[{"scopus_import":"1","file_date_updated":"2020-07-14T12:47:54Z","ddc":["576"],"intvolume":"        80","citation":{"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>.","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.","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>.","short":"P. Oliveto, T. Paixao, J. Pérez Heredia, D. Sudholt, B. Trubenova, Algorithmica 80 (2018) 1604–1633.","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.","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>"},"doi":"10.1007/s00453-017-0369-2","publication_status":"published","oa_version":"Published Version","date_published":"2018-05-01T00:00:00Z","status":"public","oa":1,"month":"05","ec_funded":1,"issue":"5","abstract":[{"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.","lang":"eng"}],"date_updated":"2023-09-11T14:11:35Z","year":"2018","_id":"723","article_processing_charge":"No","pubrep_id":"1014","publist_id":"6957","volume":80,"quality_controlled":"1","external_id":{"isi":["000428239300010"]},"has_accepted_license":"1","publication":"Algorithmica","date_created":"2018-12-11T11:48:09Z","page":"1604 - 1633","type":"journal_article","department":[{"_id":"NiBa"},{"_id":"CaGu"}],"language":[{"iso":"eng"}],"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","publisher":"Springer","title":"How to escape local optima in black box optimisation when non elitism outperforms elitism","day":"01","tmp":{"short":"CC BY (4.0)","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"isi":1,"author":[{"full_name":"Oliveto, Pietro","last_name":"Oliveto","first_name":"Pietro"},{"full_name":"Paixao, Tiago","orcid":"0000-0003-2361-3953","first_name":"Tiago","id":"2C5658E6-F248-11E8-B48F-1D18A9856A87","last_name":"Paixao"},{"full_name":"Pérez Heredia, Jorge","last_name":"Pérez Heredia","first_name":"Jorge"},{"full_name":"Sudholt, Dirk","first_name":"Dirk","last_name":"Sudholt"},{"full_name":"Trubenova, Barbora","first_name":"Barbora","orcid":"0000-0002-6873-2967","id":"42302D54-F248-11E8-B48F-1D18A9856A87","last_name":"Trubenova"}],"project":[{"_id":"25B1EC9E-B435-11E9-9278-68D0E5697425","grant_number":"618091","call_identifier":"FP7","name":"Speed of Adaptation in Population Genetics and Evolutionary Computation"}],"file":[{"file_size":691245,"content_type":"application/pdf","relation":"main_file","access_level":"open_access","file_id":"4674","creator":"system","checksum":"7d92f5d7be81e387edeec4f06442791c","date_created":"2018-12-12T10:08:14Z","file_name":"IST-2018-1014-v1+1_2018_Paixao_Escape.pdf","date_updated":"2020-07-14T12:47:54Z"}]},{"date_published":"2017-02-01T00:00:00Z","oa_version":"Published Version","publication_status":"published","doi":"10.1534/genetics.116.189340","citation":{"short":"J. Heredia, B. Trubenova, D. Sudholt, T. Paixao, Genetics 205 (2017) 803–825.","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.","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>","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>.","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>","ista":"Heredia J, Trubenova B, Sudholt D, Paixao T. 2017. Selection limits to adaptive walks on correlated landscapes. Genetics. 205(2), 803–825.","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>."},"intvolume":"       205","main_file_link":[{"url":"https://doi.org/10.1534/genetics.116.189340","open_access":"1"}],"scopus_import":"1","_id":"1111","year":"2017","date_updated":"2023-09-20T11:35:03Z","abstract":[{"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.","lang":"eng"}],"issue":"2","ec_funded":1,"month":"02","oa":1,"publication_identifier":{"issn":["00166731"]},"status":"public","language":[{"iso":"eng"}],"department":[{"_id":"NiBa"}],"type":"journal_article","page":"803 - 825","date_created":"2018-12-11T11:50:12Z","publication":"Genetics","external_id":{"pmid":["27881471"],"isi":["000394144900025"]},"quality_controlled":"1","volume":205,"publist_id":"6256","article_processing_charge":"No","article_type":"original","project":[{"name":"Speed of Adaptation in Population Genetics and Evolutionary Computation","call_identifier":"FP7","_id":"25B1EC9E-B435-11E9-9278-68D0E5697425","grant_number":"618091"}],"isi":1,"author":[{"last_name":"Heredia","first_name":"Jorge","full_name":"Heredia, Jorge"},{"last_name":"Trubenova","id":"42302D54-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-6873-2967","first_name":"Barbora","full_name":"Trubenova, Barbora"},{"full_name":"Sudholt, Dirk","last_name":"Sudholt","first_name":"Dirk"},{"full_name":"Paixao, Tiago","id":"2C5658E6-F248-11E8-B48F-1D18A9856A87","last_name":"Paixao","first_name":"Tiago","orcid":"0000-0003-2361-3953"}],"day":"01","pmid":1,"title":"Selection limits to adaptive walks on correlated landscapes","publisher":"Genetics Society of America","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1"},{"month":"01","title":"An application of stochastic differential equations to evolutionary algorithms","publication_identifier":{"isbn":["978-145034651-1"]},"publisher":"ACM","status":"public","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"1112","author":[{"full_name":"Paixao, Tiago","first_name":"Tiago","orcid":"0000-0003-2361-3953","id":"2C5658E6-F248-11E8-B48F-1D18A9856A87","last_name":"Paixao"},{"first_name":"Jorge","last_name":"Pérez Heredia","full_name":"Pérez Heredia, Jorge"}],"day":"12","year":"2017","date_updated":"2021-01-12T06:48:22Z","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"}],"quality_controlled":"1","citation":{"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>","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.","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>.","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>.","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.","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>","short":"T. Paixao, J. Pérez Heredia, in:, Proceedings of the 14th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, ACM, 2017, pp. 3–11."},"scopus_import":1,"publist_id":"6255","language":[{"iso":"eng"}],"department":[{"_id":"NiBa"}],"date_published":"2017-01-12T00:00:00Z","oa_version":"None","type":"conference","date_created":"2018-12-11T11:50:12Z","page":"3 - 11","publication":"Proceedings of the 14th ACM/SIGEVO Conference on Foundations of Genetic Algorithms","conference":{"start_date":"2017-01-12","name":"FOGA: Foundations of Genetic Algorithms","end_date":"2017-01-15","location":"Copenhagen, Denmark"},"publication_status":"published","doi":"10.1145/3040718.3040729"},{"article_type":"original","pubrep_id":"894","publist_id":"7004","volume":13,"quality_controlled":"1","related_material":{"record":[{"status":"public","relation":"research_data","id":"9849"},{"relation":"research_data","status":"public","id":"9850"},{"relation":"research_data","status":"public","id":"9851"},{"id":"9852","relation":"research_data","status":"public"},{"id":"6263","relation":"dissertation_contains","status":"public"}]},"has_accepted_license":"1","publication":"PLoS Computational Biology","date_created":"2018-12-11T11:47:58Z","type":"journal_article","department":[{"_id":"ToBo"},{"_id":"NiBa"},{"_id":"CaGu"}],"language":[{"iso":"eng"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publisher":"Public Library of Science","title":"Stress induced mutagenesis: Stress diversity facilitates the persistence of mutator genes","day":"18","tmp":{"short":"CC BY (4.0)","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"author":[{"orcid":"0000-0002-2519-8004","first_name":"Marta","id":"4342E402-F248-11E8-B48F-1D18A9856A87","last_name":"Lukacisinova","full_name":"Lukacisinova, Marta"},{"full_name":"Novak, Sebastian","last_name":"Novak","id":"461468AE-F248-11E8-B48F-1D18A9856A87","first_name":"Sebastian","orcid":"0000-0002-2519-824X"},{"first_name":"Tiago","orcid":"0000-0003-2361-3953","id":"2C5658E6-F248-11E8-B48F-1D18A9856A87","last_name":"Paixao","full_name":"Paixao, Tiago"}],"project":[{"name":"Speed of Adaptation in Population Genetics and Evolutionary Computation","call_identifier":"FP7","_id":"25B1EC9E-B435-11E9-9278-68D0E5697425","grant_number":"618091"}],"file":[{"file_name":"IST-2017-894-v1+1_journal.pcbi.1005609.pdf","date_updated":"2020-07-14T12:47:46Z","date_created":"2018-12-12T10:15:01Z","creator":"system","file_id":"5117","checksum":"9143c290fa6458ed2563bff4b295554a","access_level":"open_access","content_type":"application/pdf","relation":"main_file","file_size":3775716}],"file_date_updated":"2020-07-14T12:47:46Z","scopus_import":1,"ddc":["576"],"citation":{"short":"M. Lukacisinova, S. Novak, T. Paixao, PLoS Computational Biology 13 (2017).","ama":"Lukacisinova M, Novak S, Paixao T. Stress induced mutagenesis: Stress diversity facilitates the persistence of mutator genes. <i>PLoS Computational Biology</i>. 