[{"isi":1,"corr_author":"1","title":"Well posedness and maximum entropy approximation for the dynamics of quantitative traits","status":"public","_id":"607","oa":1,"date_created":"2018-12-11T11:47:28Z","abstract":[{"lang":"eng","text":"We study the Fokker-Planck equation derived in the large system limit of the Markovian process describing the dynamics of quantitative traits. The Fokker-Planck equation is posed on a bounded domain and its transport and diffusion coefficients vanish on the domain's boundary. We first argue that, despite this degeneracy, the standard no-flux boundary condition is valid. We derive the weak formulation of the problem and prove the existence and uniqueness of its solutions by constructing the corresponding contraction semigroup on a suitable function space. Then, we prove that for the parameter regime with high enough mutation rate the problem exhibits a positive spectral gap, which implies exponential convergence to equilibrium.Next, we provide a simple derivation of the so-called Dynamic Maximum Entropy (DynMaxEnt) method for approximation of observables (moments) of the Fokker-Planck solution, which can be interpreted as a nonlinear Galerkin approximation. The limited applicability of the DynMaxEnt method inspires us to introduce its modified version that is valid for the whole range of admissible parameters. Finally, we present several numerical experiments to demonstrate the performance of both the original and modified DynMaxEnt methods. We observe that in the parameter regimes where both methods are valid, the modified one exhibits slightly better approximation properties compared to the original one."}],"oa_version":"Submitted Version","scopus_import":"1","date_updated":"2024-10-09T20:58:45Z","year":"2018","publication_status":"published","page":"108-120","external_id":{"isi":["000437962900012"],"arxiv":["1704.08757"]},"type":"journal_article","volume":"376-377","doi":"10.1016/j.physd.2017.10.015","month":"08","publist_id":"7198","quality_controlled":"1","author":[{"first_name":"Katarina","last_name":"Bodova","full_name":"Bodova, Katarina","orcid":"0000-0002-7214-0171","id":"2BA24EA0-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Jan","last_name":"Haskovec","full_name":"Haskovec, Jan"},{"last_name":"Markowich","first_name":"Peter","full_name":"Markowich, Peter"}],"department":[{"_id":"NiBa"},{"_id":"GaTk"}],"acknowledgement":"JH and PM are funded by KAUST baseline funds and grant no. 1000000193 .\r\nWe thank Nicholas Barton (IST Austria) for his useful comments and suggestions. \r\n\r\n","arxiv":1,"language":[{"iso":"eng"}],"publication":"Physica D: Nonlinear Phenomena","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","citation":{"apa":"Bodova, K., Haskovec, J., &#38; Markowich, P. (2018). Well posedness and maximum entropy approximation for the dynamics of quantitative traits. <i>Physica D: Nonlinear Phenomena</i>. Elsevier. <a href=\"https://doi.org/10.1016/j.physd.2017.10.015\">https://doi.org/10.1016/j.physd.2017.10.015</a>","mla":"Bodova, Katarina, et al. “Well Posedness and Maximum Entropy Approximation for the Dynamics of Quantitative Traits.” <i>Physica D: Nonlinear Phenomena</i>, vol. 376–377, Elsevier, 2018, pp. 108–20, doi:<a href=\"https://doi.org/10.1016/j.physd.2017.10.015\">10.1016/j.physd.2017.10.015</a>.","chicago":"Bodova, Katarina, Jan Haskovec, and Peter Markowich. “Well Posedness and Maximum Entropy Approximation for the Dynamics of Quantitative Traits.” <i>Physica D: Nonlinear Phenomena</i>. Elsevier, 2018. <a href=\"https://doi.org/10.1016/j.physd.2017.10.015\">https://doi.org/10.1016/j.physd.2017.10.015</a>.","ista":"Bodova K, Haskovec J, Markowich P. 2018. Well posedness and maximum entropy approximation for the dynamics of quantitative traits. Physica D: Nonlinear Phenomena. 376–377, 108–120.","ieee":"K. Bodova, J. Haskovec, and P. Markowich, “Well posedness and maximum entropy approximation for the dynamics of quantitative traits,” <i>Physica D: Nonlinear Phenomena</i>, vol. 376–377. Elsevier, pp. 108–120, 2018.","ama":"Bodova K, Haskovec J, Markowich P. Well posedness and maximum entropy approximation for the dynamics of quantitative traits. <i>Physica D: Nonlinear Phenomena</i>. 2018;376-377:108-120. doi:<a href=\"https://doi.org/10.1016/j.physd.2017.10.015\">10.1016/j.physd.2017.10.015</a>","short":"K. Bodova, J. Haskovec, P. Markowich, Physica D: Nonlinear Phenomena 376–377 (2018) 108–120."},"publisher":"Elsevier","article_processing_charge":"No","day":"01","main_file_link":[{"url":"https://arxiv.org/abs/1704.08757","open_access":"1"}],"date_published":"2018-08-01T00:00:00Z"},{"citation":{"short":"H. Ringbauer, Inferring Recent Demography from Spatial Genetic Structure, Institute of Science and Technology Austria, 2018.","ama":"Ringbauer H. Inferring recent demography from spatial genetic structure. 2018. doi:<a href=\"https://doi.org/10.15479/AT:ISTA:th_963\">10.15479/AT:ISTA:th_963</a>","ieee":"H. Ringbauer, “Inferring recent demography from spatial genetic structure,” Institute of Science and Technology Austria, 2018.","ista":"Ringbauer H. 2018. Inferring recent demography from spatial genetic structure. Institute of Science and Technology Austria.","chicago":"Ringbauer, Harald. “Inferring Recent Demography from Spatial Genetic Structure.” Institute of Science and Technology Austria, 2018. <a href=\"https://doi.org/10.15479/AT:ISTA:th_963\">https://doi.org/10.15479/AT:ISTA:th_963</a>.","mla":"Ringbauer, Harald. <i>Inferring Recent Demography from Spatial Genetic Structure</i>. Institute of Science and Technology Austria, 2018, doi:<a href=\"https://doi.org/10.15479/AT:ISTA:th_963\">10.15479/AT:ISTA:th_963</a>.","apa":"Ringbauer, H. (2018). <i>Inferring recent demography from spatial genetic structure</i>. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/AT:ISTA:th_963\">https://doi.org/10.15479/AT:ISTA:th_963</a>"},"publisher":"Institute of Science and Technology Austria","file":[{"file_id":"5111","file_name":"IST-2018-963-v1+1_thesis.pdf","creator":"system","date_created":"2018-12-12T10:14:55Z","checksum":"8cc534d2b528ae017acf80874cce48c9","relation":"main_file","access_level":"open_access","file_size":5792935,"content_type":"application/pdf","date_updated":"2020-07-14T12:45:23Z"},{"date_created":"2019-04-05T09:30:12Z","file_id":"6224","file_name":"2018_thesis_ringbauer_source.zip","creator":"dernst","date_updated":"2020-07-14T12:45:23Z","content_type":"application/zip","access_level":"closed","file_size":113365,"checksum":"6af18d7e5a7e2728ceda2f41ee24f628","relation":"source_file"}],"pubrep_id":"963","article_processing_charge":"No","date_published":"2018-02-21T00:00:00Z","day":"21","file_date_updated":"2020-07-14T12:45:23Z","department":[{"_id":"NiBa"}],"related_material":{"record":[{"id":"563","relation":"part_of_dissertation","status":"public"},{"relation":"part_of_dissertation","status":"public","id":"1074"}]},"OA_place":"publisher","author":[{"orcid":"0000-0002-4884-9682","id":"417FCFF4-F248-11E8-B48F-1D18A9856A87","last_name":"Ringbauer","first_name":"Harald","full_name":"Ringbauer, Harald"}],"tmp":{"name":"Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)","short":"CC BY-NC (4.0)","legal_code_url":"https://creativecommons.org/licenses/by-nc/4.0/legalcode","image":"/images/cc_by_nc.png"},"user_id":"ba8df636-2132-11f1-aed0-ed93e2281fdd","ddc":["576"],"language":[{"iso":"eng"}],"publication_identifier":{"issn":["2663-337X"]},"alternative_title":["ISTA Thesis"],"month":"02","publist_id":"7713","type":"dissertation","has_accepted_license":"1","doi":"10.15479/AT:ISTA:th_963","year":"2018","publication_status":"published","page":"146","oa_version":"Published Version","date_updated":"2026-04-08T14:06:37Z","status":"public","_id":"200","title":"Inferring recent demography from spatial genetic structure","date_created":"2018-12-11T11:45:10Z","oa":1,"abstract":[{"text":"This thesis is concerned with the inference of current population structure based on geo-referenced genetic data. The underlying idea is that population structure affects its spatial genetic structure. Therefore, genotype information can be utilized to estimate important demographic parameters such as migration rates. These indirect estimates of population structure have become very attractive, as genotype data is now widely available. However, there also has been much concern about these approaches. Importantly, genetic structure can be influenced by many complex patterns, which often cannot be disentangled. Moreover, many methods merely fit heuristic patterns of genetic structure, and do not build upon population genetics theory. Here, I describe two novel inference methods that address these shortcomings. In Chapter 2, I introduce an inference scheme based on a new type of signal, identity by descent (IBD) blocks. Recently, it has become feasible to detect such long blocks of genome shared between pairs of samples. These blocks are direct traces of recent coalescence events. As such, they contain ample signal for inferring recent demography. I examine sharing of IBD blocks in two-dimensional populations with local migration. Using a diffusion approximation, I derive formulas for an isolation by distance pattern of long IBD blocks and show that sharing of long IBD blocks approaches rapid exponential decay for growing sample distance. I describe an inference scheme based on these results. It can robustly estimate the dispersal rate and population density, which is demonstrated on simulated data. I also show an application to estimate mean migration and the rate of recent population growth within Eastern Europe. Chapter 3 is about a novel method to estimate barriers to gene flow in a two dimensional population. This inference scheme utilizes geographically localized allele frequency fluctuations - a classical isolation by distance signal. The strength of these local fluctuations increases on average next to a barrier, and there is less correlation across it. I again use a framework of diffusion of ancestral lineages to model this effect, and provide an efficient numerical implementation to fit the results to geo-referenced biallelic SNP data. This inference scheme is able to robustly estimate strong barriers to gene flow, as tests on simulated data confirm.","lang":"eng"}],"degree_awarded":"PhD","supervisor":[{"id":"4880FE40-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-8548-5240","full_name":"Barton, Nicholas H","last_name":"Barton","first_name":"Nicholas H"}],"corr_author":"1"},{"user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","date_updated":"2025-04-15T07:17:08Z","related_material":{"record":[{"id":"316","relation":"used_in_publication","status":"public"}]},"department":[{"_id":"NiBa"},{"_id":"GaTk"}],"author":[{"first_name":"Katarína","last_name":"Bod'ová","full_name":"Bod'ová, Katarína","orcid":"0000-0002-7214-0171","id":"2BA24EA0-F248-11E8-B48F-1D18A9856A87"},{"id":"3C869AA0-F248-11E8-B48F-1D18A9856A87","full_name":"Priklopil, Tadeas","last_name":"Priklopil","first_name":"Tadeas"},{"first_name":"David","last_name":"Field","full_name":"Field, David","orcid":"0000-0002-4014-8478","id":"419049E2-F248-11E8-B48F-1D18A9856A87"},{"orcid":"0000-0002-8548-5240","id":"4880FE40-F248-11E8-B48F-1D18A9856A87","last_name":"Barton","first_name":"Nicholas H","full_name":"Barton, Nicholas H"},{"id":"2C78037E-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-6118-0541","full_name":"Pickup, Melinda","first_name":"Melinda","last_name":"Pickup"}],"oa_version":"Published Version","date_published":"2018-04-30T00:00:00Z","main_file_link":[{"open_access":"1","url":"https://doi.org/10.25386/genetics.6148304.v1"}],"day":"30","article_processing_charge":"No","year":"2018","publisher":"Genetics Society of America","citation":{"short":"K. Bodova, T. Priklopil, D. Field, N.H. Barton, M. Pickup, (2018).","ista":"Bodova K, Priklopil T, Field D, Barton NH, Pickup M. 2018. Supplemental material for Bodova et al., 2018, Genetics Society of America, <a href=\"https://doi.org/10.25386/genetics.6148304.v1\">10.25386/genetics.6148304.v1</a>.","ieee":"K. Bodova, T. Priklopil, D. Field, N. H. Barton, and M. Pickup, “Supplemental material for Bodova et al., 2018.” Genetics Society of America, 2018.","chicago":"Bodova, Katarina, Tadeas Priklopil, David Field, Nicholas H Barton, and Melinda Pickup. “Supplemental Material for Bodova et Al., 2018.” Genetics Society of America, 2018. <a href=\"https://doi.org/10.25386/genetics.6148304.v1\">https://doi.org/10.25386/genetics.6148304.v1</a>.","ama":"Bodova K, Priklopil T, Field D, Barton NH, Pickup M. Supplemental material for Bodova et al., 2018. 