an additive trait (i.e., determined by the sum of effects of the genes), the optimum population size and the maximum possible response (i.e., the total change in trait mean) are both proportional to √C."}],"file":[{"file_id":"5159","file_size":475844,"date_created":"2018-12-12T10:15:38Z","date_updated":"2020-07-14T12:45:45Z","content_type":"application/pdf","creator":"system","access_level":"open_access","file_name":"IST-2016-564-v1+1_NickGECCO_2013_1_-1.pdf","checksum":"9d9be9090ce5c20766e0eb076ace5b98","relation":"main_file"}],"type":"conference","day":"01","month":"07","date_updated":"2021-01-12T06:59:15Z"}