2017;13(7). doi:<a href=\"https://doi.org/10.1371/journal.pcbi.1005609\">10.1371/journal.pcbi.1005609</a>","ieee":"M. Lukacisinova, S. Novak, and T. Paixao, “Stress induced mutagenesis: Stress diversity facilitates the persistence of mutator genes,” <i>PLoS Computational Biology</i>, vol. 13, no. 7. Public Library of Science, 2017.","chicago":"Lukacisinova, Marta, Sebastian Novak, and Tiago Paixao. “Stress Induced Mutagenesis: Stress Diversity Facilitates the Persistence of Mutator Genes.” <i>PLoS Computational Biology</i>. Public Library of Science, 2017. <a href=\"https://doi.org/10.1371/journal.pcbi.1005609\">https://doi.org/10.1371/journal.pcbi.1005609</a>.","ista":"Lukacisinova M, Novak S, Paixao T. 2017. Stress induced mutagenesis: Stress diversity facilitates the persistence of mutator genes. PLoS Computational Biology. 13(7), e1005609.","apa":"Lukacisinova, M., Novak, S., &#38; Paixao, T. (2017). Stress induced mutagenesis: Stress diversity facilitates the persistence of mutator genes. <i>PLoS Computational Biology</i>. Public Library of Science. <a href=\"https://doi.org/10.1371/journal.pcbi.1005609\">https://doi.org/10.1371/journal.pcbi.1005609</a>","mla":"Lukacisinova, Marta, et al. “Stress Induced Mutagenesis: Stress Diversity Facilitates the Persistence of Mutator Genes.” <i>PLoS Computational Biology</i>, vol. 13, no. 7, e1005609, Public Library of Science, 2017, doi:<a href=\"https://doi.org/10.1371/journal.pcbi.1005609\">10.1371/journal.pcbi.1005609</a>."},"intvolume":"        13","doi":"10.1371/journal.pcbi.1005609","publication_status":"published","oa_version":"Published Version","date_published":"2017-07-18T00:00:00Z","status":"public","publication_identifier":{"issn":["1553734X"]},"oa":1,"month":"07","ec_funded":1,"issue":"7","abstract":[{"text":"Mutator strains are expected to evolve when the availability and effect of beneficial mutations are high enough to counteract the disadvantage from deleterious mutations that will inevitably accumulate. As the population becomes more adapted to its environment, both availability and effect of beneficial mutations necessarily decrease and mutation rates are predicted to decrease. It has been shown that certain molecular mechanisms can lead to increased mutation rates when the organism finds itself in a stressful environment. While this may be a correlated response to other functions, it could also be an adaptive mechanism, raising mutation rates only when it is most advantageous. Here, we use a mathematical model to investigate the plausibility of the adaptive hypothesis. We show that such a mechanism can be mantained if the population is subjected to diverse stresses. By simulating various antibiotic treatment schemes, we find that combination treatments can reduce the effectiveness of second-order selection on stress-induced mutagenesis. We discuss the implications of our results to strategies of antibiotic therapy.","lang":"eng"}],"date_updated":"2024-03-25T23:30:14Z","year":"2017","article_number":"e1005609","_id":"696"},{"publication_identifier":{"issn":["01784617"]},"oa":1,"status":"public","ec_funded":1,"month":"06","year":"2017","date_updated":"2023-09-20T11:14:42Z","issue":"2","abstract":[{"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.","lang":"eng"}],"_id":"1336","ddc":["576"],"file_date_updated":"2020-07-14T12:44:44Z","scopus_import":"1","citation":{"short":"T. Paixao, J. Pérez Heredia, D. Sudholt, B. Trubenova, Algorithmica 78 (2017) 681–713.","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.","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>","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>","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.","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>."},"intvolume":"        78","publication_status":"published","doi":"10.1007/s00453-016-0212-1","date_published":"2017-06-01T00:00:00Z","oa_version":"Published Version","title":"Towards a runtime comparison of natural and artificial evolution","publisher":"Springer","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","tmp":{"short":"CC BY (4.0)","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"day":"01","file":[{"file_name":"IST-2016-658-v1+1_s00453-016-0212-1.pdf","date_updated":"2020-07-14T12:44:44Z","date_created":"2018-12-12T10:10:19Z","creator":"system","checksum":"7873f665a0c598ac747c908f34cb14b9","file_id":"4805","access_level":"open_access","content_type":"application/pdf","relation":"main_file","file_size":710206}],"project":[{"call_identifier":"FP7","name":"Speed of Adaptation in Population Genetics and Evolutionary Computation","_id":"25B1EC9E-B435-11E9-9278-68D0E5697425","grant_number":"618091"}],"author":[{"full_name":"Paixao, Tiago","first_name":"Tiago","orcid":"0000-0003-2361-3953","id":"2C5658E6-F248-11E8-B48F-1D18A9856A87","last_name":"Paixao"},{"full_name":"Pérez Heredia, Jorge","last_name":"Pérez Heredia","first_name":"Jorge"},{"first_name":"Dirk","last_name":"Sudholt","full_name":"Sudholt, Dirk"},{"first_name":"Barbora","orcid":"0000-0002-6873-2967","last_name":"Trubenova","id":"42302D54-F248-11E8-B48F-1D18A9856A87","full_name":"Trubenova, Barbora"}],"isi":1,"publist_id":"5931","article_processing_charge":"No","pubrep_id":"658","external_id":{"isi":["000400379500013"]},"quality_controlled":"1","volume":78,"date_created":"2018-12-11T11:51:27Z","page":"681 - 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C., Gupta, A., Henzinger, T. A., Paixao, T., &#38; Petrov, T. (2017). Model checking the evolution of gene regulatory networks. <i>Acta Informatica</i>. Springer. <a href=\"https://doi.org/10.1007/s00236-016-0278-x\">https://doi.org/10.1007/s00236-016-0278-x</a>","ista":"Giacobbe M, Guet CC, Gupta A, Henzinger TA, Paixao T, Petrov T. 2017. Model checking the evolution of gene regulatory networks. Acta Informatica. 54(8), 765–787.","mla":"Giacobbe, Mirco, et al. “Model Checking the Evolution of Gene Regulatory Networks.” <i>Acta Informatica</i>, vol. 54, no. 8, Springer, 2017, pp. 765–87, doi:<a href=\"https://doi.org/10.1007/s00236-016-0278-x\">10.1007/s00236-016-0278-x</a>.","chicago":"Giacobbe, Mirco, Calin C Guet, Ashutosh Gupta, Thomas A Henzinger, Tiago Paixao, and Tatjana Petrov. “Model Checking the Evolution of Gene Regulatory Networks.” <i>Acta Informatica</i>. Springer, 2017. <a href=\"https://doi.org/10.1007/s00236-016-0278-x\">https://doi.org/10.1007/s00236-016-0278-x</a>.","ieee":"M. Giacobbe, C. C. Guet, A. Gupta, T. A. Henzinger, T. Paixao, and T. Petrov, “Model checking the evolution of gene regulatory networks,” <i>Acta Informatica</i>, vol. 54, no. 8. Springer, pp. 765–787, 2017.","ama":"Giacobbe M, Guet CC, Gupta A, Henzinger TA, Paixao T, Petrov T. Model checking the evolution of gene regulatory networks. <i>Acta Informatica</i>. 2017;54(8):765-787. doi:<a href=\"https://doi.org/10.1007/s00236-016-0278-x\">10.1007/s00236-016-0278-x</a>","short":"M. Giacobbe, C.C. Guet, A. Gupta, T.A. Henzinger, T. Paixao, T. Petrov, Acta Informatica 54 (2017) 765–787."},"intvolume":"        54","file_date_updated":"2020-07-14T12:44:46Z","scopus_import":"1","ddc":["006","576"],"_id":"1351","abstract":[{"text":"The behaviour of gene regulatory networks (GRNs) is typically analysed using simulation-based statistical testing-like methods. In this paper, we demonstrate that we can replace this approach by a formal verification-like method that gives higher assurance and scalability. We focus on Wagner’s weighted GRN model with varying weights, which is used in evolutionary biology. In the model, weight parameters represent the gene interaction strength that may change due to genetic mutations. For a property of interest, we synthesise the constraints over the parameter space that represent the set of GRNs satisfying the property. We experimentally show that our parameter synthesis procedure computes the mutational robustness of GRNs—an important problem of interest in evolutionary biology—more efficiently than the classical simulation method. We specify the property in linear temporal logic. We employ symbolic bounded model checking and SMT solving to compute the space of GRNs that satisfy the property, which amounts to synthesizing a set of linear constraints on the weights.","lang":"eng"}],"issue":"8","date_updated":"2025-05-28T11:57:04Z","year":"2017","month":"12","ec_funded":1,"status":"public","oa":1,"publication_identifier":{"issn":["00015903"]}},{"title":"On the mechanistic nature of epistasis in a canonical cis-regulatory element","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","publisher":"eLife Sciences Publications","file":[{"content_type":"application/pdf","relation":"main_file","file_size":2441529,"date_updated":"2020-07-14T12:48:16Z","file_name":"IST-2017-841-v1+1_elife-25192-v2.pdf","date_created":"2018-12-12T10:17:49Z","file_id":"5306","creator":"system","checksum":"59cdd4400fb41280122d414fea971546","access_level":"open_access"},{"relation":"main_file","content_type":"application/pdf","file_size":3752660,"file_id":"5307","checksum":"b69024880558b858eb8c5d47a92b6377","creator":"system","access_level":"open_access","file_name":"IST-2017-841-v1+2_elife-25192-figures-v2.pdf","date_updated":"2020-07-14T12:48:16Z","date_created":"2018-12-12T10:17:50Z"}],"isi":1,"author":[{"full_name":"Lagator, Mato","id":"345D25EC-F248-11E8-B48F-1D18A9856A87","last_name":"Lagator","first_name":"Mato"},{"full_name":"Paixao, Tiago","id":"2C5658E6-F248-11E8-B48F-1D18A9856A87","last_name":"Paixao","first_name":"Tiago","orcid":"0000-0003-2361-3953"},{"id":"4880FE40-F248-11E8-B48F-1D18A9856A87","last_name":"Barton","orcid":"0000-0002-8548-5240","first_name":"Nicholas