2018. doi:<a href=\"https://doi.org/10.25386/genetics.6148304.v1\">10.25386/genetics.6148304.v1</a>","apa":"Bodova, K., Priklopil, T., Field, D., Barton, N. H., &#38; Pickup, M. (2018). Supplemental material for Bodova et al., 2018. Genetics Society of America. <a href=\"https://doi.org/10.25386/genetics.6148304.v1\">https://doi.org/10.25386/genetics.6148304.v1</a>","mla":"Bodova, Katarina, et al. <i>Supplemental Material for Bodova et Al., 2018</i>. Genetics Society of America, 2018, doi:<a href=\"https://doi.org/10.25386/genetics.6148304.v1\">10.25386/genetics.6148304.v1</a>."},"doi":"10.25386/genetics.6148304.v1","type":"research_data_reference","abstract":[{"text":"File S1 contains figures that clarify the following features: (i) effect of population size on the average number/frequency of SI classes, (ii) changes in the minimal completeness deficit in time for a single class, and (iii) diversification diagrams for all studied pathways, including the summary figure for k = 8. File S2 contains the code required for a stochastic simulation of the SLF system with an example. This file also includes the output in the form of figures and tables.","lang":"eng"}],"month":"04","oa":1,"date_created":"2021-08-06T13:04:32Z","_id":"9813","status":"public","title":"Supplemental material for Bodova et al., 2018"},{"type":"research_data_reference","doi":"10.5061/dryad.72cg113","title":"Data from: Multiple chromosomal rearrangements in a hybrid zone between Littorina saxatilis ecotypes","status":"public","_id":"9837","month":"10","date_created":"2021-08-09T12:46:39Z","oa":1,"abstract":[{"lang":"eng","text":"Both classical and recent studies suggest that chromosomal inversion polymorphisms are important in adaptation and speciation. However, biases in discovery and reporting of inversions make it difficult to assess their prevalence and biological importance. Here, we use an approach based on linkage disequilibrium among markers genotyped for samples collected across a transect between contrasting habitats to detect chromosomal rearrangements de novo. We report 17 polymorphic rearrangements in a single locality for the coastal marine snail, Littorina saxatilis. Patterns of diversity in the field and of recombination in controlled crosses provide strong evidence that at least the majority of these rearrangements are inversions. Most show clinal changes in frequency between habitats, suggestive of divergent selection, but only one appears to be fixed for different arrangements in the two habitats. Consistent with widespread evidence for balancing selection on inversion polymorphisms, we argue that a combination of heterosis and divergent selection can explain the observed patterns and should be considered in other systems spanning environmental gradients."}],"oa_version":"Published Version","author":[{"full_name":"Faria, Rui","last_name":"Faria","first_name":"Rui"},{"full_name":"Chaube, Pragya","first_name":"Pragya","last_name":"Chaube"},{"last_name":"Morales","first_name":"Hernán E.","full_name":"Morales, Hernán E."},{"last_name":"Larsson","first_name":"Tomas","full_name":"Larsson, Tomas"},{"full_name":"Lemmon, Alan R.","first_name":"Alan R.","last_name":"Lemmon"},{"full_name":"Lemmon, Emily M.","last_name":"Lemmon","first_name":"Emily M."},{"full_name":"Rafajlović, Marina","last_name":"Rafajlović","first_name":"Marina"},{"full_name":"Panova, Marina","first_name":"Marina","last_name":"Panova"},{"last_name":"Ravinet","first_name":"Mark","full_name":"Ravinet, Mark"},{"last_name":"Johannesson","first_name":"Kerstin","full_name":"Johannesson, Kerstin"},{"orcid":"0000-0003-1050-4969","id":"3C147470-F248-11E8-B48F-1D18A9856A87","first_name":"Anja M","last_name":"Westram","full_name":"Westram, Anja M"},{"full_name":"Butlin, Roger K.","first_name":"Roger K.","last_name":"Butlin"}],"department":[{"_id":"NiBa"}],"related_material":{"record":[{"status":"public","relation":"used_in_publication","id":"6095"}]},"user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","date_updated":"2023-08-24T14:50:26Z","citation":{"ama":"Faria R, Chaube P, Morales HE, et al. Data from: Multiple chromosomal rearrangements in a hybrid zone between Littorina saxatilis ecotypes. 2018. doi:<a href=\"https://doi.org/10.5061/dryad.72cg113\">10.5061/dryad.72cg113</a>","ieee":"R. Faria <i>et al.</i>, “Data from: Multiple chromosomal rearrangements in a hybrid zone between Littorina saxatilis ecotypes.” Dryad, 2018.","ista":"Faria R, Chaube P, Morales HE, Larsson T, Lemmon AR, Lemmon EM, Rafajlović M, Panova M, Ravinet M, Johannesson K, Westram AM, Butlin RK. 2018. Data from: Multiple chromosomal rearrangements in a hybrid zone between Littorina saxatilis ecotypes, Dryad, <a href=\"https://doi.org/10.5061/dryad.72cg113\">10.5061/dryad.72cg113</a>.","chicago":"Faria, Rui, Pragya Chaube, Hernán E. Morales, Tomas Larsson, Alan R. Lemmon, Emily M. Lemmon, Marina Rafajlović, et al. “Data from: Multiple Chromosomal Rearrangements in a Hybrid Zone between Littorina Saxatilis Ecotypes.” Dryad, 2018. <a href=\"https://doi.org/10.5061/dryad.72cg113\">https://doi.org/10.5061/dryad.72cg113</a>.","short":"R. Faria, P. Chaube, H.E. Morales, T. Larsson, A.R. Lemmon, E.M. Lemmon, M. Rafajlović, M. Panova, M. Ravinet, K. Johannesson, A.M. Westram, R.K. Butlin, (2018).","mla":"Faria, Rui, et al. <i>Data from: Multiple Chromosomal Rearrangements in a Hybrid Zone between Littorina Saxatilis Ecotypes</i>. Dryad, 2018, doi:<a href=\"https://doi.org/10.5061/dryad.72cg113\">10.5061/dryad.72cg113</a>.","apa":"Faria, R., Chaube, P., Morales, H. E., Larsson, T., Lemmon, A. R., Lemmon, E. M., … Butlin, R. K. (2018). Data from: Multiple chromosomal rearrangements in a hybrid zone between Littorina saxatilis ecotypes. Dryad. <a href=\"https://doi.org/10.5061/dryad.72cg113\">https://doi.org/10.5061/dryad.72cg113</a>"},"publisher":"Dryad","year":"2018","article_processing_charge":"No","day":"09","date_published":"2018-10-09T00:00:00Z","main_file_link":[{"url":"https://doi.org/10.5061/dryad.72cg113","open_access":"1"}]},{"date_updated":"2025-04-15T08:17:50Z","user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","author":[{"full_name":"Payne, Pavel","last_name":"Payne","first_name":"Pavel","id":"35F78294-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-2711-9453"},{"full_name":"Geyrhofer, Lukas","first_name":"Lukas","last_name":"Geyrhofer"},{"orcid":"0000-0002-8548-5240","id":"4880FE40-F248-11E8-B48F-1D18A9856A87","first_name":"Nicholas H","last_name":"Barton","full_name":"Barton, Nicholas H"},{"first_name":"Jonathan P","last_name":"Bollback","full_name":"Bollback, Jonathan P","orcid":"0000-0002-4624-4612","id":"2C6FA9CC-F248-11E8-B48F-1D18A9856A87"}],"oa_version":"Published Version","related_material":{"record":[{"id":"423","relation":"used_in_publication","status":"public"}]},"department":[{"_id":"NiBa"},{"_id":"JoBo"}],"day":"12","date_published":"2018-03-12T00:00:00Z","main_file_link":[{"open_access":"1","url":"https://doi.org/10.5061/dryad.42n44"}],"article_processing_charge":"No","publisher":"Dryad","citation":{"ama":"Payne P, Geyrhofer L, Barton NH, Bollback JP. Data from: CRISPR-based herd immunity limits phage epidemics in bacterial populations. 2018. doi:<a href=\"https://doi.org/10.5061/dryad.42n44\">10.5061/dryad.42n44</a>","chicago":"Payne, Pavel, Lukas Geyrhofer, Nicholas H Barton, and Jonathan P Bollback. “Data from: CRISPR-Based Herd Immunity Limits Phage Epidemics in Bacterial Populations.” Dryad, 2018. <a href=\"https://doi.org/10.5061/dryad.42n44\">https://doi.org/10.5061/dryad.42n44</a>.","ieee":"P. Payne, L. Geyrhofer, N. H. Barton, and J. P. Bollback, “Data from: CRISPR-based herd immunity limits phage epidemics in bacterial populations.” Dryad, 2018.","ista":"Payne P, Geyrhofer L, Barton NH, Bollback JP. 2018. Data from: CRISPR-based herd immunity limits phage epidemics in bacterial populations, Dryad, <a href=\"https://doi.org/10.5061/dryad.42n44\">10.5061/dryad.42n44</a>.","short":"P. Payne, L. Geyrhofer, N.H. Barton, J.P. Bollback, (2018).","mla":"Payne, Pavel, et al. <i>Data from: CRISPR-Based Herd Immunity Limits Phage Epidemics in Bacterial Populations</i>. Dryad, 2018, doi:<a href=\"https://doi.org/10.5061/dryad.42n44\">10.5061/dryad.42n44</a>.","apa":"Payne, P., Geyrhofer, L., Barton, N. H., &#38; Bollback, J. P. (2018). Data from: CRISPR-based herd immunity limits phage epidemics in bacterial populations. Dryad. <a href=\"https://doi.org/10.5061/dryad.42n44\">https://doi.org/10.5061/dryad.42n44</a>"},"year":"2018","doi":"10.5061/dryad.42n44","type":"research_data_reference","abstract":[{"lang":"eng","text":"Herd immunity, a process in which resistant individuals limit the spread of a pathogen among susceptible hosts has been extensively studied in eukaryotes. Even though bacteria have evolved multiple immune systems against their phage pathogens, herd immunity in bacteria remains unexplored. Here we experimentally demonstrate that herd immunity arises during phage epidemics in structured and unstructured Escherichia coli populations consisting of differing frequencies of susceptible and resistant cells harboring CRISPR immunity. In addition, we develop a mathematical model that quantifies how herd immunity is affected by spatial population structure, bacterial growth rate, and phage replication rate. Using our model we infer a general epidemiological rule describing the relative speed of an epidemic in partially resistant spatially structured populations. Our experimental and theoretical findings indicate that herd immunity may be important in bacterial communities, allowing for stable coexistence of bacteria and their phages and the maintenance of polymorphism in bacterial immunity."}],"month":"03","oa":1,"date_created":"2021-08-09T13:10:02Z","title":"Data from: CRISPR-based herd immunity limits phage epidemics in bacterial populations","_id":"9840","status":"public"},{"oa":1,"date_created":"2018-12-11T11:48:09Z","abstract":[{"lang":"eng","text":"Escaping local optima is one of the major obstacles to function optimisation. Using the metaphor of a fitness landscape, local optima correspond to hills separated by fitness valleys that have to be overcome. We define a class of fitness valleys of tunable difficulty by considering their length, representing the Hamming path between the two optima and their depth, the drop in fitness. For this function class we present a runtime comparison between stochastic search algorithms using different search strategies. The (1+1) EA is a simple and well-studied evolutionary algorithm that has to jump across the valley to a point of higher fitness because it does not accept worsening moves (elitism). In contrast, the Metropolis algorithm and the Strong Selection Weak Mutation (SSWM) algorithm, a famous process in population genetics, are both able to cross the fitness valley by accepting worsening moves. We show that the runtime of the (1+1) EA depends critically on the length of the valley while the runtimes of the non-elitist algorithms depend crucially on the depth of the valley. Moreover, we show that both SSWM and Metropolis can also efficiently optimise a rugged function consisting of consecutive valleys."