{"tmp":{"short":"CC BY (4.0)","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png"},"publication_status":"published","oa_version":"Published Version","oa":1,"has_accepted_license":"1","intvolume":"        95","file":[{"access_level":"open_access","file_size":569005,"checksum":"979d7a8034e9df198f068f0d251f31bd","date_created":"2018-12-12T10:10:49Z","content_type":"application/pdf","file_id":"4839","file_name":"IST-2015-391-v1+1_1-s2.0-S0040580914000355-main.pdf","relation":"main_file","creator":"system","date_updated":"2020-07-14T12:45:31Z"}],"department":[{"_id":"NiBa"}],"_id":"2168","title":"Coalescent simulation in continuous space: Algorithms for large neighbourhood size","month":"08","page":"13 - 23","date_updated":"2021-01-12T06:55:44Z","volume":95,"date_created":"2018-12-11T11:56:06Z","year":"2014","type":"journal_article","author":[{"first_name":"Jerome","last_name":"Kelleher","full_name":"Kelleher, Jerome"},{"first_name":"Alison","full_name":"Etheridge, Alison","last_name":"Etheridge"},{"orcid":"0000-0002-8548-5240","last_name":"Barton","full_name":"Barton, Nicholas H","first_name":"Nicholas H","id":"4880FE40-F248-11E8-B48F-1D18A9856A87"}],"ddc":["570"],"doi":"10.1016/j.tpb.2014.05.001","scopus_import":1,"citation":{"chicago":"Kelleher, Jerome, Alison Etheridge, and Nicholas H Barton. “Coalescent Simulation in Continuous Space: Algorithms for Large Neighbourhood Size.” <i>Theoretical Population Biology</i>. Academic Press, 2014. <a href=\"https://doi.org/10.1016/j.tpb.2014.05.001\">https://doi.org/10.1016/j.tpb.2014.05.001</a>.","ama":"Kelleher J, Etheridge A, Barton NH. Coalescent simulation in continuous space: Algorithms for large neighbourhood size. <i>Theoretical Population Biology</i>. 2014;95:13-23. doi:<a href=\"https://doi.org/10.1016/j.tpb.2014.05.001\">10.1016/j.tpb.2014.05.001</a>","ieee":"J. Kelleher, A. Etheridge, and N. H. Barton, “Coalescent simulation in continuous space: Algorithms for large neighbourhood size,” <i>Theoretical Population Biology</i>, vol. 95. Academic Press, pp. 13–23, 2014.","apa":"Kelleher, J., Etheridge, A., &#38; Barton, N. H. (2014). Coalescent simulation in continuous space: Algorithms for large neighbourhood size. <i>Theoretical Population Biology</i>. Academic Press. <a href=\"https://doi.org/10.1016/j.tpb.2014.05.001\">https://doi.org/10.1016/j.tpb.2014.05.001</a>","short":"J. Kelleher, A. Etheridge, N.H. Barton, Theoretical Population Biology 95 (2014) 13–23.","ista":"Kelleher J, Etheridge A, Barton NH. 2014. Coalescent simulation in continuous space: Algorithms for large neighbourhood size. Theoretical Population Biology. 95, 13–23.","mla":"Kelleher, Jerome, et al. “Coalescent Simulation in Continuous Space: Algorithms for Large Neighbourhood Size.” <i>Theoretical Population Biology</i>, vol. 95, Academic Press, 2014, pp. 13–23, doi:<a href=\"https://doi.org/10.1016/j.tpb.2014.05.001\">10.1016/j.tpb.2014.05.001</a>."},"language":[{"iso":"eng"}],"publisher":"Academic Press","publist_id":"4816","abstract":[{"lang":"eng","text":"Many species have an essentially continuous distribution in space, in which there are no natural divisions between randomly mating subpopulations. Yet, the standard approach to modelling these populations is to impose an arbitrary grid of demes, adjusting deme sizes and migration rates in an attempt to capture the important features of the population. Such indirect methods are required because of the failure of the classical models of isolation by distance, which have been shown to have major technical flaws. A recently introduced model of extinction and recolonisation in two dimensions solves these technical problems, and provides a rigorous technical foundation for the study of populations evolving in a spatial continuum. The coalescent process for this model is simply stated, but direct simulation is very inefficient for large neighbourhood sizes. We present efficient and exact algorithms to simulate this coalescent process for arbitrary sample sizes and numbers of loci, and analyse these algorithms in detail."}],"file_date_updated":"2020-07-14T12:45:31Z","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","quality_controlled":"1","publication":"Theoretical Population Biology","pubrep_id":"391","day":"01","status":"public","ec_funded":1,"project":[{"_id":"25B07788-B435-11E9-9278-68D0E5697425","call_identifier":"FP7","name":"Limits to selection in biology and in evolutionary computation","grant_number":"250152"}],"date_published":"2014-08-01T00:00:00Z"}