H","full_name":"Barton, Nicholas H"},{"last_name":"Bollback","id":"2C6FA9CC-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-4624-4612","first_name":"Jonathan P","full_name":"Bollback, Jonathan P"},{"id":"47F8433E-F248-11E8-B48F-1D18A9856A87","last_name":"Guet","first_name":"Calin C","orcid":"0000-0001-6220-2052","full_name":"Guet, Calin C"}],"project":[{"call_identifier":"FP7","name":"Speed of Adaptation in Population Genetics and Evolutionary Computation","grant_number":"618091","_id":"25B1EC9E-B435-11E9-9278-68D0E5697425"},{"_id":"25681D80-B435-11E9-9278-68D0E5697425","grant_number":"291734","name":"International IST Postdoc Fellowship Programme","call_identifier":"FP7"},{"_id":"2578D616-B435-11E9-9278-68D0E5697425","grant_number":"648440","name":"Selective Barriers to Horizontal Gene Transfer","call_identifier":"H2020"}],"day":"18","tmp":{"short":"CC BY (4.0)","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"quality_controlled":"1","volume":6,"external_id":{"isi":["000404024800001"]},"article_processing_charge":"Yes","pubrep_id":"841","publist_id":"6460","department":[{"_id":"CaGu"},{"_id":"NiBa"},{"_id":"JoBo"}],"language":[{"iso":"eng"}],"type":"journal_article","publication":"eLife","date_created":"2018-12-11T11:49:23Z","has_accepted_license":"1","ec_funded":1,"month":"05","oa":1,"publication_identifier":{"issn":["2050084X"]},"status":"public","_id":"954","article_number":"e25192","year":"2017","abstract":[{"text":"Understanding the relation between genotype and phenotype remains a major challenge. The difficulty of predicting individual mutation effects, and particularly the interactions between them, has prevented the development of a comprehensive theory that links genotypic changes to their phenotypic effects. We show that a general thermodynamic framework for gene regulation, based on a biophysical understanding of protein-DNA binding, accurately predicts the sign of epistasis in a canonical cis-regulatory element consisting of overlapping RNA polymerase and repressor binding sites. Sign and magnitude of individual mutation effects are sufficient to predict the sign of epistasis and its environmental dependence. Thus, the thermodynamic model offers the correct null prediction for epistasis between mutations across DNA-binding sites. Our results indicate that a predictive theory for the effects of cis-regulatory mutations is possible from first principles, as long as the essential molecular mechanisms and the constraints these impose on a biological system are accounted for.","lang":"eng"}],"date_updated":"2023-09-22T10:01:17Z","citation":{"apa":"Lagator, M., Paixao, T., Barton, N. H., Bollback, J. P., &#38; Guet, C. C. (2017). On the mechanistic nature of epistasis in a canonical cis-regulatory element. <i>ELife</i>. eLife Sciences Publications. <a href=\"https://doi.org/10.7554/eLife.25192\">https://doi.org/10.7554/eLife.25192</a>","ista":"Lagator M, Paixao T, Barton NH, Bollback JP, Guet CC. 2017. On the mechanistic nature of epistasis in a canonical cis-regulatory element. eLife. 6, e25192.","mla":"Lagator, Mato, et al. “On the Mechanistic Nature of Epistasis in a Canonical Cis-Regulatory Element.” <i>ELife</i>, vol. 6, e25192, eLife Sciences Publications, 2017, doi:<a href=\"https://doi.org/10.7554/eLife.25192\">10.7554/eLife.25192</a>.","chicago":"Lagator, Mato, Tiago Paixao, Nicholas H Barton, Jonathan P Bollback, and Calin C Guet. “On the Mechanistic Nature of Epistasis in a Canonical Cis-Regulatory Element.” <i>ELife</i>. eLife Sciences Publications, 2017. <a href=\"https://doi.org/10.7554/eLife.25192\">https://doi.org/10.7554/eLife.25192</a>.","short":"M. Lagator, T. Paixao, N.H. Barton, J.P. Bollback, C.C. Guet, ELife 6 (2017).","ama":"Lagator M, Paixao T, Barton NH, Bollback JP, Guet CC. On the mechanistic nature of epistasis in a canonical cis-regulatory element. <i>eLife</i>. 2017;6. doi:<a href=\"https://doi.org/10.7554/eLife.25192\">10.7554/eLife.25192</a>","ieee":"M. Lagator, T. Paixao, N. H. Barton, J. P. Bollback, and C. C. Guet, “On the mechanistic nature of epistasis in a canonical cis-regulatory element,” <i>eLife</i>, vol. 6. eLife Sciences Publications, 2017."},"intvolume":"         6","ddc":["576"],"scopus_import":"1","file_date_updated":"2020-07-14T12:48:16Z","date_published":"2017-05-18T00:00:00Z","oa_version":"Published Version","doi":"10.7554/eLife.25192","publication_status":"published"},{"date_created":"2021-08-09T14:02:34Z","doi":"10.1371/journal.pcbi.1005609.s001","date_published":"2017-07-18T00:00:00Z","department":[{"_id":"ToBo"},{"_id":"NiBa"},{"_id":"CaGu"}],"type":"research_data_reference","oa_version":"Published Version","article_processing_charge":"No","related_material":{"record":[{"id":"696","status":"public","relation":"used_in_publication"}]},"citation":{"ama":"Lukacisinova M, Novak S, Paixao T. Modelling and simulation details. 2017. doi:<a href=\"https://doi.org/10.1371/journal.pcbi.1005609.s001\">10.1371/journal.pcbi.1005609.s001</a>","ieee":"M. Lukacisinova, S. Novak, and T. Paixao, “Modelling and simulation details.” Public Library of Science, 2017.","short":"M. Lukacisinova, S. Novak, T. Paixao, (2017).","apa":"Lukacisinova, M., Novak, S., &#38; Paixao, T. (2017). Modelling and simulation details. Public Library of Science. <a href=\"https://doi.org/10.1371/journal.pcbi.1005609.s001\">https://doi.org/10.1371/journal.pcbi.1005609.s001</a>","mla":"Lukacisinova, Marta, et al. <i>Modelling and Simulation Details</i>. Public Library of Science, 2017, doi:<a href=\"https://doi.org/10.1371/journal.pcbi.1005609.s001\">10.1371/journal.pcbi.1005609.s001</a>.","ista":"Lukacisinova M, Novak S, Paixao T. 2017. Modelling and simulation details, Public Library of Science, <a href=\"https://doi.org/10.1371/journal.pcbi.1005609.s001\">10.1371/journal.pcbi.1005609.s001</a>.","chicago":"Lukacisinova, Marta, Sebastian Novak, and Tiago Paixao. “Modelling and Simulation Details.” Public Library of Science, 2017. <a href=\"https://doi.org/10.1371/journal.pcbi.1005609.s001\">https://doi.org/10.1371/journal.pcbi.1005609.s001</a>."},"year":"2017","day":"18","abstract":[{"lang":"eng","text":"This text provides additional information about the model, a derivation of the analytic results in Eq (4), and details about simulations of an additional parameter set."}],"date_updated":"2023-02-23T12:55:39Z","_id":"9849","author":[{"full_name":"Lukacisinova, Marta","id":"4342E402-F248-11E8-B48F-1D18A9856A87","last_name":"Lukacisinova","orcid":"0000-0002-2519-8004","first_name":"Marta"},{"full_name":"Novak, Sebastian","id":"461468AE-F248-11E8-B48F-1D18A9856A87","last_name":"Novak","first_name":"Sebastian"},{"first_name":"Tiago","orcid":"0000-0003-2361-3953","last_name":"Paixao","id":"2C5658E6-F248-11E8-B48F-1D18A9856A87","full_name":"Paixao, Tiago"}],"title":"Modelling and simulation details","user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","publisher":"Public Library of Science","status":"public","month":"07"},{"year":"2017","day":"18","abstract":[{"text":"In this text, we discuss how a cost of resistance and the possibility of lethal mutations impact our model.","lang":"eng"}],"date_updated":"2023-02-23T12:55:39Z","_id":"9850","author":[{"full_name":"Lukacisinova, Marta","last_name":"Lukacisinova","id":"4342E402-F248-11E8-B48F-1D18A9856A87","first_name":"Marta","orcid":"0000-0002-2519-8004"},{"id":"461468AE-F248-11E8-B48F-1D18A9856A87","last_name":"Novak","first_name":"Sebastian","full_name":"Novak, Sebastian"},{"orcid":"0000-0003-2361-3953","first_name":"Tiago","id":"2C5658E6-F248-11E8-B48F-1D18A9856A87","last_name":"Paixao","full_name":"Paixao, Tiago"}],"title":"Extensions of the model","user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","publisher":"Public Library of Science","status":"public","month":"07","date_created":"2021-08-09T14:05:24Z","doi":"10.1371/journal.pcbi.1005609.s002","department":[{"_id":"ToBo"},{"_id":"CaGu"},{"_id":"NiBa"}],"date_published":"2017-07-18T00:00:00Z","oa_version":"Published Version","type":"research_data_reference","article_processing_charge":"No","related_material":{"record":[{"relation":"used_in_publication","status":"public","id":"696"}]},"citation":{"chicago":"Lukacisinova, Marta, Sebastian Novak, and Tiago Paixao. “Extensions of the Model.” Public Library of Science, 2017. <a href=\"https://doi.org/10.1371/journal.pcbi.1005609.s002\">https://doi.org/10.1371/journal.pcbi.1005609.s002</a>.","mla":"Lukacisinova, Marta, et al. <i>Extensions of the Model</i>. Public Library of Science, 2017, doi:<a href=\"https://doi.org/10.1371/journal.pcbi.1005609.s002\">10.1371/journal.pcbi.1005609.s002</a>.","apa":"Lukacisinova, M., Novak, S., &#38; Paixao, T. (2017). Extensions of the model. Public Library of Science. <a href=\"https://doi.org/10.1371/journal.pcbi.1005609.s002\">https://doi.org/10.1371/journal.pcbi.1005609.s002</a>","ista":"Lukacisinova M, Novak S, Paixao T. 2017. Extensions of the model, Public Library of Science, <a href=\"https://doi.org/10.1371/journal.pcbi.1005609.s002\">10.1371/journal.pcbi.1005609.s002</a>.","ama":"Lukacisinova M, Novak S, Paixao T. Extensions of the model. 