}],"title":"How to escape local optima in black box optimisation when non elitism outperforms elitism","status":"public","_id":"723","isi":1,"publication_status":"published","page":"1604 - 1633","project":[{"_id":"25B1EC9E-B435-11E9-9278-68D0E5697425","call_identifier":"FP7","name":"Speed of Adaptation in Population Genetics and Evolutionary Computation","grant_number":"618091"}],"year":"2018","date_updated":"2025-04-15T08:22:22Z","scopus_import":"1","oa_version":"Published Version","month":"05","publist_id":"6957","quality_controlled":"1","volume":80,"has_accepted_license":"1","doi":"10.1007/s00453-017-0369-2","external_id":{"isi":["000428239300010"]},"type":"journal_article","file_date_updated":"2020-07-14T12:47:54Z","article_processing_charge":"No","date_published":"2018-05-01T00:00:00Z","day":"01","citation":{"ieee":"P. Oliveto, T. Paixao, J. Pérez Heredia, D. Sudholt, and B. Trubenova, “How to escape local optima in black box optimisation when non elitism outperforms elitism,” <i>Algorithmica</i>, vol. 80, no. 5. Springer, pp. 1604–1633, 2018.","ista":"Oliveto P, Paixao T, Pérez Heredia J, Sudholt D, Trubenova B. 2018. How to escape local optima in black box optimisation when non elitism outperforms elitism. Algorithmica. 80(5), 1604–1633.","chicago":"Oliveto, Pietro, Tiago Paixao, Jorge Pérez Heredia, Dirk Sudholt, and Barbora Trubenova. “How to Escape Local Optima in Black Box Optimisation When Non Elitism Outperforms Elitism.” <i>Algorithmica</i>. Springer, 2018. <a href=\"https://doi.org/10.1007/s00453-017-0369-2\">https://doi.org/10.1007/s00453-017-0369-2</a>.","ama":"Oliveto P, Paixao T, Pérez Heredia J, Sudholt D, Trubenova B. How to escape local optima in black box optimisation when non elitism outperforms elitism. <i>Algorithmica</i>. 2018;80(5):1604-1633. doi:<a href=\"https://doi.org/10.1007/s00453-017-0369-2\">10.1007/s00453-017-0369-2</a>","short":"P. Oliveto, T. Paixao, J. Pérez Heredia, D. Sudholt, B. Trubenova, Algorithmica 80 (2018) 1604–1633.","apa":"Oliveto, P., Paixao, T., Pérez Heredia, J., Sudholt, D., &#38; Trubenova, B. (2018). How to escape local optima in black box optimisation when non elitism outperforms elitism. <i>Algorithmica</i>. Springer. <a href=\"https://doi.org/10.1007/s00453-017-0369-2\">https://doi.org/10.1007/s00453-017-0369-2</a>","mla":"Oliveto, Pietro, et al. “How to Escape Local Optima in Black Box Optimisation When Non Elitism Outperforms Elitism.” <i>Algorithmica</i>, vol. 80, no. 5, Springer, 2018, pp. 1604–33, doi:<a href=\"https://doi.org/10.1007/s00453-017-0369-2\">10.1007/s00453-017-0369-2</a>."},"file":[{"access_level":"open_access","file_size":691245,"content_type":"application/pdf","date_updated":"2020-07-14T12:47:54Z","relation":"main_file","checksum":"7d92f5d7be81e387edeec4f06442791c","date_created":"2018-12-12T10:08:14Z","file_name":"IST-2018-1014-v1+1_2018_Paixao_Escape.pdf","creator":"system","file_id":"4674"}],"publisher":"Springer","pubrep_id":"1014","intvolume":"        80","issue":"5","ddc":["576"],"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","publication":"Algorithmica","language":[{"iso":"eng"}],"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"ec_funded":1,"author":[{"last_name":"Oliveto","first_name":"Pietro","full_name":"Oliveto, Pietro"},{"id":"2C5658E6-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-2361-3953","full_name":"Paixao, Tiago","first_name":"Tiago","last_name":"Paixao"},{"full_name":"Pérez Heredia, Jorge","last_name":"Pérez Heredia","first_name":"Jorge"},{"full_name":"Sudholt, Dirk","last_name":"Sudholt","first_name":"Dirk"},{"first_name":"Barbora","last_name":"Trubenova","full_name":"Trubenova, Barbora","orcid":"0000-0002-6873-2967","id":"42302D54-F248-11E8-B48F-1D18A9856A87"}],"department":[{"_id":"NiBa"},{"_id":"CaGu"}]},{"year":"2018","publication_status":"published","scopus_import":"1","oa_version":"Published Version","date_updated":"2025-07-10T11:52:27Z","title":"Is the sky the limit? On the expansion threshold of a species’ range","_id":"315","status":"public","abstract":[{"text":"More than 100 years after Grigg’s influential analysis of species’ borders, the causes of limits to species’ ranges still represent a puzzle that has never been understood with clarity. The topic has become especially important recently as many scientists have become interested in the potential for species’ ranges to shift in response to climate change—and yet nearly all of those studies fail to recognise or incorporate evolutionary genetics in a way that relates to theoretical developments. I show that range margins can be understood based on just two measurable parameters: (i) the fitness cost of dispersal—a measure of environmental heterogeneity—and (ii) the strength of genetic drift, which reduces genetic diversity. Together, these two parameters define an ‘expansion threshold’: adaptation fails when genetic drift reduces genetic diversity below that required for adaptation to a heterogeneous environment. When the key parameters drop below this expansion threshold locally, a sharp range margin forms. When they drop below this threshold throughout the species’ range, adaptation collapses everywhere, resulting in either extinction or formation of a fragmented metapopulation. Because the effects of dispersal differ fundamentally with dimension, the second parameter—the strength of genetic drift—is qualitatively different compared to a linear habitat. In two-dimensional habitats, genetic drift becomes effectively independent of selection. It decreases with ‘neighbourhood size’—the number of individuals accessible by dispersal within one generation. Moreover, in contrast to earlier predictions, which neglected evolution of genetic variance and/or stochasticity in two dimensions, dispersal into small marginal populations aids adaptation. This is because the reduction of both genetic and demographic stochasticity has a stronger effect than the cost of dispersal through increased maladaptation. The expansion threshold thus provides a novel, theoretically justified, and testable prediction for formation of the range margin and collapse of the species’ range.","lang":"eng"}],"date_created":"2018-12-11T11:45:46Z","oa":1,"publisher":"Public Library of Science","file":[{"relation":"main_file","checksum":"908c52751bba30c55ed36789e5e4c84d","content_type":"application/pdf","date_updated":"2020-07-14T12:46:01Z","access_level":"open_access","file_size":6968201,"file_id":"5870","file_name":"2017_PLOS_Polechova.pdf","creator":"dernst","date_created":"2019-01-22T08:30:03Z"}],"citation":{"short":"J. Polechova, PLoS Biology 16 (2018).","ieee":"J. Polechova, “Is the sky the limit? On the expansion threshold of a species’ range,” <i>PLoS Biology</i>, vol. 16, no. 6. Public Library of Science, 2018.","ista":"Polechova J. 2018. Is the sky the limit? On the expansion threshold of a species’ range. PLoS Biology. 16(6), e2005372.","chicago":"Polechova, Jitka. “Is the Sky the Limit? On the Expansion Threshold of a Species’ Range.” <i>PLoS Biology</i>. Public Library of Science, 2018. <a href=\"https://doi.org/10.1371/journal.pbio.2005372\">https://doi.org/10.1371/journal.pbio.2005372</a>.","ama":"Polechova J. Is the sky the limit? On the expansion threshold of a species’ range. <i>PLoS Biology</i>. 2018;16(6). doi:<a href=\"https://doi.org/10.1371/journal.pbio.2005372\">10.1371/journal.pbio.2005372</a>","apa":"Polechova, J. (2018). Is the sky the limit? On the expansion threshold of a species’ range. <i>PLoS Biology</i>. Public Library of Science. <a href=\"https://doi.org/10.1371/journal.pbio.2005372\">https://doi.org/10.1371/journal.pbio.2005372</a>","mla":"Polechova, Jitka. “Is the Sky the Limit? On the Expansion Threshold of a Species’ Range.” <i>PLoS Biology</i>, vol. 16, no. 6, e2005372, Public Library of Science, 2018, doi:<a href=\"https://doi.org/10.1371/journal.pbio.2005372\">10.1371/journal.pbio.2005372</a>."},"issue":"6","intvolume":"        16","article_number":"e2005372","file_date_updated":"2020-07-14T12:46:01Z","day":"15","date_published":"2018-06-15T00:00:00Z","article_processing_charge":"No","author":[{"first_name":"Jitka","last_name":"Polechova","full_name":"Polechova, Jitka","orcid":"0000-0003-0951-3112","id":"3BBFB084-F248-11E8-B48F-1D18A9856A87"}],"related_material":{"record":[{"status":"public","relation":"research_data","id":"9839"}]},"department":[{"_id":"NiBa"}],"language":[{"iso":"eng"}],"publication":"PLoS Biology","ddc":["576"],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"publication_identifier":{"issn":["1544-9173"]},"quality_controlled":"1","publist_id":"7550","month":"06","type":"journal_article","doi":"10.1371/journal.pbio.2005372","has_accepted_license":"1","volume":16},{"language":[{"iso":"eng"}],"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","publication":"Genetics","ec_funded":1,"author":[{"full_name":"Bodova, Katarina","first_name":"Katarina","last_name":"Bodova","id":"2BA24EA0-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-7214-0171"},{"full_name":"Priklopil, Tadeas","last_name":"Priklopil","first_name":"Tadeas","id":"3C869AA0-F248-11E8-B48F-1D18A9856A87"},{"id":"419049E2-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-4014-8478","full_name":"Field, David","last_name":"Field","first_name":"David"},{"first_name":"Nicholas H","last_name":"Barton","full_name":"Barton, Nicholas H","orcid":"0000-0002-8548-5240","id":"4880FE40-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Pickup, Melinda","first_name":"Melinda","last_name":"Pickup","id":"2C78037E-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-6118-0541"}],"department":[{"_id":"NiBa"},{"_id":"GaTk"}],"related_material":{"link":[{"relation":"press_release","url":"https://ist.ac.at/en/news/recognizing-others-but-not-yourself-new-insights-into-the-evolution-of-plant-mating/","description":"News on IST Homepage"}],"record":[{"status":"public","relation":"research_data","id":"9813"}]},"article_processing_charge":"No","day":"01","date_published":"2018-07-01T00:00:00Z","main_file_link":[{"open_access":"1","url":"https://www.biorxiv.org/node/80098.abstract"}],"citation":{"mla":"Bodova, Katarina, et al. “Evolutionary Pathways for the Generation of New Self-Incompatibility Haplotypes in a Non-Self Recognition System.” <i>Genetics</i>, vol. 209, no. 3, Genetics Society of America, 2018, pp. 861–83, doi:<a href=\"https://doi.org/10.1534/genetics.118.300748\">10.1534/genetics.118.300748</a>.","apa":"Bodova, K., Priklopil, T., Field, D., Barton, N. H., &#38; Pickup, M. (2018). Evolutionary pathways for the generation of new self-incompatibility haplotypes in a non-self recognition system. <i>Genetics</i>. Genetics Society of America. <a href=\"https://doi.org/10.1534/genetics.118.300748\">https://doi.org/10.1534/genetics.118.300748</a>","ama":"Bodova K, Priklopil T, Field D, Barton NH, Pickup M. Evolutionary pathways for the generation of new self-incompatibility haplotypes in a non-self recognition system. <i>Genetics</i>. 2018;209(3):861-883. doi:<a href=\"https://doi.org/10.1534/genetics.118.300748\">10.1534/genetics.118.300748</a>","chicago":"Bodova, Katarina, Tadeas Priklopil, David Field, Nicholas H Barton, and Melinda Pickup. “Evolutionary Pathways for the Generation of New Self-Incompatibility Haplotypes in a Non-Self Recognition System.” <i>Genetics</i>. Genetics Society of America, 2018. <a href=\"https://doi.org/10.1534/genetics.118.300748\">https://doi.org/10.1534/genetics.118.300748</a>.","ieee":"K. Bodova, T. Priklopil, D. Field, N. H. Barton, and M. Pickup, “Evolutionary pathways for the generation of new self-incompatibility haplotypes in a non-self recognition system,” <i>Genetics</i>, vol. 209, no. 3. Genetics Society of America, pp. 861–883, 2018.","ista":"Bodova K, Priklopil T, Field D, Barton NH, Pickup M. 2018. Evolutionary pathways for the generation of new self-incompatibility haplotypes in a non-self recognition system. Genetics. 209(3), 861–883.","short":"K. Bodova, T. Priklopil, D. Field, N.H. Barton, M. Pickup, Genetics 209 (2018) 861–883."},"publisher":"Genetics Society of America","intvolume":"       209","issue":"3","volume":209,"doi":"10.1534/genetics.118.300748","external_id":{"isi":["000437171700017"]},"type":"journal_article","month":"07","quality_controlled":"1","article_type":"original","date_updated":"2025-04-15T06:50:00Z","scopus_import":"1","oa_version":"Preprint","publication_status":"published","page":"861-883","project":[{"_id":"25B36484-B435-11E9-9278-68D0E5697425","call_identifier":"FP7","name":"Mating system and the evolutionary dynamics of hybrid zones","grant_number":"329960"},{"name":"Limits to selection in biology and in evolutionary computation","grant_number":"250152","_id":"25B07788-B435-11E9-9278-68D0E5697425","call_identifier":"FP7"},{"call_identifier":"FP7","_id":"25681D80-B435-11E9-9278-68D0E5697425","grant_number":"291734","name":"International IST Postdoc Fellowship Programme"}],"year":"2018","isi":1,"date_created":"2018-12-11T11:45:47Z","oa":1,"abstract":[{"text":"Self-incompatibility (SI) is a genetically based recognition system that functions to prevent self-fertilization and mating among related plants. An enduring puzzle in SI is how the high diversity observed in nature arises and is maintained. Based on the underlying recognition mechanism, SI can be classified into two main groups: self- and non-self recognition. Most work has focused on diversification within self-recognition systems despite expected differences between the two groups in the evolutionary pathways and outcomes of diversification. Here, we use a deterministic population genetic model and stochastic simulations to investigate how novel S-haplotypes evolve in a gametophytic non-self recognition (SRNase/S Locus F-box (SLF)) SI system. For this model the pathways for diversification involve either the maintenance or breakdown of SI and can vary in the order of mutations of the female (SRNase) and male (SLF) components. We show analytically that diversification can occur with high inbreeding depression and self-pollination, but this varies with evolutionary pathway and level of completeness (which determines the number of potential mating partners in the population), and in general is more likely for lower haplotype number. The conditions for diversification are broader in stochastic simulations of finite population size. However, the number of haplotypes observed under high inbreeding and moderate to high self-pollination is less than that commonly observed in nature. Diversification was observed through pathways that maintain SI as well as through self-compatible intermediates. Yet the lifespan of diversified haplotypes was sensitive to their level of completeness. By examining diversification in a non-self recognition SI system, this model extends our understanding of the evolution and maintenance of haplotype diversity observed in a self recognition system common in flowering plants.","lang":"eng"}],"title":"Evolutionary pathways for the generation of new self-incompatibility haplotypes in a non-self recognition system","_id":"316","status":"public"},{"oa_version":"Published Version","scopus_import":"1","date_updated":"2023-10-17T12:24:43Z","year":"2018","pmid":1,"publication_status":"published","isi":1,"_id":"33","status":"public","title":"Can secondary contact following range expansion be distinguished from barriers to gene flow?","abstract":[{"text":"Secondary contact is the reestablishment of gene flow between sister populations that have diverged. For instance, at the end of the Quaternary glaciations in Europe, secondary contact occurred during the northward expansion of the populations which had found refugia in the southern peninsulas. With the advent of multi-locus markers, secondary contact can be investigated using various molecular signatures including gradients of allele frequency, admixture clines, and local increase of genetic differentiation. We use coalescent simulations to investigate if molecular data provide enough information to distinguish between secondary contact following range expansion and an alternative evolutionary scenario consisting of a barrier to gene flow in an isolation-by-distance model. We find that an excess of linkage disequilibrium and of genetic diversity at the suture zone is a unique signature of secondary contact. We also find that the directionality index ψ, which was proposed to study range expansion, is informative to distinguish between the two hypotheses. However, although evidence for secondary contact is usually conveyed by statistics related to admixture coefficients, we find that they can be confounded by isolation-by-distance. We recommend to account for the spatial repartition of individuals when investigating secondary contact in order to better reflect the complex spatio-temporal evolution of populations and species.","lang":"eng"}],"oa":1,"date_created":"2018-12-11T11:44:16Z","acknowledgement":"Johanna Bertl was supported by the Vienna Graduate School of Population Genetics (Austrian Science Fund (FWF): W1225-B20) and worked on this project while employed at the Department of Statistics and Operations Research, University of Vienna, Austria. This article was developed in the framework of the Grenoble Alpes Data Institute, which is supported by the French National Research Agency under the “Investissments d’avenir” program (ANR-15-IDEX-02).","department":[{"_id":"NiBa"}],"author":[{"last_name":"Bertl","first_name":"Johanna","full_name":"Bertl, Johanna"},{"last_name":"Ringbauer","first_name":"Harald","full_name":"Ringbauer, Harald","orcid":"0000-0002-4884-9682","id":"417FCFF4-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Blum, Michaël","first_name":"Michaël","last_name":"Blum"}],"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"publication":"PeerJ","language":[{"iso":"eng"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","ddc":["576"],"issue":"10","intvolume":"      2018","file":[{"date_created":"2018-12-17T10:46:06Z","file_id":"5692","creator":"dernst","file_name":"2018_PeerJ_Bertl.pdf","access_level":"open_access","file_size":1328344,"content_type":"application/pdf","date_updated":"2020-07-14T12:46:06Z","relation":"main_file","checksum":"3334886c4b39678db4c4b74299ca14ba"}],"publisher":"PeerJ","citation":{"mla":"Bertl, Johanna, et al. “Can Secondary Contact Following Range Expansion Be Distinguished from Barriers to Gene Flow?” <i>PeerJ</i>, vol. 2018, no. 10, e5325, PeerJ, 2018, doi:<a href=\"https://doi.org/10.7717/peerj.5325\">10.7717/peerj.5325</a>.","apa":"Bertl, J., Ringbauer, H., &#38; Blum, M. (2018). Can secondary contact following range expansion be distinguished from barriers to gene flow? <i>PeerJ</i>. PeerJ. <a href=\"https://doi.org/10.7717/peerj.5325\">https://doi.org/10.7717/peerj.5325</a>","ama":"Bertl J, Ringbauer H, Blum M. Can secondary contact following range expansion be distinguished from barriers to gene flow? <i>PeerJ</i>. 2018;2018(10). doi:<a href=\"https://doi.org/10.7717/peerj.5325\">10.7717/peerj.5325</a>","ieee":"J. Bertl, H. Ringbauer, and M. Blum, “Can secondary contact following range expansion be distinguished from barriers to gene flow?,” <i>PeerJ</i>, vol. 2018, no. 10. PeerJ, 2018.","ista":"Bertl J, Ringbauer H, Blum M. 2018. Can secondary contact following range expansion be distinguished from barriers to gene flow? PeerJ. 2018(10), e5325.","chicago":"Bertl, Johanna, Harald Ringbauer, and Michaël Blum. “Can Secondary Contact Following Range Expansion Be Distinguished from Barriers to Gene Flow?” <i>PeerJ</i>. PeerJ, 2018. <a href=\"https://doi.org/10.7717/peerj.5325\">https://doi.org/10.7717/peerj.5325</a>.","short":"J. Bertl, H. Ringbauer, M. Blum, PeerJ 2018 (2018)."},"date_published":"2018-10-01T00:00:00Z","day":"01","article_processing_charge":"No","article_number":"e5325","file_date_updated":"2020-07-14T12:46:06Z","type":"journal_article","external_id":{"isi":["000447204400001"],"pmid":["30294507"]},"doi":"10.7717/peerj.5325","volume":2018,"has_accepted_license":"1","quality_controlled":"1","publist_id":"8022","month":"10"},{"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","ddc":["570"],"language":[{"iso":"eng"}],"publication":"PNAS","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode","short":"CC BY-NC-ND (4.0)","image":"/images/cc_by_nc_nd.png","name":"Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)"},"author":[{"first_name":"Hugo","last_name":"Tavares","full_name":"Tavares, Hugo"},{"full_name":"Whitley, Annabel","first_name":"Annabel","last_name":"Whitley"},{"first_name":"David","last_name":"Field","full_name":"Field, David","orcid":"0000-0002-4014-8478","id":"419049E2-F248-11E8-B48F-1D18A9856A87"},{"last_name":"Bradley","first_name":"Desmond","full_name":"Bradley, Desmond"},{"full_name":"Couchman, Matthew","last_name":"Couchman","first_name":"Matthew"},{"last_name":"Copsey","first_name":"Lucy","full_name":"Copsey, Lucy"},{"full_name":"Elleouet, Joane","first_name":"Joane","last_name":"Elleouet"},{"first_name":"Monique","last_name":"Burrus","full_name":"Burrus, Monique"},{"first_name":"Christophe","last_name":"Andalo","full_name":"Andalo, Christophe"},{"full_name":"Li, Miaomiao","first_name":"Miaomiao","last_name":"Li"},{"full_name":"Li, Qun","last_name":"Li","first_name":"Qun"},{"full_name":"Xue, Yongbiao","first_name":"Yongbiao","last_name":"Xue"},{"full_name":"Rebocho, Alexandra B","first_name":"Alexandra B","last_name":"Rebocho"},{"full_name":"Barton, Nicholas H","last_name":"Barton","first_name":"Nicholas H","id":"4880FE40-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-8548-5240"},{"full_name":"Coen, Enrico","last_name":"Coen","first_name":"Enrico"}],"acknowledgement":" ERC Grant 201252 (to N.H.B.)","department":[{"_id":"NiBa"}],"file_date_updated":"2020-07-14T12:46:16Z","date_published":"2018-10-23T00:00:00Z","day":"23","article_processing_charge":"No","publisher":"National Academy of Sciences","file":[{"date_updated":"2020-07-14T12:46:16Z","content_type":"application/pdf","access_level":"open_access","file_size":1911302,"relation":"main_file","checksum":"d2305d0cc81dbbe4c1c677d64ad6f6d1","date_created":"2018-12-17T08:44:03Z","file_id":"5683","file_name":"11006.full.pdf","creator":"dernst"}],"citation":{"apa":"Tavares, H., Whitley, A., Field, D., Bradley, D., Couchman, M., Copsey, L., … Coen, E. (2018). Selection and gene flow shape genomic islands that control floral guides. <i>PNAS</i>. National Academy of Sciences. <a href=\"https://doi.org/10.1073/pnas.1801832115\">https://doi.org/10.1073/pnas.1801832115</a>","mla":"Tavares, Hugo, et al. “Selection and Gene Flow Shape Genomic Islands That Control Floral Guides.” <i>PNAS</i>, vol. 115, no. 43, National Academy of Sciences, 2018, pp. 11006–11, doi:<a href=\"https://doi.org/10.1073/pnas.1801832115\">10.1073/pnas.1801832115</a>.","chicago":"Tavares, Hugo, Annabel Whitley, David Field, Desmond Bradley, Matthew Couchman, Lucy Copsey, Joane Elleouet, et al. “Selection and Gene Flow Shape Genomic Islands That Control Floral Guides.” <i>PNAS</i>. National Academy of Sciences, 2018. <a href=\"https://doi.org/10.1073/pnas.1801832115\">https://doi.org/10.1073/pnas.1801832115</a>.","ieee":"H. Tavares <i>et al.</i>, “Selection and gene flow shape genomic islands that control floral guides,” <i>PNAS</i>, vol. 115, no. 43. National Academy of Sciences, pp. 11006–11011, 2018.","ista":"Tavares H, Whitley A, Field D, Bradley D, Couchman M, Copsey L, Elleouet J, Burrus M, Andalo C, Li M, Li Q, Xue Y, Rebocho AB, Barton NH, Coen E. 2018. Selection and gene flow shape genomic islands that control floral guides. PNAS. 115(43), 11006–11011.","ama":"Tavares H, Whitley A, Field D, et al. Selection and gene flow shape genomic islands that control floral guides. <i>PNAS</i>. 