2017. doi:<a href=\"https://doi.org/10.1371/journal.pcbi.1005609.s002\">10.1371/journal.pcbi.1005609.s002</a>","ieee":"M. Lukacisinova, S. Novak, and T. Paixao, “Extensions of the model.” Public Library of Science, 2017.","short":"M. Lukacisinova, S. Novak, T. Paixao, (2017)."}},{"status":"public","publisher":"Public Library of Science","user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","title":"Heuristic prediction for multiple stresses","month":"07","date_updated":"2023-02-23T12:55:39Z","abstract":[{"lang":"eng","text":"Based on the intuitive derivation of the dynamics of SIM allele frequency pM in the main text, we present a heuristic prediction for the long-term SIM allele frequencies with χ > 1 stresses and compare it to numerical simulations."}],"day":"18","year":"2017","author":[{"orcid":"0000-0002-2519-8004","first_name":"Marta","id":"4342E402-F248-11E8-B48F-1D18A9856A87","last_name":"Lukacisinova","full_name":"Lukacisinova, Marta"},{"first_name":"Sebastian","id":"461468AE-F248-11E8-B48F-1D18A9856A87","last_name":"Novak","full_name":"Novak, Sebastian"},{"first_name":"Tiago","orcid":"0000-0003-2361-3953","last_name":"Paixao","id":"2C5658E6-F248-11E8-B48F-1D18A9856A87","full_name":"Paixao, Tiago"}],"_id":"9851","article_processing_charge":"No","citation":{"chicago":"Lukacisinova, Marta, Sebastian Novak, and Tiago Paixao. “Heuristic Prediction for Multiple Stresses.” Public Library of Science, 2017. <a href=\"https://doi.org/10.1371/journal.pcbi.1005609.s003\">https://doi.org/10.1371/journal.pcbi.1005609.s003</a>.","ista":"Lukacisinova M, Novak S, Paixao T. 2017. Heuristic prediction for multiple stresses, Public Library of Science, <a href=\"https://doi.org/10.1371/journal.pcbi.1005609.s003\">10.1371/journal.pcbi.1005609.s003</a>.","mla":"Lukacisinova, Marta, et al. <i>Heuristic Prediction for Multiple Stresses</i>. Public Library of Science, 2017, doi:<a href=\"https://doi.org/10.1371/journal.pcbi.1005609.s003\">10.1371/journal.pcbi.1005609.s003</a>.","apa":"Lukacisinova, M., Novak, S., &#38; Paixao, T. (2017). Heuristic prediction for multiple stresses. Public Library of Science. <a href=\"https://doi.org/10.1371/journal.pcbi.1005609.s003\">https://doi.org/10.1371/journal.pcbi.1005609.s003</a>","short":"M. Lukacisinova, S. Novak, T. Paixao, (2017).","ieee":"M. Lukacisinova, S. Novak, and T. Paixao, “Heuristic prediction for multiple stresses.” Public Library of Science, 2017.","ama":"Lukacisinova M, Novak S, Paixao T. Heuristic prediction for multiple stresses. 2017. doi:<a href=\"https://doi.org/10.1371/journal.pcbi.1005609.s003\">10.1371/journal.pcbi.1005609.s003</a>"},"related_material":{"record":[{"status":"public","relation":"used_in_publication","id":"696"}]},"doi":"10.1371/journal.pcbi.1005609.s003","date_created":"2021-08-09T14:08:14Z","type":"research_data_reference","oa_version":"Published Version","date_published":"2017-07-18T00:00:00Z","department":[{"_id":"ToBo"},{"_id":"CaGu"},{"_id":"NiBa"}]},{"year":"2017","day":"18","abstract":[{"lang":"eng","text":"We show how different combination strategies affect the fraction of individuals that are multi-resistant."}],"date_updated":"2023-02-23T12:55:39Z","_id":"9852","author":[{"last_name":"Lukacisinova","id":"4342E402-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-2519-8004","first_name":"Marta","full_name":"Lukacisinova, Marta"},{"full_name":"Novak, Sebastian","last_name":"Novak","id":"461468AE-F248-11E8-B48F-1D18A9856A87","first_name":"Sebastian"},{"full_name":"Paixao, Tiago","last_name":"Paixao","id":"2C5658E6-F248-11E8-B48F-1D18A9856A87","first_name":"Tiago","orcid":"0000-0003-2361-3953"}],"title":"Resistance frequencies for different combination strategies","user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","publisher":"Public Library of Science","status":"public","month":"07","date_created":"2021-08-09T14:11:40Z","doi":"10.1371/journal.pcbi.1005609.s004","date_published":"2017-07-18T00:00:00Z","department":[{"_id":"ToBo"},{"_id":"CaGu"},{"_id":"NiBa"}],"type":"research_data_reference","oa_version":"Published Version","article_processing_charge":"No","related_material":{"record":[{"status":"public","relation":"used_in_publication","id":"696"}]},"citation":{"ama":"Lukacisinova M, Novak S, Paixao T. Resistance frequencies for different combination strategies. 2017. doi:<a href=\"https://doi.org/10.1371/journal.pcbi.1005609.s004\">10.1371/journal.pcbi.1005609.s004</a>","ieee":"M. Lukacisinova, S. Novak, and T. Paixao, “Resistance frequencies for different combination strategies.” Public Library of Science, 2017.","short":"M. Lukacisinova, S. Novak, T. Paixao, (2017).","ista":"Lukacisinova M, Novak S, Paixao T. 2017. Resistance frequencies for different combination strategies, Public Library of Science, <a href=\"https://doi.org/10.1371/journal.pcbi.1005609.s004\">10.1371/journal.pcbi.1005609.s004</a>.","apa":"Lukacisinova, M., Novak, S., &#38; Paixao, T. (2017). Resistance frequencies for different combination strategies. Public Library of Science. <a href=\"https://doi.org/10.1371/journal.pcbi.1005609.s004\">https://doi.org/10.1371/journal.pcbi.1005609.s004</a>","mla":"Lukacisinova, Marta, et al. <i>Resistance Frequencies for Different Combination Strategies</i>. Public Library of Science, 2017, doi:<a href=\"https://doi.org/10.1371/journal.pcbi.1005609.s004\">10.1371/journal.pcbi.1005609.s004</a>.","chicago":"Lukacisinova, Marta, Sebastian Novak, and Tiago Paixao. “Resistance Frequencies for Different Combination Strategies.” Public Library of Science, 2017. <a href=\"https://doi.org/10.1371/journal.pcbi.1005609.s004\">https://doi.org/10.1371/journal.pcbi.1005609.s004</a>."}},{"pubrep_id":"650","publist_id":"5900","quality_controlled":"1","has_accepted_license":"1","publication":"Proceedings of the Genetic and Evolutionary Computation Conference 2016 ","page":"1163 - 1170","date_created":"2018-12-11T11:51:31Z","type":"conference","department":[{"_id":"NiBa"},{"_id":"CaGu"}],"language":[{"iso":"eng"}],"user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","publisher":"ACM","title":"When non-elitism outperforms elitism for crossing fitness valleys","tmp":{"short":"CC BY (4.0)","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"day":"20","author":[{"last_name":"Oliveto","first_name":"Pietro","full_name":"Oliveto, Pietro"},{"full_name":"Paixao, Tiago","id":"2C5658E6-F248-11E8-B48F-1D18A9856A87","last_name":"Paixao","orcid":"0000-0003-2361-3953","first_name":"Tiago"},{"full_name":"Heredia, Jorge","last_name":"Heredia","first_name":"Jorge"},{"first_name":"Dirk","last_name":"Sudholt","full_name":"Sudholt, Dirk"},{"full_name":"Trubenova, Barbora","orcid":"0000-0002-6873-2967","first_name":"Barbora","last_name":"Trubenova","id":"42302D54-F248-11E8-B48F-1D18A9856A87"}],"project":[{"grant_number":"618091","_id":"25B1EC9E-B435-11E9-9278-68D0E5697425","name":"Speed of Adaptation in Population Genetics and Evolutionary Computation","call_identifier":"FP7"}],"file":[{"access_level":"open_access","checksum":"a1896e39e4113f2711e46b435d5f3e69","creator":"system","file_id":"5214","date_created":"2018-12-12T10:16:27Z","date_updated":"2020-07-14T12:44:45Z","file_name":"IST-2016-650-v1+1_p1163-oliveto.pdf","file_size":979026,"content_type":"application/pdf","relation":"main_file"}],"file_date_updated":"2020-07-14T12:44:45Z","scopus_import":1,"ddc":["576"],"citation":{"short":"P. Oliveto, T. Paixao, J. Heredia, D. Sudholt, B. Trubenova, in:, Proceedings of the Genetic and Evolutionary Computation Conference 2016 , ACM, 2016, pp. 1163–1170.","ieee":"P. Oliveto, T. Paixao, J. Heredia, D. Sudholt, and B. Trubenova, “When non-elitism outperforms elitism for crossing fitness valleys,” in <i>Proceedings of the Genetic and Evolutionary Computation Conference 2016 </i>, Denver, CO, USA, 2016, pp. 1163–1170.","ama":"Oliveto P, Paixao T, Heredia J, Sudholt D, Trubenova B. When non-elitism outperforms elitism for crossing fitness valleys. In: <i>Proceedings of the Genetic and Evolutionary Computation Conference 2016 </i>. ACM; 2016:1163-1170. doi:<a href=\"https://doi.org/10.1145/2908812.2908909\">10.1145/2908812.2908909</a>","chicago":"Oliveto, Pietro, Tiago Paixao, Jorge Heredia, Dirk Sudholt, and Barbora Trubenova. “When Non-Elitism Outperforms Elitism for Crossing Fitness Valleys.” In <i>Proceedings of the Genetic and Evolutionary Computation Conference 2016 </i>, 1163–70. ACM, 2016. <a href=\"https://doi.org/10.1145/2908812.2908909\">https://doi.org/10.1145/2908812.2908909</a>.","apa":"Oliveto, P., Paixao, T., Heredia, J., Sudholt, D., &#38; Trubenova, B. (2016). When non-elitism outperforms elitism for crossing fitness valleys. In <i>Proceedings of the Genetic and Evolutionary Computation Conference 2016 </i> (pp. 1163–1170). Denver, CO, USA: ACM. <a href=\"https://doi.org/10.1145/2908812.2908909\">https://doi.org/10.1145/2908812.2908909</a>","mla":"Oliveto, Pietro, et al. “When Non-Elitism Outperforms Elitism for Crossing Fitness Valleys.” <i>Proceedings of the Genetic and Evolutionary Computation Conference 2016 </i>, ACM, 2016, pp. 1163–70, doi:<a href=\"https://doi.org/10.1145/2908812.2908909\">10.1145/2908812.2908909</a>.","ista":"Oliveto P, Paixao T, Heredia J, Sudholt D, Trubenova B. 2016. When non-elitism outperforms elitism for crossing fitness valleys. Proceedings of the Genetic and Evolutionary Computation Conference 2016 . GECCO: Genetic and evolutionary computation conference, 1163–1170."