2018;115(43):11006-11011. doi:<a href=\"https://doi.org/10.1073/pnas.1801832115\">10.1073/pnas.1801832115</a>","short":"H. Tavares, A. Whitley, D. Field, D. Bradley, M. Couchman, L. Copsey, J. Elleouet, M. Burrus, C. Andalo, M. Li, Q. Li, Y. Xue, A.B. Rebocho, N.H. Barton, E. Coen, PNAS 115 (2018) 11006–11011."},"issue":"43","intvolume":"       115","doi":"10.1073/pnas.1801832115","has_accepted_license":"1","volume":115,"type":"journal_article","external_id":{"isi":["000448040500065"],"pmid":["30297406"]},"quality_controlled":"1","publist_id":"8017","month":"10","publication_identifier":{"issn":["0027-8424"]},"date_updated":"2025-07-10T11:52:32Z","oa_version":"Published Version","scopus_import":"1","page":"11006 - 11011","publication_status":"published","pmid":1,"year":"2018","isi":1,"abstract":[{"lang":"eng","text":"Genomes of closely-related species or populations often display localized regions of enhanced relative sequence divergence, termed genomic islands. It has been proposed that these islands arise through selective sweeps and/or barriers to gene flow. Here, we genetically dissect a genomic island that controls flower color pattern differences between two subspecies of Antirrhinum majus, A.m.striatum and A.m.pseudomajus, and relate it to clinal variation across a natural hybrid zone. We show that selective sweeps likely raised relative divergence at two tightly-linked MYB-like transcription factors, leading to distinct flower patterns in the two subspecies. The two patterns provide alternate floral guides and create a strong barrier to gene flow where populations come into contact. This barrier affects the selected flower color genes and tightlylinked loci, but does not extend outside of this domain, allowing gene flow to lower relative divergence for the rest of the chromosome. Thus, both selective sweeps and barriers to gene flow play a role in shaping genomic islands: sweeps cause elevation in relative divergence, while heterogeneous gene flow flattens the surrounding \"sea,\" making the island of divergence stand out. By showing how selective sweeps establish alternative adaptive phenotypes that lead to barriers to gene flow, our study sheds light on possible mechanisms leading to reproductive isolation and speciation."}],"date_created":"2018-12-11T11:44:18Z","oa":1,"title":"Selection and gene flow shape genomic islands that control floral guides","status":"public","_id":"38"},{"language":[{"iso":"eng"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publication":"Genetics","author":[{"first_name":"Himani","last_name":"Sachdeva","full_name":"Sachdeva, Himani","id":"42377A0A-F248-11E8-B48F-1D18A9856A87"},{"id":"4880FE40-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-8548-5240","full_name":"Barton, Nicholas H","first_name":"Nicholas H","last_name":"Barton"}],"department":[{"_id":"NiBa"}],"article_processing_charge":"No","date_published":"2018-12-04T00:00:00Z","main_file_link":[{"open_access":"1","url":"https://www.biorxiv.org/content/10.1101/379578v1"}],"day":"04","citation":{"mla":"Sachdeva, Himani, and Nicholas H. Barton. “Replicability of Introgression under Linked, Polygenic Selection.” <i>Genetics</i>, vol. 210, no. 4, Genetics Society of America, 2018, pp. 1411–27, doi:<a href=\"https://doi.org/10.1534/genetics.118.301429\">10.1534/genetics.118.301429</a>.","apa":"Sachdeva, H., &#38; Barton, N. H. (2018). Replicability of introgression under linked, polygenic selection. <i>Genetics</i>. Genetics Society of America. <a href=\"https://doi.org/10.1534/genetics.118.301429\">https://doi.org/10.1534/genetics.118.301429</a>","short":"H. Sachdeva, N.H. Barton, Genetics 210 (2018) 1411–1427.","ama":"Sachdeva H, Barton NH. Replicability of introgression under linked, polygenic selection. <i>Genetics</i>. 2018;210(4):1411-1427. doi:<a href=\"https://doi.org/10.1534/genetics.118.301429\">10.1534/genetics.118.301429</a>","ieee":"H. Sachdeva and N. H. Barton, “Replicability of introgression under linked, polygenic selection,” <i>Genetics</i>, vol. 210, no. 4. Genetics Society of America, pp. 1411–1427, 2018.","chicago":"Sachdeva, Himani, and Nicholas H Barton. “Replicability of Introgression under Linked, Polygenic Selection.” <i>Genetics</i>. Genetics Society of America, 2018. <a href=\"https://doi.org/10.1534/genetics.118.301429\">https://doi.org/10.1534/genetics.118.301429</a>.","ista":"Sachdeva H, Barton NH. 2018. Replicability of introgression under linked, polygenic selection. Genetics. 210(4), 1411–1427."},"publisher":"Genetics Society of America","intvolume":"       210","issue":"4","volume":210,"doi":"10.1534/genetics.118.301429","external_id":{"isi":["000452315900021"]},"type":"journal_article","month":"12","quality_controlled":"1","article_type":"original","publication_identifier":{"issn":["0016-6731"]},"date_updated":"2025-07-10T11:52:33Z","oa_version":"Preprint","scopus_import":"1","page":"1411-1427","publication_status":"published","year":"2018","isi":1,"oa":1,"date_created":"2018-12-11T11:44:18Z","abstract":[{"lang":"eng","text":"We study how a block of genome with a large number of weakly selected loci introgresses under directional selection into a genetically homogeneous population. We derive exact expressions for the expected rate of growth of any fragment of the introduced block during the initial phase of introgression, and show that the growth rate of a single-locus variant is largely insensitive to its own additive effect, but depends instead on the combined effect of all loci within a characteristic linkage scale. The expected growth rate of a fragment is highly correlated with its long-term introgression probability in populations of moderate size, and can hence identify variants that are likely to introgress across replicate populations. We clarify how the introgression probability of an individual variant is determined by the interplay between hitchhiking with relatively large fragments during the early phase of introgression and selection on fine-scale variation within these, which at longer times results in differential introgression probabilities for beneficial and deleterious loci within successful fragments. By simulating individuals, we also investigate how introgression probabilities at individual loci depend on the variance of fitness effects, the net fitness of the introduced block, and the size of the recipient population, and how this shapes the net advance under selection. Our work suggests that even highly replicable substitutions may be associated with a range of selective effects, which makes it challenging to fine map the causal loci that underlie polygenic adaptation."}],"title":"Replicability of introgression under linked, polygenic selection","_id":"39","status":"public"},{"abstract":[{"lang":"eng","text":"Hanemaaijer et al. (Molecular Ecology, 27, 2018) describe the genetic consequences of the introgression of an insecticide resistance allele into a mosquito population. Linked alleles initially increased, but many of these later declined. It is hard to determine whether this decline was due to counter‐selection, rather than simply to chance."}],"date_created":"2018-12-11T11:44:18Z","oa":1,"status":"public","_id":"40","title":"The consequences of an introgression event","corr_author":"1","isi":1,"publication_status":"published","page":"4973-4975","year":"2018","pmid":1,"date_updated":"2025-07-10T11:52:34Z","scopus_import":"1","oa_version":"Published Version","article_type":"letter_note","quality_controlled":"1","month":"12","publist_id":"8014","publication_identifier":{"issn":["1365-294X"]},"doi":"10.1111/mec.14950","has_accepted_license":"1","volume":27,"type":"journal_article","external_id":{"isi":["000454600500001"],"pmid":["30599087"]},"day":"31","date_published":"2018-12-31T00:00:00Z","article_processing_charge":"Yes (via OA deal)","file_date_updated":"2020-07-14T12:46:22Z","issue":"24","intvolume":"        27","publisher":"Wiley","file":[{"relation":"main_file","file_size":295452,"access_level":"open_access","content_type":"application/pdf","date_updated":"2020-07-14T12:46:22Z","creator":"apreinsp","file_name":"2018_MolecularEcology_BartonNick.pdf","file_id":"6652","date_created":"2019-07-19T06:54:46Z"}],"citation":{"ama":"Barton NH. The consequences of an introgression event. <i>Molecular Ecology</i>. 2018;27(24):4973-4975. doi:<a href=\"https://doi.org/10.1111/mec.14950\">10.1111/mec.14950</a>","chicago":"Barton, Nicholas H. “The Consequences of an Introgression Event.” <i>Molecular Ecology</i>. Wiley, 2018. <a href=\"https://doi.org/10.1111/mec.14950\">https://doi.org/10.1111/mec.14950</a>.","ieee":"N. H. Barton, “The consequences of an introgression event,” <i>Molecular Ecology</i>, vol. 27, no. 24. Wiley, pp. 4973–4975, 2018.","ista":"Barton NH. 2018. The consequences of an introgression event. Molecular Ecology. 27(24), 4973–4975.","short":"N.H. Barton, Molecular Ecology 27 (2018) 4973–4975.","mla":"Barton, Nicholas H. “The Consequences of an Introgression Event.” <i>Molecular Ecology</i>, vol. 27, no. 24, Wiley, 2018, pp. 4973–75, doi:<a href=\"https://doi.org/10.1111/mec.14950\">10.1111/mec.14950</a>.","apa":"Barton, N. H. (2018). The consequences of an introgression event. <i>Molecular Ecology</i>. Wiley. <a href=\"https://doi.org/10.1111/mec.14950\">https://doi.org/10.1111/mec.14950</a>"},"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"ddc":["576"],"language":[{"iso":"eng"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publication":"Molecular Ecology","related_material":{"record":[{"status":"public","relation":"research_data","id":"9805"}]},"department":[{"_id":"NiBa"}],"author":[{"id":"4880FE40-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-8548-5240","full_name":"Barton, Nicholas H","first_name":"Nicholas H","last_name":"Barton"}]},{"doi":"10.7554/eLife.32035","volume":7,"has_accepted_license":"1","type":"journal_article","external_id":{"isi":["000431035800001"]},"quality_controlled":"1","month":"03","publist_id":"7400","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"ddc":["576"],"language":[{"iso":"eng"}],"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","publication":"eLife","related_material":{"record":[{"status":"public","relation":"research_data","id":"9840"}]},"acknowledgement":"We are grateful to Remy Chait for his help and assistance with establishing our experimental setups and to Tobias Bergmiller for valuable insights into some specific experimental details. We thank Luciano Marraffini for donating us the pCas9 plasmid used in this study. We also want to express our gratitude to Seth Barribeau, Andrea Betancourt, Călin Guet, Mato Lagator, Tiago Paixão and Maroš Pleška for valuable discussions on the manuscript. Finally, we would like to thank the \r\neditors and reviewers for their helpful comments and suggestions.","department":[{"_id":"NiBa"},{"_id":"JoBo"}],"ec_funded":1,"author":[{"full_name":"Payne, Pavel","first_name":"Pavel","last_name":"Payne","id":"35F78294-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-2711-9453"},{"last_name":"Geyrhofer","first_name":"Lukas","full_name":"Geyrhofer, Lukas"},{"orcid":"0000-0002-8548-5240","id":"4880FE40-F248-11E8-B48F-1D18A9856A87","last_name":"Barton","first_name":"Nicholas H","full_name":"Barton, Nicholas H"},{"first_name":"Jonathan P","last_name":"Bollback","full_name":"Bollback, Jonathan P","orcid":"0000-0002-4624-4612","id":"2C6FA9CC-F248-11E8-B48F-1D18A9856A87"}],"day":"09","date_published":"2018-03-09T00:00:00Z","article_processing_charge":"No","article_number":"e32035","file_date_updated":"2020-07-14T12:46:25Z","intvolume":"         7","file":[{"creator":"dernst","file_name":"2018_eLife_Payne.pdf","file_id":"5689","date_created":"2018-12-17T10:36:07Z","relation":"main_file","checksum":"447cf6e680bdc3c01062a8737d876569","date_updated":"2020-07-14T12:46:25Z","content_type":"application/pdf","file_size":3533881,"access_level":"open_access"}],"publisher":"eLife Sciences Publications","citation":{"mla":"Payne, Pavel, et al. “CRISPR-Based Herd Immunity Can Limit Phage Epidemics in Bacterial Populations.” <i>ELife</i>, vol. 7, e32035, eLife Sciences Publications, 2018, doi:<a href=\"https://doi.org/10.7554/eLife.32035\">10.7554/eLife.32035</a>.","apa":"Payne, P., Geyrhofer, L., Barton, N. H., &#38; Bollback, J. P. (2018). CRISPR-based herd immunity can limit phage epidemics in bacterial populations. <i>ELife</i>. eLife Sciences Publications. <a href=\"https://doi.org/10.7554/eLife.32035\">https://doi.org/10.7554/eLife.32035</a>","short":"P. Payne, L. Geyrhofer, N.H. Barton, J.P. Bollback, ELife 7 (2018).","ama":"Payne P, Geyrhofer L, Barton NH, Bollback JP. CRISPR-based herd immunity can limit phage epidemics in bacterial populations. <i>eLife</i>. 2018;7. doi:<a href=\"https://doi.org/10.7554/eLife.32035\">10.7554/eLife.32035</a>","ista":"Payne P, Geyrhofer L, Barton NH, Bollback JP. 2018. CRISPR-based herd immunity can limit phage epidemics in bacterial populations. eLife. 7, e32035.","ieee":"P. Payne, L. Geyrhofer, N. H. Barton, and J. P. Bollback, “CRISPR-based herd immunity can limit phage epidemics in bacterial populations,” <i>eLife</i>, vol. 7. eLife Sciences Publications, 2018.","chicago":"Payne, Pavel, Lukas Geyrhofer, Nicholas H Barton, and Jonathan P Bollback. “CRISPR-Based Herd Immunity Can Limit Phage Epidemics in Bacterial Populations.” <i>ELife</i>. eLife Sciences Publications, 2018. <a href=\"https://doi.org/10.7554/eLife.32035\">https://doi.org/10.7554/eLife.32035</a>."},"isi":1,"abstract":[{"text":"Herd immunity, a process in which resistant individuals limit the spread of a pathogen among susceptible hosts has been extensively studied in eukaryotes. Even though bacteria have evolved multiple immune systems against their phage pathogens, herd immunity in bacteria remains unexplored. Here we experimentally demonstrate that herd immunity arises during phage epidemics in structured and unstructured Escherichia coli populations consisting of differing frequencies of susceptible and resistant cells harboring CRISPR immunity. In addition, we develop a mathematical model that quantifies how herd immunity is affected by spatial population structure, bacterial growth rate, and phage replication rate. Using our model we infer a general epidemiological rule describing the relative speed of an epidemic in partially resistant spatially structured populations. Our experimental and theoretical findings indicate that herd immunity may be important in bacterial communities, allowing for stable coexistence of bacteria and their phages and the maintenance of polymorphism in bacterial immunity.","lang":"eng"}],"oa":1,"date_created":"2018-12-11T11:46:23Z","_id":"423","status":"public","title":"CRISPR-based herd immunity can limit phage epidemics in bacterial populations","date_updated":"2025-03-31T16:00:24Z","oa_version":"Published Version","scopus_import":"1","publication_status":"published","year":"2018","project":[{"name":"Selective Barriers to Horizontal Gene Transfer","grant_number":"648440","call_identifier":"H2020","_id":"2578D616-B435-11E9-9278-68D0E5697425"}]},{"intvolume":"       208","issue":"4","citation":{"apa":"Novembre, J., &#38; Barton, N. H. (2018). Tread lightly interpreting polygenic tests of selection. <i>Genetics</i>. Genetics Society of America. <a href=\"https://doi.org/10.1534/genetics.118.300786\">https://doi.org/10.1534/genetics.118.300786</a>","mla":"Novembre, John, and Nicholas H. Barton. “Tread Lightly Interpreting Polygenic Tests of Selection.” <i>Genetics</i>, vol. 208, no. 4, Genetics Society of America, 2018, pp. 1351–55, doi:<a href=\"https://doi.org/10.1534/genetics.118.300786\">10.1534/genetics.118.300786</a>.","ista":"Novembre J, Barton NH. 2018. Tread lightly interpreting polygenic tests of selection. Genetics. 208(4), 1351–1355.","ieee":"J. Novembre and N. H. Barton, “Tread lightly interpreting polygenic tests of selection,” <i>Genetics</i>, vol. 208, no. 4. Genetics Society of America, pp. 1351–1355, 2018.","chicago":"Novembre, John, and Nicholas H Barton. “Tread Lightly Interpreting Polygenic Tests of Selection.” <i>Genetics</i>. Genetics Society of America, 2018. <a href=\"https://doi.org/10.1534/genetics.118.300786\">https://doi.org/10.1534/genetics.118.300786</a>.","ama":"Novembre J, Barton NH. Tread lightly interpreting polygenic tests of selection. <i>Genetics</i>. 2018;208(4):1351-1355. doi:<a href=\"https://doi.org/10.1534/genetics.118.300786\">10.1534/genetics.118.300786</a>","short":"J. Novembre, N.H. Barton, Genetics 208 (2018) 1351–1355."},"publisher":"Genetics Society of America","file":[{"file_size":500129,"access_level":"open_access","date_updated":"2020-07-14T12:46:26Z","content_type":"application/pdf","checksum":"3d838dc285df394376555b794b6a5ad1","relation":"main_file","date_created":"2018-12-12T10:12:40Z","file_id":"4958","creator":"system","file_name":"IST-2018-1012-v1+1_2018_Barton_Tread.pdf"}],"pubrep_id":"1012","article_processing_charge":"No","date_published":"2018-04-01T00:00:00Z","day":"01","file_date_updated":"2020-07-14T12:46:26Z","department":[{"_id":"NiBa"}],"author":[{"full_name":"Novembre, John","last_name":"Novembre","first_name":"John"},{"full_name":"Barton, Nicholas H","first_name":"Nicholas H","last_name":"Barton","id":"4880FE40-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-8548-5240"}],"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"language":[{"iso":"eng"}],"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","ddc":["576"],"publication":"Genetics","month":"04","publist_id":"7393","quality_controlled":"1","external_id":{"isi":["000429094400005"]},"type":"journal_article","has_accepted_license":"1","volume":208,"doi":"10.1534/genetics.118.300786","year":"2018","page":"1351 - 1355","publication_status":"published","oa_version":"Published Version","scopus_import":"1","date_updated":"2023-09-19T10:17:30Z","status":"public","_id":"430","title":"Tread lightly interpreting polygenic tests of selection","oa":1,"date_created":"2018-12-11T11:46:26Z","abstract":[{"text":"In this issue of GENETICS, a new method for detecting natural selection on polygenic traits is developed and applied to sev- eral human examples ( Racimo et al. 2018 ). By de fi nition, many loci contribute to variation in polygenic traits, and a challenge for evolutionary ge neticists has been that these traits can evolve by small, nearly undetectable shifts in allele frequencies across each of many, typically unknown, loci. Recently, a helpful remedy has arisen. Genome-wide associ- ation studies (GWAS) have been illuminating sets of loci that can be interrogated jointly for c hanges in allele frequencies. By aggregating small signal s of change across many such loci, directional natural selection is now in principle detect- able using genetic data, even for highly polygenic traits. This is an exciting arena of progress – with these methods, tests can be made for selection associated with traits, and we can now study selection in what may be its most prevalent mode. The continuing fast pace of GWAS publications suggest there will be many more polygenic tests of selection in the near future, as every new GWAS is an opportunity for an accom- panying test of polygenic selection. However, it is important to be aware of complications th at arise in interpretation, especially given that these studies may easily be misinter- preted both in and outside the evolutionary genetics commu- nity. Here, we provide context for understanding polygenic tests and urge caution regarding how these results are inter- preted and reported upon more broadly.","lang":"eng"}],"isi":1},{"type":"journal_article","external_id":{"isi":["000394144900025"],"pmid":["27881471"]},"doi":"10.1534/genetics.116.189340","volume":205,"publication_identifier":{"issn":["0016-6731"]},"article_type":"original","quality_controlled":"1","month":"02","publist_id":"6256","department":[{"_id":"NiBa"}],"ec_funded":1,"author":[{"full_name":"Heredia, Jorge","first_name":"Jorge","last_name":"Heredia"},{"orcid":"0000-0002-6873-2967","id":"42302D54-F248-11E8-B48F-1D18A9856A87","last_name":"Trubenova","first_name":"Barbora","full_name":"Trubenova, Barbora"},{"full_name":"Sudholt, Dirk","last_name":"Sudholt","first_name":"Dirk"},{"orcid":"0000-0003-2361-3953","id":"2C5658E6-F248-11E8-B48F-1D18A9856A87","first_name":"Tiago","last_name":"Paixao","full_name":"Paixao, Tiago"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publication":"Genetics","language":[{"iso":"eng"}],"ddc":["570"],"issue":"2","intvolume":"       205","publisher":"Genetics Society of America","citation":{"mla":"Heredia, Jorge, et al. “Selection Limits to Adaptive Walks on Correlated Landscapes.” <i>Genetics</i>, vol. 205, no. 2, Genetics Society of America, 2017, pp. 803–25, doi:<a href=\"https://doi.org/10.1534/genetics.116.189340\">10.1534/genetics.116.189340</a>.","apa":"Heredia, J., Trubenova, B., Sudholt, D., &#38; Paixao, T. (2017). Selection limits to adaptive walks on correlated landscapes. <i>Genetics</i>. Genetics Society of America. <a href=\"https://doi.org/10.1534/genetics.116.189340\">https://doi.org/10.1534/genetics.116.189340</a>","short":"J. Heredia, B. Trubenova, D. Sudholt, T. Paixao, Genetics 205 (2017) 803–825.","ama":"Heredia J, Trubenova B, Sudholt D, Paixao T. Selection limits to adaptive walks on correlated landscapes. <i>Genetics</i>. 2017;205(2):803-825. doi:<a href=\"https://doi.org/10.1534/genetics.116.189340\">10.1534/genetics.116.189340</a>","ieee":"J. Heredia, B. Trubenova, D. Sudholt, and T. Paixao, “Selection limits to adaptive walks on correlated landscapes,” <i>Genetics</i>, vol. 205, no. 2. Genetics Society of America, pp. 803–825, 2017.","ista":"Heredia J, Trubenova B, Sudholt D, Paixao T. 2017. Selection limits to adaptive walks on correlated landscapes. Genetics. 205(2), 803–825.","chicago":"Heredia, Jorge, Barbora Trubenova, Dirk Sudholt, and Tiago Paixao. “Selection Limits to Adaptive Walks on Correlated Landscapes.” <i>Genetics</i>. Genetics Society of America, 2017. <a href=\"https://doi.org/10.1534/genetics.116.189340\">https://doi.org/10.1534/genetics.116.189340</a>."},"day":"01","date_published":"2017-02-01T00:00:00Z","main_file_link":[{"url":"https://doi.org/10.1534/genetics.116.189340","open_access":"1"}],"article_processing_charge":"No","isi":1,"_id":"1111","status":"public","title":"Selection limits to adaptive walks on correlated landscapes","abstract":[{"lang":"eng","text":"Adaptation depends critically on the effects of new mutations and their dependency on the genetic background in which they occur. These two factors can be summarized by the fitness landscape. However, it would require testing all mutations in all backgrounds, making the definition and analysis of fitness landscapes mostly inaccessible. Instead of postulating a particular fitness landscape, we address this problem by considering general classes of landscapes and calculating an upper limit for the time it takes for a population to reach a fitness peak, circumventing the need to have full knowledge about the fitness landscape. We analyze populations in the weak-mutation regime and characterize the conditions that enable them to quickly reach the fitness peak as a function of the number of sites under selection. We show that for additive landscapes there is a critical selection strength enabling populations to reach high-fitness genotypes, regardless of the distribution of effects. This threshold scales with the number of sites under selection, effectively setting a limit to adaptation, and results from the inevitable increase in deleterious mutational pressure as the population adapts in a space of discrete genotypes. Furthermore, we show that for the class of all unimodal landscapes this condition is sufficient but not necessary for rapid adaptation, as in some highly epistatic landscapes the critical strength does not depend on the number of sites under selection; effectively removing this barrier to adaptation."