},"doi":"10.1145/2908812.2908909","publication_status":"published","conference":{"location":"Denver, CO, USA","end_date":"2016-07-24","name":"GECCO: Genetic and evolutionary computation conference","start_date":"2016-07-20"},"oa_version":"Published Version","date_published":"2016-07-20T00:00:00Z","status":"public","oa":1,"month":"07","ec_funded":1,"abstract":[{"lang":"eng","text":"Crossing fitness valleys is one of the major obstacles to function optimization. In this paper we investigate how the structure of the fitness valley, namely its depth d and length ℓ, influence the runtime of different strategies for crossing these valleys. We present a runtime comparison between the (1+1) EA and two non-elitist nature-inspired algorithms, Strong Selection Weak Mutation (SSWM) and the Metropolis algorithm. While the (1+1) EA has to jump across the valley to a point of higher fitness because it does not accept decreasing moves, the non-elitist algorithms may cross the valley by accepting worsening moves. We show that while the runtime of the (1+1) EA algorithm depends critically on the length of the valley, the runtimes of the non-elitist algorithms depend crucially only on the depth of the valley. In particular, the expected runtime of both SSWM and Metropolis is polynomial in ℓ and exponential in d while the (1+1) EA is efficient only for valleys of small length. Moreover, we show that both SSWM and Metropolis can also efficiently optimize a rugged function consisting of consecutive valleys."}],"date_updated":"2021-01-12T06:50:03Z","year":"2016","_id":"1349"},{"citation":{"short":"T. Paixao, N.H. Barton, PNAS 113 (2016) 4422–4427.","ieee":"T. Paixao and N. H. Barton, “The effect of gene interactions on the long-term response to selection,” <i>PNAS</i>, vol. 113, no. 16. National Academy of Sciences, pp. 4422–4427, 2016.","ama":"Paixao T, Barton NH. The effect of gene interactions on the long-term response to selection. <i>PNAS</i>. 2016;113(16):4422-4427. doi:<a href=\"https://doi.org/10.1073/pnas.1518830113\">10.1073/pnas.1518830113</a>","mla":"Paixao, Tiago, and Nicholas H. Barton. “The Effect of Gene Interactions on the Long-Term Response to Selection.” <i>PNAS</i>, vol. 113, no. 16, National Academy of Sciences, 2016, pp. 4422–27, doi:<a href=\"https://doi.org/10.1073/pnas.1518830113\">10.1073/pnas.1518830113</a>.","apa":"Paixao, T., &#38; Barton, N. H. (2016). The effect of gene interactions on the long-term response to selection. <i>PNAS</i>. National Academy of Sciences. <a href=\"https://doi.org/10.1073/pnas.1518830113\">https://doi.org/10.1073/pnas.1518830113</a>","ista":"Paixao T, Barton NH. 2016. The effect of gene interactions on the long-term response to selection. PNAS. 113(16), 4422–4427.","chicago":"Paixao, Tiago, and Nicholas H Barton. “The Effect of Gene Interactions on the Long-Term Response to Selection.” <i>PNAS</i>. National Academy of Sciences, 2016. <a href=\"https://doi.org/10.1073/pnas.1518830113\">https://doi.org/10.1073/pnas.1518830113</a>."},"intvolume":"       113","main_file_link":[{"open_access":"1","url":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4843425/"}],"scopus_import":1,"oa_version":"Published Version","date_published":"2016-04-19T00:00:00Z","publication_status":"published","doi":"10.1073/pnas.1518830113","month":"04","ec_funded":1,"status":"public","oa":1,"_id":"1359","date_updated":"2021-01-12T06:50:08Z","issue":"16","abstract":[{"text":"The role of gene interactions in the evolutionary process has long\r\nbeen controversial. Although some argue that they are not of\r\nimportance, because most variation is additive, others claim that\r\ntheir effect in the long term can be substantial. Here, we focus on\r\nthe long-term effects of genetic interactions under directional\r\nselection assuming no mutation or dominance, and that epistasis is\r\nsymmetrical overall. We ask by how much the mean of a complex\r\ntrait can be increased by selection and analyze two extreme\r\nregimes, in which either drift or selection dominate the dynamics\r\nof allele frequencies. In both scenarios, epistatic interactions affect\r\nthe long-term response to selection by modulating the additive\r\ngenetic variance. When drift dominates, we extend Robertson\r\n’\r\ns\r\n[Robertson A (1960)\r\nProc R Soc Lond B Biol Sci\r\n153(951):234\r\n−\r\n249]\r\nargument to show that, for any form of epistasis, the total response\r\nof a haploid population is proportional to the initial total genotypic\r\nvariance. In contrast, the total response of a diploid population is\r\nincreased by epistasis, for a given initial genotypic variance. When\r\nselection dominates, we show that the total selection response can\r\nonly be increased by epistasis when s\r\nome initially deleterious alleles\r\nbecome favored as the genetic background changes. We find a sim-\r\nple approximation for this effect and show that, in this regime, it is\r\nthe structure of the genotype - phenotype map that matters and not\r\nthe variance components of the population.","lang":"eng"}],"year":"2016","external_id":{"pmid":["27044080"]},"quality_controlled":"1","volume":113,"publist_id":"5886","article_type":"original","article_processing_charge":"No","type":"journal_article","language":[{"iso":"eng"}],"department":[{"_id":"NiBa"},{"_id":"CaGu"}],"page":"4422 - 4427","date_created":"2018-12-11T11:51:34Z","publication":"PNAS","publisher":"National Academy of Sciences","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","title":"The effect of gene interactions on the long-term response to selection","project":[{"_id":"25B07788-B435-11E9-9278-68D0E5697425","grant_number":"250152","call_identifier":"FP7","name":"Limits to selection in biology and in evolutionary computation"},{"_id":"25B1EC9E-B435-11E9-9278-68D0E5697425","grant_number":"618091","call_identifier":"FP7","name":"Speed of Adaptation in Population Genetics and Evolutionary Computation"}],"author":[{"last_name":"Paixao","id":"2C5658E6-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-2361-3953","first_name":"Tiago","full_name":"Paixao, Tiago"},{"full_name":"Barton, Nicholas H","id":"4880FE40-F248-11E8-B48F-1D18A9856A87","last_name":"Barton","first_name":"Nicholas H","orcid":"0000-0002-8548-5240"}],"pmid":1,"day":"19"},{"quality_controlled":"1","volume":11,"related_material":{"record":[{"id":"9712","relation":"research_data","status":"public"},{"status":"public","relation":"dissertation_contains","id":"1131"}]},"publist_id":"5483","pubrep_id":"463","type":"journal_article","language":[{"iso":"eng"}],"department":[{"_id":"NiBa"},{"_id":"CaGu"},{"_id":"GaTk"}],"has_accepted_license":"1","date_created":"2018-12-11T11:53:21Z","publication":"PLoS Genetics","publisher":"Public Library of Science","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","title":"Dynamics of transcription factor binding site evolution","project":[{"name":"Limits to selection in biology and in evolutionary computation","call_identifier":"FP7","_id":"25B07788-B435-11E9-9278-68D0E5697425","grant_number":"250152"}],"author":[{"orcid":"0000-0002-8523-0758","first_name":"Murat","id":"37C323C6-F248-11E8-B48F-1D18A9856A87","last_name":"Tugrul","full_name":"Tugrul, Murat"},{"full_name":"Paixao, Tiago","last_name":"Paixao","id":"2C5658E6-F248-11E8-B48F-1D18A9856A87","first_name":"Tiago","orcid":"0000-0003-2361-3953"},{"orcid":"0000-0002-8548-5240","first_name":"Nicholas H","last_name":"Barton","id":"4880FE40-F248-11E8-B48F-1D18A9856A87","full_name":"Barton, Nicholas H"},{"id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","last_name":"Tkacik","first_name":"Gasper","orcid":"0000-0002-6699-1455","full_name":"Tkacik, Gasper"}],"file":[{"file_name":"IST-2016-463-v1+1_journal.pgen.1005639.pdf","date_updated":"2020-07-14T12:45:10Z","date_created":"2018-12-12T10:07:58Z","creator":"system","file_id":"4657","checksum":"a4e72fca5ccf40ddacf4d08c8e46b554","access_level":"open_access","content_type":"application/pdf","relation":"main_file","file_size":2580778}],"tmp":{"short":"CC BY (4.0)","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"day":"06","citation":{"ieee":"M. Tugrul, T. Paixao, N. H. Barton, and G. Tkačik, “Dynamics of transcription factor binding site evolution,” <i>PLoS Genetics</i>, vol. 11, no. 11. Public Library of Science, 2015.","ama":"Tugrul M, Paixao T, Barton NH, Tkačik G. Dynamics of transcription factor binding site evolution. <i>PLoS Genetics</i>. 2015;11(11). doi:<a href=\"https://doi.org/10.1371/journal.pgen.1005639\">10.1371/journal.pgen.1005639</a>","short":"M. Tugrul, T. Paixao, N.H. Barton, G. Tkačik, PLoS Genetics 11 (2015).","apa":"Tugrul, M., Paixao, T., Barton, N. H., &#38; Tkačik, G. (2015). Dynamics of transcription factor binding site evolution. <i>PLoS Genetics</i>. Public Library of Science. <a href=\"https://doi.org/10.1371/journal.pgen.1005639\">https://doi.org/10.1371/journal.pgen.1005639</a>","mla":"Tugrul, Murat, et al. “Dynamics of Transcription Factor Binding Site Evolution.” <i>PLoS Genetics</i>, vol. 11, no. 11, Public Library of Science, 2015, doi:<a href=\"https://doi.org/10.1371/journal.pgen.1005639\">10.1371/journal.pgen.1005639</a>.","ista":"Tugrul M, Paixao T, Barton NH, Tkačik G. 2015. Dynamics of transcription factor binding site evolution. PLoS Genetics. 