}],"oa":1,"date_created":"2018-12-11T11:50:12Z","oa_version":"Published Version","scopus_import":"1","date_updated":"2026-06-18T10:46:55Z","year":"2017","pmid":1,"project":[{"_id":"25B1EC9E-B435-11E9-9278-68D0E5697425","call_identifier":"FP7","name":"Speed of Adaptation in Population Genetics and Evolutionary Computation","grant_number":"618091"}],"page":"803 - 825","publication_status":"published"},{"department":[{"_id":"NiBa"}],"author":[{"orcid":"0000-0003-2361-3953","id":"2C5658E6-F248-11E8-B48F-1D18A9856A87","first_name":"Tiago","last_name":"Paixao","full_name":"Paixao, Tiago"},{"last_name":"Pérez Heredia","first_name":"Jorge","full_name":"Pérez Heredia, Jorge"}],"scopus_import":1,"oa_version":"None","conference":{"location":"Copenhagen, Denmark","start_date":"2017-01-12","name":"FOGA: Foundations of Genetic Algorithms","end_date":"2017-01-15"},"date_updated":"2021-01-12T06:48:22Z","publication":"Proceedings of the 14th ACM/SIGEVO Conference on Foundations of Genetic Algorithms","language":[{"iso":"eng"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","year":"2017","publisher":"ACM","citation":{"mla":"Paixao, Tiago, and Jorge Pérez Heredia. “An Application of Stochastic Differential Equations to Evolutionary Algorithms.” <i>Proceedings of the 14th ACM/SIGEVO Conference on Foundations of Genetic Algorithms</i>, ACM, 2017, pp. 3–11, doi:<a href=\"https://doi.org/10.1145/3040718.3040729\">10.1145/3040718.3040729</a>.","apa":"Paixao, T., &#38; Pérez Heredia, J. (2017). An application of stochastic differential equations to evolutionary algorithms. In <i>Proceedings of the 14th ACM/SIGEVO Conference on Foundations of Genetic Algorithms</i> (pp. 3–11). Copenhagen, Denmark: ACM. <a href=\"https://doi.org/10.1145/3040718.3040729\">https://doi.org/10.1145/3040718.3040729</a>","short":"T. Paixao, J. Pérez Heredia, in:, Proceedings of the 14th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, ACM, 2017, pp. 3–11.","ama":"Paixao T, Pérez Heredia J. An application of stochastic differential equations to evolutionary algorithms. In: <i>Proceedings of the 14th ACM/SIGEVO Conference on Foundations of Genetic Algorithms</i>. ACM; 2017:3-11. doi:<a href=\"https://doi.org/10.1145/3040718.3040729\">10.1145/3040718.3040729</a>","chicago":"Paixao, Tiago, and Jorge Pérez Heredia. “An Application of Stochastic Differential Equations to Evolutionary Algorithms.” In <i>Proceedings of the 14th ACM/SIGEVO Conference on Foundations of Genetic Algorithms</i>, 3–11. ACM, 2017. <a href=\"https://doi.org/10.1145/3040718.3040729\">https://doi.org/10.1145/3040718.3040729</a>.","ista":"Paixao T, Pérez Heredia J. 2017. An application of stochastic differential equations to evolutionary algorithms. Proceedings of the 14th ACM/SIGEVO Conference on Foundations of Genetic Algorithms. FOGA: Foundations of Genetic Algorithms, 3–11.","ieee":"T. Paixao and J. Pérez Heredia, “An application of stochastic differential equations to evolutionary algorithms,” in <i>Proceedings of the 14th ACM/SIGEVO Conference on Foundations of Genetic Algorithms</i>, Copenhagen, Denmark, 2017, pp. 3–11."},"day":"12","date_published":"2017-01-12T00:00:00Z","publication_status":"published","page":"3 - 11","type":"conference","doi":"10.1145/3040718.3040729","_id":"1112","status":"public","publication_identifier":{"isbn":["978-145034651-1"]},"title":"An application of stochastic differential equations to evolutionary algorithms","quality_controlled":"1","abstract":[{"text":"There has been renewed interest in modelling the behaviour of evolutionary algorithms by more traditional mathematical objects, such as ordinary differential equations or Markov chains. The advantage is that the analysis becomes greatly facilitated due to the existence of well established methods. However, this typically comes at the cost of disregarding information about the process. Here, we introduce the use of stochastic differential equations (SDEs) for the study of EAs. SDEs can produce simple analytical results for the dynamics of stochastic processes, unlike Markov chains which can produce rigorous but unwieldy expressions about the dynamics. On the other hand, unlike ordinary differential equations (ODEs), they do not discard information about the stochasticity of the process. We show that these are especially suitable for the analysis of fixed budget scenarios and present analogs of the additive and multiplicative drift theorems for SDEs. We exemplify the use of these methods for two model algorithms ((1+1) EA and RLS) on two canonical problems(OneMax and LeadingOnes).","lang":"eng"}],"publist_id":"6255","date_created":"2018-12-11T11:50:12Z","month":"01"},{"project":[{"grant_number":"618091","name":"Speed of Adaptation in Population Genetics and Evolutionary Computation","_id":"25B1EC9E-B435-11E9-9278-68D0E5697425","call_identifier":"FP7"},{"_id":"25B07788-B435-11E9-9278-68D0E5697425","call_identifier":"FP7","name":"Limits to selection in biology and in evolutionary computation","grant_number":"250152"}],"year":"2017","page":"367 - 374","publication_status":"published","scopus_import":"1","oa_version":"Submitted Version","date_updated":"2025-07-10T11:50:13Z","title":"Spatial gene frequency waves under genotype dependent dispersal","_id":"1169","status":"public","oa":1,"date_created":"2018-12-11T11:50:31Z","abstract":[{"lang":"eng","text":"Dispersal is a crucial factor in natural evolution, since it determines the habitat experienced by any population and defines the spatial scale of interactions between individuals. There is compelling evidence for systematic differences in dispersal characteristics within the same population, i.e., genotype-dependent dispersal. The consequences of genotype-dependent dispersal on other evolutionary phenomena, however, are poorly understood. In this article we investigate the effect of genotype-dependent dispersal on spatial gene frequency patterns, using a generalization of the classical diffusion model of selection and dispersal. Dispersal is characterized by the variance of dispersal (diffusion coefficient) and the mean displacement (directional advection term). We demonstrate that genotype-dependent dispersal may change the qualitative behavior of Fisher waves, which change from being “pulled” to being “pushed” wave fronts as the discrepancy in dispersal between genotypes increases. The speed of any wave is partitioned into components due to selection, genotype-dependent variance of dispersal, and genotype-dependent mean displacement. We apply our findings to wave fronts maintained by selection against heterozygotes. Furthermore, we identify a benefit of increased variance of dispersal, quantify its effect on the speed of the wave, and discuss the implications for the evolution of dispersal strategies."}],"isi":1,"citation":{"mla":"Novak, Sebastian, and Richard Kollár. “Spatial Gene Frequency Waves under Genotype Dependent Dispersal.” <i>Genetics</i>, vol. 205, no. 1, Genetics Society of America, 2017, pp. 367–74, doi:<a href=\"https://doi.org/10.1534/genetics.116.193946\">10.1534/genetics.116.193946</a>.","apa":"Novak, S., &#38; Kollár, R. (2017). Spatial gene frequency waves under genotype dependent dispersal. <i>Genetics</i>. Genetics Society of America. <a href=\"https://doi.org/10.1534/genetics.116.193946\">https://doi.org/10.1534/genetics.116.193946</a>","short":"S. Novak, R. Kollár, Genetics 205 (2017) 367–374.","ama":"Novak S, Kollár R. Spatial gene frequency waves under genotype dependent dispersal. <i>Genetics</i>. 2017;205(1):367-374. doi:<a href=\"https://doi.org/10.1534/genetics.116.193946\">10.1534/genetics.116.193946</a>","chicago":"Novak, Sebastian, and Richard Kollár. “Spatial Gene Frequency Waves under Genotype Dependent Dispersal.” <i>Genetics</i>. Genetics Society of America, 2017. <a href=\"https://doi.org/10.1534/genetics.116.193946\">https://doi.org/10.1534/genetics.116.193946</a>.","ista":"Novak S, Kollár R. 2017. Spatial gene frequency waves under genotype dependent dispersal. Genetics. 205(1), 367–374.","ieee":"S. Novak and R. Kollár, “Spatial gene frequency waves under genotype dependent dispersal,” <i>Genetics</i>, vol. 205, no. 1. Genetics Society of America, pp. 367–374, 2017."},"publisher":"Genetics Society of America","pubrep_id":"727","file":[{"date_created":"2018-12-12T10:10:43Z","file_id":"4833","creator":"system","file_name":"IST-2016-727-v1+1_SFC_Genetics_final.pdf","content_type":"application/pdf","date_updated":"2020-07-14T12:44:37Z","file_size":361500,"access_level":"open_access","checksum":"7c8ab79cda1f92760bbbbe0f53175bfc","relation":"main_file"}],"intvolume":"       205","issue":"1","file_date_updated":"2020-07-14T12:44:37Z","article_processing_charge":"No","date_published":"2017-01-01T00:00:00Z","day":"01","ec_funded":1,"author":[{"full_name":"Novak, Sebastian","last_name":"Novak","first_name":"Sebastian","id":"461468AE-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-2519-824X"},{"last_name":"Kollár","first_name":"Richard","full_name":"Kollár, Richard"}],"department":[{"_id":"NiBa"}],"language":[{"iso":"eng"}],"publication":"Genetics","ddc":["576"],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publication_identifier":{"issn":["0016-6731"]},"month":"01","publist_id":"6188","quality_controlled":"1","external_id":{"isi":["000393677300025"]},"type":"journal_article","has_accepted_license":"1","volume":205,"doi":"10.1534/genetics.116.193946"},{"arxiv":1,"user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","language":[{"iso":"eng"}],"publication":"Bulletin of Mathematical Biology","department":[{"_id":"NiBa"}],"acknowledgement":"We thank Nick Barton, Katarína Bod’ová, and Sr\r\n-\r\ndan Sarikas for constructive feed-\r\nback and support. Furthermore, we would like to express our deep gratitude to the anonymous referees (one\r\nof whom, Jimmy Garnier, agreed to reveal his identity) and the editor Max Souza, for very helpful and\r\ndetailed comments and suggestions that significantly helped us to improve the manuscript. This project has\r\nreceived funding from the European Union’s Seventh Framework Programme for research, technological\r\ndevelopment and demonstration under Grant Agreement 618091 Speed of Adaptation in Population Genet-\r\nics and Evolutionary Computation (SAGE) and the European Research Council (ERC) Grant No. 250152\r\n(SN), from the Scientific Grant Agency of the Slovak Republic under the Grant 1/0459/13 and by the Slovak\r\nResearch and Development Agency under the Contract No. APVV-14-0378 (RK). RK would also like to\r\nthank IST Austria for its hospitality during the work on this project.","ec_funded":1,"author":[{"last_name":"Kollár","first_name":"Richard","full_name":"Kollár, Richard"},{"first_name":"Sebastian","last_name":"Novak","full_name":"Novak, Sebastian","orcid":"0000-0002-2519-824X","id":"461468AE-F248-11E8-B48F-1D18A9856A87"}],"article_processing_charge":"No","date_published":"2017-03-01T00:00:00Z","main_file_link":[{"url":"https://arxiv.org/abs/1607.00944","open_access":"1"}],"day":"01","intvolume":"        79","issue":"3","citation":{"mla":"Kollár, Richard, and Sebastian Novak. “Existence of Traveling Waves for the Generalized F–KPP Equation.” <i>Bulletin of Mathematical Biology</i>, vol. 79, no. 3, Springer, 2017, pp. 525–59, doi:<a href=\"https://doi.org/10.1007/s11538-016-0244-3\">10.1007/s11538-016-0244-3</a>.","apa":"Kollár, R., &#38; Novak, S. (2017). Existence of traveling waves for the generalized F–KPP equation. <i>Bulletin of Mathematical Biology</i>. Springer. <a href=\"https://doi.org/10.1007/s11538-016-0244-3\">https://doi.org/10.1007/s11538-016-0244-3</a>","short":"R. Kollár, S. Novak, Bulletin of Mathematical Biology 79 (2017) 525–559.","ama":"Kollár R, Novak S. Existence of traveling waves for the generalized F–KPP equation. <i>Bulletin of Mathematical Biology</i>. 