11(11).","chicago":"Tugrul, Murat, Tiago Paixao, Nicholas H Barton, and Gašper Tkačik. “Dynamics of Transcription Factor Binding Site Evolution.” <i>PLoS Genetics</i>. Public Library of Science, 2015. <a href=\"https://doi.org/10.1371/journal.pgen.1005639\">https://doi.org/10.1371/journal.pgen.1005639</a>."},"intvolume":"        11","file_date_updated":"2020-07-14T12:45:10Z","scopus_import":1,"ddc":["576"],"oa_version":"Published Version","date_published":"2015-11-06T00:00:00Z","publication_status":"published","doi":"10.1371/journal.pgen.1005639","month":"11","ec_funded":1,"status":"public","oa":1,"_id":"1666","date_updated":"2023-09-07T11:53:49Z","issue":"11","abstract":[{"lang":"eng","text":"Evolution of gene regulation is crucial for our understanding of the phenotypic differences between species, populations and individuals. Sequence-specific binding of transcription factors to the regulatory regions on the DNA is a key regulatory mechanism that determines gene expression and hence heritable phenotypic variation. We use a biophysical model for directional selection on gene expression to estimate the rates of gain and loss of transcription factor binding sites (TFBS) in finite populations under both point and insertion/deletion mutations. Our results show that these rates are typically slow for a single TFBS in an isolated DNA region, unless the selection is extremely strong. These rates decrease drastically with increasing TFBS length or increasingly specific protein-DNA interactions, making the evolution of sites longer than ∼ 10 bp unlikely on typical eukaryotic speciation timescales. Similarly, evolution converges to the stationary distribution of binding sequences very slowly, making the equilibrium assumption questionable. The availability of longer regulatory sequences in which multiple binding sites can evolve simultaneously, the presence of “pre-sites” or partially decayed old sites in the initial sequence, and biophysical cooperativity between transcription factors, can all facilitate gain of TFBS and reconcile theoretical calculations with timescales inferred from comparative genomics."}],"year":"2015"},{"date_updated":"2025-05-28T11:57:04Z","abstract":[{"text":"The behaviour of gene regulatory networks (GRNs) is typically analysed using simulation-based statistical testing-like methods. In this paper, we demonstrate that we can replace this approach by a formal verification-like method that gives higher assurance and scalability. We focus on Wagner’s weighted GRN model with varying weights, which is used in evolutionary biology. In the model, weight parameters represent the gene interaction strength that may change due to genetic mutations. For a property of interest, we synthesise the constraints over the parameter space that represent the set of GRNs satisfying the property. We experimentally show that our parameter synthesis procedure computes the mutational robustness of GRNs –an important problem of interest in evolutionary biology– more efficiently than the classical simulation method. We specify the property in linear temporal logics. We employ symbolic bounded model checking and SMT solving to compute the space of GRNs that satisfy the property, which amounts to synthesizing a set of linear constraints on the weights.","lang":"eng"}],"year":"2015","_id":"1835","status":"public","oa":1,"month":"04","ec_funded":1,"publication_status":"published","conference":{"location":"London, United Kingdom","end_date":"2015-04-18","name":"TACAS: Tools and Algorithms for the Construction and Analysis of Systems","start_date":"2015-04-11"},"doi":"10.1007/978-3-662-46681-0_47","oa_version":"Preprint","date_published":"2015-04-01T00:00:00Z","main_file_link":[{"open_access":"1","url":"http://arxiv.org/abs/1410.7704"}],"scopus_import":1,"citation":{"ama":"Giacobbe M, Guet CC, Gupta A, Henzinger TA, Paixao T, Petrov T. Model checking gene regulatory networks. 2015;9035:469-483. doi:<a href=\"https://doi.org/10.1007/978-3-662-46681-0_47\">10.1007/978-3-662-46681-0_47</a>","ieee":"M. Giacobbe, C. C. Guet, A. Gupta, T. A. Henzinger, T. Paixao, and T. Petrov, “Model checking gene regulatory networks,” vol. 9035. Springer, pp. 469–483, 2015.","short":"M. Giacobbe, C.C. Guet, A. Gupta, T.A. Henzinger, T. Paixao, T. Petrov, 9035 (2015) 469–483.","apa":"Giacobbe, M., Guet, C. C., Gupta, A., Henzinger, T. A., Paixao, T., &#38; Petrov, T. (2015). Model checking gene regulatory networks. Presented at the TACAS: Tools and Algorithms for the Construction and Analysis of Systems, London, United Kingdom: Springer. <a href=\"https://doi.org/10.1007/978-3-662-46681-0_47\">https://doi.org/10.1007/978-3-662-46681-0_47</a>","mla":"Giacobbe, Mirco, et al. <i>Model Checking Gene Regulatory Networks</i>. Vol. 9035, Springer, 2015, pp. 469–83, doi:<a href=\"https://doi.org/10.1007/978-3-662-46681-0_47\">10.1007/978-3-662-46681-0_47</a>.","ista":"Giacobbe M, Guet CC, Gupta A, Henzinger TA, Paixao T, Petrov T. 2015. Model checking gene regulatory networks. 9035, 469–483.","chicago":"Giacobbe, Mirco, Calin C Guet, Ashutosh Gupta, Thomas A Henzinger, Tiago Paixao, and Tatjana Petrov. “Model Checking Gene Regulatory Networks.” Lecture Notes in Computer Science. Springer, 2015. <a href=\"https://doi.org/10.1007/978-3-662-46681-0_47\">https://doi.org/10.1007/978-3-662-46681-0_47</a>."},"intvolume":"      9035","acknowledgement":"SNSF Early Postdoc.Mobility Fellowship, the grant number P2EZP2 148797.\r\n","day":"01","project":[{"grant_number":"267989","_id":"25EE3708-B435-11E9-9278-68D0E5697425","name":"Quantitative Reactive Modeling","call_identifier":"FP7"},{"_id":"25832EC2-B435-11E9-9278-68D0E5697425","grant_number":"S 11407_N23","name":"Rigorous Systems Engineering","call_identifier":"FWF"},{"name":"The Wittgenstein Prize","call_identifier":"FWF","grant_number":"Z211","_id":"25F42A32-B435-11E9-9278-68D0E5697425"},{"grant_number":"618091","_id":"25B1EC9E-B435-11E9-9278-68D0E5697425","call_identifier":"FP7","name":"Speed of Adaptation in Population Genetics and Evolutionary Computation"},{"name":"Limits to selection in biology and in evolutionary computation","call_identifier":"FP7","grant_number":"250152","_id":"25B07788-B435-11E9-9278-68D0E5697425"},{"_id":"25681D80-B435-11E9-9278-68D0E5697425","grant_number":"291734","call_identifier":"FP7","name":"International IST Postdoc Fellowship Programme"}],"author":[{"full_name":"Giacobbe, Mirco","id":"3444EA5E-F248-11E8-B48F-1D18A9856A87","last_name":"Giacobbe","orcid":"0000-0001-8180-0904","first_name":"Mirco"},{"full_name":"Guet, Calin C","first_name":"Calin C","orcid":"0000-0001-6220-2052","last_name":"Guet","id":"47F8433E-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Ashutosh","last_name":"Gupta","id":"335E5684-F248-11E8-B48F-1D18A9856A87","full_name":"Gupta, Ashutosh"},{"orcid":"0000−0002−2985−7724","first_name":"Thomas A","id":"40876CD8-F248-11E8-B48F-1D18A9856A87","last_name":"Henzinger","full_name":"Henzinger, Thomas A"},{"full_name":"Paixao, Tiago","first_name":"Tiago","orcid":"0000-0003-2361-3953","id":"2C5658E6-F248-11E8-B48F-1D18A9856A87","last_name":"Paixao"},{"full_name":"Petrov, Tatjana","id":"3D5811FC-F248-11E8-B48F-1D18A9856A87","last_name":"Petrov","first_name":"Tatjana","orcid":"0000-0002-9041-0905"}],"publisher":"Springer","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","title":"Model checking gene regulatory networks","alternative_title":["LNCS"],"series_title":"Lecture Notes in Computer Science","page":"469 - 483","date_created":"2018-12-11T11:54:16Z","type":"conference","language":[{"iso":"eng"}],"department":[{"_id":"ToHe"},{"_id":"CaGu"},{"_id":"NiBa"}],"publist_id":"5267","volume":9035,"quality_controlled":"1","related_material":{"record":[{"id":"1351","relation":"later_version","status":"public"}]}},{"license":"https://creativecommons.org/licenses/by-nc-nd/4.0/","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publisher":"Elsevier","title":"Toward a unifying framework for evolutionary processes","author":[{"full_name":"Paixao, Tiago","first_name":"Tiago","orcid":"0000-0003-2361-3953","last_name":"Paixao","id":"2C5658E6-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Badkobeh, Golnaz","first_name":"Golnaz","last_name":"Badkobeh"},{"id":"4880FE40-F248-11E8-B48F-1D18A9856A87","last_name":"Barton","orcid":"0000-0002-8548-5240","first_name":"Nicholas H","full_name":"Barton, Nicholas H"},{"first_name":"Doğan","last_name":"Çörüş","full_name":"Çörüş, Doğan"},{"last_name":"Dang","first_name":"Duccuong","full_name":"Dang, Duccuong"},{"last_name":"Friedrich","first_name":"Tobias","full_name":"Friedrich, Tobias"},{"first_name":"Per","last_name":"Lehre","full_name":"Lehre, Per"},{"full_name":"Sudholt, Dirk","last_name":"Sudholt","first_name":"Dirk"},{"last_name":"Sutton","first_name":"Andrew","full_name":"Sutton, Andrew"},{"last_name":"Trubenova","id":"42302D54-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-6873-2967","first_name":"Barbora","full_name":"Trubenova, Barbora"}],"project":[{"name":"Speed of Adaptation in Population Genetics and Evolutionary Computation","call_identifier":"FP7","grant_number":"618091","_id":"25B1EC9E-B435-11E9-9278-68D0E5697425"},{"name":"Limits to selection in biology and in evolutionary computation","call_identifier":"FP7","_id":"25B07788-B435-11E9-9278-68D0E5697425","grant_number":"250152"}],"file":[{"file_size":595307,"content_type":"application/pdf","relation":"main_file","date_created":"2018-12-12T10:16:53Z","file_name":"IST-2016-483-v1+1_1-s2.0-S0022519315003409-main.pdf","date_updated":"2020-07-14T12:45:01Z","access_level":"open_access","checksum":"33b60ecfea60764756a9ee9df5eb65ca","file_id":"5244","creator":"system"}],"tmp":{"name":"Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)","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"},"day":"21","quality_controlled":"1","volume":383,"pubrep_id":"483","publist_id":"5629","type":"journal_article","department":[{"_id":"NiBa"},{"_id":"CaGu"}],"language":[{"iso":"eng"}],"has_accepted_license":"1","publication":" Journal of Theoretical Biology","date_created":"2018-12-11T11:52:37Z","page":"28 - 43","month":"10","ec_funded":1,"status":"public","oa":1,"_id":"1542","abstract":[{"text":"The theory of population genetics and evolutionary computation have been evolving separately for nearly 30 years. Many results have been independently obtained in both fields and many others are unique to its respective field. We aim to bridge this gap by developing a unifying framework for evolutionary processes that allows both evolutionary algorithms and population genetics models to be cast in the same formal framework. The framework we present here decomposes the evolutionary process into its several components in order to facilitate the identification of similarities between different models. In particular, we propose a classification of evolutionary operators based on the defining properties of the different components. We cast several commonly used operators from both fields into this common framework. Using this, we map different evolutionary and genetic algorithms to different evolutionary regimes and identify candidates with the most potential for the translation of results between the fields. This provides a unified description of evolutionary processes and represents a stepping stone towards new tools and results to both fields. ","lang":"eng"}],"date_updated":"2021-01-12T06:51:29Z","year":"2015","citation":{"short":"T. Paixao, G. Badkobeh, N.H. Barton, D. Çörüş, D. Dang, T. Friedrich, P. Lehre, D. Sudholt, A. Sutton, B. Trubenova,  Journal of Theoretical Biology 383 (2015) 28–43.","ieee":"T. Paixao <i>et al.</i>, “Toward a unifying framework for evolutionary processes,” <i> Journal of Theoretical Biology</i>, vol. 383. Elsevier, pp. 28–43, 2015.","ama":"Paixao T, Badkobeh G, Barton NH, et al. Toward a unifying framework for evolutionary processes. <i> Journal of Theoretical Biology</i>. 2015;383:28-43. doi:<a href=\"https://doi.org/10.1016/j.jtbi.2015.07.011\">10.1016/j.jtbi.2015.07.011</a>","chicago":"Paixao, Tiago, Golnaz Badkobeh, Nicholas H Barton, Doğan Çörüş, Duccuong Dang, Tobias Friedrich, Per Lehre, Dirk Sudholt, Andrew Sutton, and Barbora Trubenova. “Toward a Unifying Framework for Evolutionary Processes.” <i> Journal of Theoretical Biology</i>. Elsevier, 2015. <a href=\"https://doi.org/10.1016/j.jtbi.2015.07.011\">https://doi.org/10.1016/j.jtbi.2015.07.011</a>.","apa":"Paixao, T., Badkobeh, G., Barton, N. H., Çörüş, D., Dang, D., Friedrich, T., … Trubenova, B. (2015). Toward a unifying framework for evolutionary processes. <i> Journal of Theoretical Biology</i>. Elsevier. <a href=\"https://doi.org/10.1016/j.jtbi.2015.07.011\">https://doi.org/10.1016/j.jtbi.2015.07.011</a>","ista":"Paixao T, Badkobeh G, Barton NH, Çörüş D, Dang D, Friedrich T, Lehre P, Sudholt D, Sutton A, Trubenova B. 2015. Toward a unifying framework for evolutionary processes.  Journal of Theoretical Biology. 383, 28–43.","mla":"Paixao, Tiago, et al. “Toward a Unifying Framework for Evolutionary Processes.” <i> Journal of Theoretical Biology</i>, vol. 383, Elsevier, 2015, pp. 28–43, doi:<a href=\"https://doi.org/10.1016/j.jtbi.2015.07.011\">10.1016/j.jtbi.2015.07.011</a>."},"intvolume":"       383","file_date_updated":"2020-07-14T12:45:01Z","scopus_import":1,"ddc":["570"],"oa_version":"Published Version","date_published":"2015-10-21T00:00:00Z","doi":"10.1016/j.jtbi.2015.07.011","publication_status":"published"},{"quality_controlled":"1","citation":{"short":"T. Paixao, D. Sudholt, J. Heredia, B. Trubenova, in:, Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation, ACM, 2015, pp. 1455–1462.","ama":"Paixao T, Sudholt D, Heredia J, Trubenova B. First steps towards a runtime comparison of natural and artificial evolution. In: <i>Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation</i>. ACM; 2015:1455-1462. doi:<a href=\"https://doi.org/10.1145/2739480.2754758\">10.1145/2739480.2754758</a>","ieee":"T. Paixao, D. Sudholt, J. Heredia, and B. Trubenova, “First steps towards a runtime comparison of natural and artificial evolution,” in <i>Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation</i>, Madrid, Spain, 2015, pp. 1455–1462.","chicago":"Paixao, Tiago, Dirk Sudholt, Jorge Heredia, and Barbora Trubenova. “First Steps towards a Runtime Comparison of Natural and Artificial Evolution.” In <i>Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation</i>, 1455–62. ACM, 2015. <a href=\"https://doi.org/10.1145/2739480.2754758\">https://doi.org/10.1145/2739480.2754758</a>.","mla":"Paixao, Tiago, et al. “First Steps towards a Runtime Comparison of Natural and Artificial Evolution.” <i>Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation</i>, ACM, 2015, pp. 1455–62, doi:<a href=\"https://doi.org/10.1145/2739480.2754758\">10.1145/2739480.2754758</a>.","apa":"Paixao, T., Sudholt, D., Heredia, J., &#38; Trubenova, B. (2015). First steps towards a runtime comparison of natural and artificial evolution. In <i>Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation</i> (pp. 1455–1462). Madrid, Spain: ACM. <a href=\"https://doi.org/10.1145/2739480.2754758\">https://doi.org/10.1145/2739480.2754758</a>","ista":"Paixao T, Sudholt D, Heredia J, Trubenova B. 2015. First steps towards a runtime comparison of natural and artificial evolution. Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation. GECCO: Genetic and evolutionary computation conference, 1455–1462."},"main_file_link":[{"url":"http://arxiv.org/abs/1504.06260","open_access":"1"}],"publist_id":"5768","scopus_import":1,"type":"conference","oa_version":"Preprint","language":[{"iso":"eng"}],"department":[{"_id":"NiBa"},{"_id":"CaGu"}],"date_published":"2015-07-11T00:00:00Z","conference":{"end_date":"2015-07-15","location":"Madrid, Spain","start_date":"2015-07-11","name":"GECCO: Genetic and evolutionary computation conference"},"publication_status":"published","doi":"10.1145/2739480.2754758","date_created":"2018-12-11T11:51:58Z","page":"1455 - 1462","publication":"Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation","month":"07","ec_funded":1,"publisher":"ACM","status":"public","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","title":"First steps towards a runtime comparison of natural and artificial evolution","oa":1,"project":[{"_id":"25B1EC9E-B435-11E9-9278-68D0E5697425","grant_number":"618091","call_identifier":"FP7","name":"Speed of Adaptation in Population Genetics and Evolutionary Computation"}],"author":[{"full_name":"Paixao, Tiago","first_name":"Tiago","orcid":"0000-0003-2361-3953","last_name":"Paixao","id":"2C5658E6-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Sudholt, Dirk","last_name":"Sudholt","first_name":"Dirk"},{"last_name":"Heredia","first_name":"Jorge","full_name":"Heredia, Jorge"},{"id":"42302D54-F248-11E8-B48F-1D18A9856A87","last_name":"Trubenova","first_name":"Barbora","orcid":"0000-0002-6873-2967","full_name":"Trubenova, Barbora"}],"_id":"1430","date_updated":"2021-01-12T06:50:41Z","abstract":[{"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 their runtime 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 occurrence of new mutations is much longer than the time it takes for a new beneficial mutation to take over the population. In this situation, the population only contains copies of one genotype and evolution can be modelled as a (1+1)-type process where the probability of accepting a new genotype (improvements or worsenings) depends on the change in fitness. We present an initial runtime analysis of SSWM, quantifying its performance for various parameters and investigating differences to the (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.","lang":"eng"}],"day":"11","year":"2015"},{"user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","status":"public","publisher":"Public Library of Science","title":"Other fitness models for comparison & for interacting TFBSs","month":"11","date_updated":"2025-05-28T11:57:04Z","year":"2015","day":"06","author":[{"full_name":"Tugrul, Murat","id":"37C323C6-F248-11E8-B48F-1D18A9856A87","last_name":"Tugrul","orcid":"0000-0002-8523-0758","first_name":"Murat"},{"full_name":"Paixao, Tiago","orcid":"0000-0003-2361-3953","first_name":"Tiago","last_name":"Paixao","id":"2C5658E6-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Barton, Nicholas H","first_name":"Nicholas H","orcid":"0000-0002-8548-5240","last_name":"Barton","id":"4880FE40-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Tkačik, Gašper","last_name":"Tkačik","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-6699-1455","first_name":"Gašper"}],"_id":"9712","article_processing_charge":"No","citation":{"short":"M. Tugrul, T. Paixao, N.H. Barton, G. Tkačik, (2015).","ieee":"M. Tugrul, T. Paixao, N. H. Barton, and G. Tkačik, “Other fitness models for comparison &#38; for interacting TFBSs.” Public Library of Science, 2015.","ama":"Tugrul M, Paixao T, Barton NH, Tkačik G. Other fitness models for comparison &#38; for interacting TFBSs. 