2017;79(3):525-559. doi:<a href=\"https://doi.org/10.1007/s11538-016-0244-3\">10.1007/s11538-016-0244-3</a>","ista":"Kollár R, Novak S. 2017. Existence of traveling waves for the generalized F–KPP equation. Bulletin of Mathematical Biology. 79(3), 525–559.","ieee":"R. Kollár and S. Novak, “Existence of traveling waves for the generalized F–KPP equation,” <i>Bulletin of Mathematical Biology</i>, vol. 79, no. 3. Springer, pp. 525–559, 2017.","chicago":"Kollár, Richard, and Sebastian Novak. “Existence of Traveling Waves for the Generalized F–KPP Equation.” <i>Bulletin of Mathematical Biology</i>. Springer, 2017. <a href=\"https://doi.org/10.1007/s11538-016-0244-3\">https://doi.org/10.1007/s11538-016-0244-3</a>."},"publisher":"Springer","volume":79,"doi":"10.1007/s11538-016-0244-3","external_id":{"arxiv":["1607.00944"],"isi":["000395156200005"]},"type":"journal_article","publist_id":"6160","month":"03","quality_controlled":"1","date_updated":"2025-09-22T09:44:54Z","oa_version":"Preprint","scopus_import":"1","publication_status":"published","page":"525-559","year":"2017","project":[{"grant_number":"618091","name":"Speed of Adaptation in Population Genetics and Evolutionary Computation","_id":"25B1EC9E-B435-11E9-9278-68D0E5697425","call_identifier":"FP7"},{"grant_number":"250152","name":"Limits to selection in biology and in evolutionary computation","call_identifier":"FP7","_id":"25B07788-B435-11E9-9278-68D0E5697425"}],"isi":1,"oa":1,"date_created":"2018-12-11T11:50:38Z","abstract":[{"lang":"eng","text":"Variation in genotypes may be responsible for differences in dispersal rates, directional biases, and growth rates of individuals. These traits may favor certain genotypes and enhance their spatiotemporal spreading into areas occupied by the less advantageous genotypes. We study how these factors influence the speed of spreading in the case of two competing genotypes under the assumption that spatial variation of the total population is small compared to the spatial variation of the frequencies of the genotypes in the population. In that case, the dynamics of the frequency of one of the genotypes is approximately described by a generalized Fisher–Kolmogorov–Petrovskii–Piskunov (F–KPP) equation. This generalized F–KPP equation with (nonlinear) frequency-dependent diffusion and advection terms admits traveling wave solutions that characterize the invasion of the dominant genotype. Our existence results generalize the classical theory for traveling waves for the F–KPP with constant coefficients. Moreover, in the particular case of the quadratic (monostable) nonlinear growth–decay rate in the generalized F–KPP we study in detail the influence of the variance in diffusion and mean displacement rates of the two genotypes on the minimal wave propagation speed."}],"_id":"1191","status":"public","title":"Existence of traveling waves for the generalized F–KPP equation"},{"page":"96 - 109","publication_status":"published","year":"2017","project":[{"_id":"25B07788-B435-11E9-9278-68D0E5697425","call_identifier":"FP7","name":"Limits to selection in biology and in evolutionary computation","grant_number":"250152"}],"date_updated":"2025-04-15T07:11:02Z","scopus_import":"1","oa_version":"Submitted Version","oa":1,"date_created":"2018-12-11T11:50:40Z","abstract":[{"lang":"eng","text":"Much of quantitative genetics is based on the ‘infinitesimal model’, under which selection has a negligible effect on the genetic variance. This is typically justified by assuming a very large number of loci with additive effects. However, it applies even when genes interact, provided that the number of loci is large enough that selection on each of them is weak relative to random drift. In the long term, directional selection will change allele frequencies, but even then, the effects of epistasis on the ultimate change in trait mean due to selection may be modest. Stabilising selection can maintain many traits close to their optima, even when the underlying alleles are weakly selected. However, the number of traits that can be optimised is apparently limited to ~4Ne by the ‘drift load’, and this is hard to reconcile with the apparent complexity of many organisms. Just as for the mutation load, this limit can be evaded by a particular form of negative epistasis. A more robust limit is set by the variance in reproductive success. This suggests that selection accumulates information most efficiently in the infinitesimal regime, when selection on individual alleles is weak, and comparable with random drift. A review of evidence on selection strength suggests that although most variance in fitness may be because of alleles with large Nes, substantial amounts of adaptation may be because of alleles in the infinitesimal regime, in which epistasis has modest effects."}],"_id":"1199","status":"public","title":"How does epistasis influence the response to selection?","isi":1,"article_processing_charge":"No","day":"01","date_published":"2017-01-01T00:00:00Z","main_file_link":[{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5176114/","open_access":"1"}],"intvolume":"       118","citation":{"mla":"Barton, Nicholas H. “How Does Epistasis Influence the Response to Selection?” <i>Heredity</i>, vol. 118, Nature Publishing Group, 2017, pp. 96–109, doi:<a href=\"https://doi.org/10.1038/hdy.2016.109\">10.1038/hdy.2016.109</a>.","apa":"Barton, N. H. (2017). How does epistasis influence the response to selection? <i>Heredity</i>. Nature Publishing Group. <a href=\"https://doi.org/10.1038/hdy.2016.109\">https://doi.org/10.1038/hdy.2016.109</a>","short":"N.H. Barton, Heredity 118 (2017) 96–109.","ama":"Barton NH. How does epistasis influence the response to selection? <i>Heredity</i>. 2017;118:96-109. doi:<a href=\"https://doi.org/10.1038/hdy.2016.109\">10.1038/hdy.2016.109</a>","chicago":"Barton, Nicholas H. “How Does Epistasis Influence the Response to Selection?” <i>Heredity</i>. Nature Publishing Group, 2017. <a href=\"https://doi.org/10.1038/hdy.2016.109\">https://doi.org/10.1038/hdy.2016.109</a>.","ieee":"N. H. Barton, “How does epistasis influence the response to selection?,” <i>Heredity</i>, vol. 118. Nature Publishing Group, pp. 96–109, 2017.","ista":"Barton NH. 2017. How does epistasis influence the response to selection? Heredity. 118, 96–109."},"publisher":"Nature Publishing Group","publication":"Heredity","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","language":[{"iso":"eng"}],"department":[{"_id":"NiBa"}],"related_material":{"record":[{"id":"9710","relation":"research_data","status":"public"}]},"author":[{"orcid":"0000-0002-8548-5240","id":"4880FE40-F248-11E8-B48F-1D18A9856A87","first_name":"Nicholas H","last_name":"Barton","full_name":"Barton, Nicholas H"}],"ec_funded":1,"month":"01","publist_id":"6151","quality_controlled":"1","volume":118,"doi":"10.1038/hdy.2016.109","external_id":{"isi":["000392229100011"]},"type":"journal_article"},{"intvolume":"        78","issue":"2","citation":{"apa":"Paixao, T., Pérez Heredia, J., Sudholt, D., &#38; Trubenova, B. (2017). Towards a runtime comparison of natural and artificial evolution. <i>Algorithmica</i>. Springer. <a href=\"https://doi.org/10.1007/s00453-016-0212-1\">https://doi.org/10.1007/s00453-016-0212-1</a>","mla":"Paixao, Tiago, et al. “Towards a Runtime Comparison of Natural and Artificial Evolution.” <i>Algorithmica</i>, vol. 78, no. 2, Springer, 2017, pp. 681–713, doi:<a href=\"https://doi.org/10.1007/s00453-016-0212-1\">10.1007/s00453-016-0212-1</a>.","chicago":"Paixao, Tiago, Jorge Pérez Heredia, Dirk Sudholt, and Barbora Trubenova. “Towards a Runtime Comparison of Natural and Artificial Evolution.” <i>Algorithmica</i>. Springer, 2017. <a href=\"https://doi.org/10.1007/s00453-016-0212-1\">https://doi.org/10.1007/s00453-016-0212-1</a>.","ieee":"T. Paixao, J. Pérez Heredia, D. Sudholt, and B. Trubenova, “Towards a runtime comparison of natural and artificial evolution,” <i>Algorithmica</i>, vol. 78, no. 2. Springer, pp. 681–713, 2017.","ista":"Paixao T, Pérez Heredia J, Sudholt D, Trubenova B. 2017. Towards a runtime comparison of natural and artificial evolution. Algorithmica. 78(2), 681–713.","ama":"Paixao T, Pérez Heredia J, Sudholt D, Trubenova B. Towards a runtime comparison of natural and artificial evolution. <i>Algorithmica</i>. 2017;78(2):681-713. doi:<a href=\"https://doi.org/10.1007/s00453-016-0212-1\">10.1007/s00453-016-0212-1</a>","short":"T. Paixao, J. Pérez Heredia, D. Sudholt, B. Trubenova, Algorithmica 78 (2017) 681–713."},"pubrep_id":"658","publisher":"Springer","file":[{"date_created":"2018-12-12T10:10:19Z","creator":"system","file_name":"IST-2016-658-v1+1_s00453-016-0212-1.pdf","file_id":"4805","content_type":"application/pdf","date_updated":"2020-07-14T12:44:44Z","file_size":710206,"access_level":"open_access","checksum":"7873f665a0c598ac747c908f34cb14b9","relation":"main_file"}],"article_processing_charge":"No","date_published":"2017-06-01T00:00:00Z","day":"01","file_date_updated":"2020-07-14T12:44:44Z","department":[{"_id":"NiBa"},{"_id":"CaGu"}],"ec_funded":1,"author":[{"full_name":"Paixao, Tiago","first_name":"Tiago","last_name":"Paixao","id":"2C5658E6-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-2361-3953"},{"full_name":"Pérez Heredia, Jorge","last_name":"Pérez Heredia","first_name":"Jorge"},{"first_name":"Dirk","last_name":"Sudholt","full_name":"Sudholt, Dirk"},{"last_name":"Trubenova","first_name":"Barbora","full_name":"Trubenova, Barbora","orcid":"0000-0002-6873-2967","id":"42302D54-F248-11E8-B48F-1D18A9856A87"}],"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"ddc":["576"],"publication":"Algorithmica","language":[{"iso":"eng"}],"user_id":"ba8df636-2132-11f1-aed0-ed93e2281fdd","publication_identifier":{"issn":["0178-4617"]},"publist_id":"5931","month":"06","quality_controlled":"1","external_id":{"isi":["000400379500013"]},"type":"journal_article","has_accepted_license":"1","volume":78,"doi":"10.1007/s00453-016-0212-1","year":"2017","project":[{"call_identifier":"FP7","_id":"25B1EC9E-B435-11E9-9278-68D0E5697425","name":"Speed of Adaptation in Population Genetics and Evolutionary Computation","grant_number":"618091"}],"publication_status":"published","page":"681 - 713","oa_version":"Published Version","scopus_import":"1","date_updated":"2026-04-16T09:55:33Z","_id":"1336","status":"public","title":"Towards a runtime comparison of natural and artificial evolution","date_created":"2018-12-11T11:51:27Z","oa":1,"abstract":[{"lang":"eng","text":"Evolutionary algorithms (EAs) form a popular optimisation paradigm inspired by natural evolution. In recent years the field of evolutionary computation has developed a rigorous analytical theory to analyse the runtimes of EAs on many illustrative problems. Here we apply this theory to a simple model of natural evolution. In the Strong Selection Weak Mutation (SSWM) evolutionary regime the time between occurrences of new mutations is much longer than the time it takes for a mutated genotype to take over the population. In this situation, the population only contains copies of one genotype and evolution can be modelled as a stochastic process evolving one genotype by means of mutation and selection between the resident and the mutated genotype. The probability of accepting the mutated genotype then depends on the change in fitness. We study this process, SSWM, from an algorithmic perspective, quantifying its expected optimisation time for various parameters and investigating differences to a similar evolutionary algorithm, the well-known (1+1) EA. We show that SSWM can have a moderate advantage over the (1+1) EA at crossing fitness valleys and study an example where SSWM outperforms the (1+1) EA by taking advantage of information on the fitness gradient."}],"isi":1}]