2015. doi:<a href=\"https://doi.org/10.1371/journal.pgen.1005639.s001\">10.1371/journal.pgen.1005639.s001</a>","mla":"Tugrul, Murat, et al. <i>Other Fitness Models for Comparison &#38; for Interacting TFBSs</i>. Public Library of Science, 2015, doi:<a href=\"https://doi.org/10.1371/journal.pgen.1005639.s001\">10.1371/journal.pgen.1005639.s001</a>.","ista":"Tugrul M, Paixao T, Barton NH, Tkačik G. 2015. Other fitness models for comparison &#38; for interacting TFBSs, Public Library of Science, <a href=\"https://doi.org/10.1371/journal.pgen.1005639.s001\">10.1371/journal.pgen.1005639.s001</a>.","apa":"Tugrul, M., Paixao, T., Barton, N. H., &#38; Tkačik, G. (2015). Other fitness models for comparison &#38; for interacting TFBSs. Public Library of Science. <a href=\"https://doi.org/10.1371/journal.pgen.1005639.s001\">https://doi.org/10.1371/journal.pgen.1005639.s001</a>","chicago":"Tugrul, Murat, Tiago Paixao, Nicholas H Barton, and Gašper Tkačik. “Other Fitness Models for Comparison &#38; for Interacting TFBSs.” Public Library of Science, 2015. <a href=\"https://doi.org/10.1371/journal.pgen.1005639.s001\">https://doi.org/10.1371/journal.pgen.1005639.s001</a>."},"related_material":{"record":[{"id":"1666","relation":"used_in_publication","status":"public"}]},"doi":"10.1371/journal.pgen.1005639.s001","date_created":"2021-07-23T12:00:37Z","type":"research_data_reference","oa_version":"Published Version","department":[{"_id":"NiBa"},{"_id":"CaGu"},{"_id":"GaTk"}],"date_published":"2015-11-06T00:00:00Z"},{"month":"07","status":"public","publisher":"National Academy of Sciences","user_id":"4435EBFC-F248-11E8-B48F-1D18A9856A87","title":"Diverse forms of selection in evolution and computer science","oa":1,"author":[{"full_name":"Barton, Nicholas H","orcid":"0000-0002-8548-5240","first_name":"Nicholas H","id":"4880FE40-F248-11E8-B48F-1D18A9856A87","last_name":"Barton"},{"full_name":"Novak, Sebastian","id":"461468AE-F248-11E8-B48F-1D18A9856A87","last_name":"Novak","first_name":"Sebastian"},{"full_name":"Paixao, Tiago","first_name":"Tiago","orcid":"0000-0003-2361-3953","id":"2C5658E6-F248-11E8-B48F-1D18A9856A87","last_name":"Paixao"}],"_id":"2169","date_updated":"2021-01-12T06:55:45Z","issue":"29","day":"22","year":"2014","citation":{"ama":"Barton NH, Novak S, Paixao T. Diverse forms of selection in evolution and computer science. <i>PNAS</i>. 2014;111(29):10398-10399. doi:<a href=\"https://doi.org/10.1073/pnas.1410107111\">10.1073/pnas.1410107111</a>","ieee":"N. H. Barton, S. Novak, and T. Paixao, “Diverse forms of selection in evolution and computer science,” <i>PNAS</i>, vol. 111, no. 29. National Academy of Sciences, pp. 10398–10399, 2014.","short":"N.H. Barton, S. Novak, T. Paixao, PNAS 111 (2014) 10398–10399.","chicago":"Barton, Nicholas H, Sebastian Novak, and Tiago Paixao. “Diverse Forms of Selection in Evolution and Computer Science.” <i>PNAS</i>. National Academy of Sciences, 2014. <a href=\"https://doi.org/10.1073/pnas.1410107111\">https://doi.org/10.1073/pnas.1410107111</a>.","mla":"Barton, Nicholas H., et al. “Diverse Forms of Selection in Evolution and Computer Science.” <i>PNAS</i>, vol. 111, no. 29, National Academy of Sciences, 2014, pp. 10398–99, doi:<a href=\"https://doi.org/10.1073/pnas.1410107111\">10.1073/pnas.1410107111</a>.","apa":"Barton, N. H., Novak, S., &#38; Paixao, T. (2014). Diverse forms of selection in evolution and computer science. <i>PNAS</i>. National Academy of Sciences. <a href=\"https://doi.org/10.1073/pnas.1410107111\">https://doi.org/10.1073/pnas.1410107111</a>","ista":"Barton NH, Novak S, Paixao T. 2014. Diverse forms of selection in evolution and computer science. PNAS. 111(29), 10398–10399."},"quality_controlled":"1","intvolume":"       111","volume":111,"publist_id":"4815","scopus_import":1,"main_file_link":[{"open_access":"1","url":"http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4115508/"}],"oa_version":"Submitted Version","type":"journal_article","language":[{"iso":"eng"}],"date_published":"2014-07-22T00:00:00Z","department":[{"_id":"NiBa"}],"publication_status":"published","doi":"10.1073/pnas.1410107111","page":"10398 - 10399","date_created":"2018-12-11T11:56:07Z","publication":"PNAS"},{"language":[{"iso":"eng"}],"date_published":"2014-01-01T00:00:00Z","department":[{"_id":"NiBa"}],"oa_version":"None","type":"journal_article","page":"130 - 135","date_created":"2018-12-11T11:56:35Z","publication":"Journal of Heredity","publication_status":"published","doi":"10.1093/jhered/est063","citation":{"ieee":"S. Phadke, T. Paixao, T. Pham, S. Pham, and R. Zufall, “Genetic background alters dominance relationships between mat alleles in the ciliate Tetrahymena Thermophila,” <i>Journal of Heredity</i>, vol. 105, no. 1. Oxford University Press, pp. 130–135, 2014.","ama":"Phadke S, Paixao T, Pham T, Pham S, Zufall R. Genetic background alters dominance relationships between mat alleles in the ciliate Tetrahymena Thermophila. <i>Journal of Heredity</i>. 2014;105(1):130-135. doi:<a href=\"https://doi.org/10.1093/jhered/est063\">10.1093/jhered/est063</a>","short":"S. Phadke, T. Paixao, T. Pham, S. Pham, R. Zufall, Journal of Heredity 105 (2014) 130–135.","chicago":"Phadke, Sujal, Tiago Paixao, Tuan Pham, Stephanie Pham, and Rebecca Zufall. “Genetic Background Alters Dominance Relationships between Mat Alleles in the Ciliate Tetrahymena Thermophila.” <i>Journal of Heredity</i>. Oxford University Press, 2014. <a href=\"https://doi.org/10.1093/jhered/est063\">https://doi.org/10.1093/jhered/est063</a>.","mla":"Phadke, Sujal, et al. “Genetic Background Alters Dominance Relationships between Mat Alleles in the Ciliate Tetrahymena Thermophila.” <i>Journal of Heredity</i>, vol. 105, no. 1, Oxford University Press, 2014, pp. 130–35, doi:<a href=\"https://doi.org/10.1093/jhered/est063\">10.1093/jhered/est063</a>.","apa":"Phadke, S., Paixao, T., Pham, T., Pham, S., &#38; Zufall, R. (2014). Genetic background alters dominance relationships between mat alleles in the ciliate Tetrahymena Thermophila. <i>Journal of Heredity</i>. Oxford University Press. <a href=\"https://doi.org/10.1093/jhered/est063\">https://doi.org/10.1093/jhered/est063</a>","ista":"Phadke S, Paixao T, Pham T, Pham S, Zufall R. 2014. Genetic background alters dominance relationships between mat alleles in the ciliate Tetrahymena Thermophila. Journal of Heredity. 105(1), 130–135."},"intvolume":"       105","volume":105,"quality_controlled":"1","scopus_import":"1","publist_id":"4695","article_processing_charge":"No","_id":"2252","author":[{"last_name":"Phadke","first_name":"Sujal","full_name":"Phadke, Sujal"},{"full_name":"Paixao, Tiago","id":"2C5658E6-F248-11E8-B48F-1D18A9856A87","last_name":"Paixao","orcid":"0000-0003-2361-3953","first_name":"Tiago"},{"full_name":"Pham, Tuan","last_name":"Pham","first_name":"Tuan"},{"last_name":"Pham","first_name":"Stephanie","full_name":"Pham, Stephanie"},{"last_name":"Zufall","first_name":"Rebecca","full_name":"Zufall, Rebecca"}],"day":"01","year":"2014","date_updated":"2022-08-25T14:45:42Z","abstract":[{"lang":"eng","text":"The pattern of inheritance and mechanism of sex determination can have important evolutionary consequences. We studied probabilistic sex determination in the ciliate Tetrahymena thermophila, which was previously shown to cause evolution of skewed sex ratios. We find that the genetic background alters the sex determination patterns of mat alleles in heterozygotes and that allelic interaction can differentially influence the expression probability of the 7 sexes. We quantify the dominance relationships between several mat alleles and find that A-type alleles, which specify sex I, are indeed recessive to B-type alleles, which are unable to specify that sex. Our results provide additional support for the presence of modifier loci and raise implications for the dynamics of sex ratios in populations of T. thermophila."}],"issue":"1","month":"01","title":"Genetic background alters dominance relationships between mat alleles in the ciliate Tetrahymena Thermophila","publication_identifier":{"issn":["00221503"]},"publisher":"Oxford University Press","status":"public","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87"}]