Evolved Modular Epistasis in Artificial Organisms
How does complexity evolve in artificial and natural systems? A central concept within genetic systems is epistasis, namely the modulation of the effects of a given gene by one or sev- eral other genes. Epistasis is known to have an impact on many features of organisms, from recombination and sex to the ruggedness of the underlying fitness landscapes. How- ever, the multi-scale nature of evolution and organisms makes often difficult to properly characterize epistatic interactions. Here we study the hierarchical organization of epistatic inter- actions between machine instructions in evolved digital or- ganisms. We present a new quantitative approach to discover epistatic interactions that is able to capture the presence and role of groups of epistatic modules. Therefore, it thus takes into account the intrinsic nested nature of individual complex- ity. We found evidences of modular epistasis in avidians, with some modules having a tendency toward antagonistic epis- tasis while others show the opposite epistatic sign. We also found that this modular organization was positively correlated to organismal robustness.
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Massachusetts Institute of Technology
2012
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Online Access: | http://hdl.handle.net/10261/112546 http://dx.doi.org/10.13039/501100004837 http://dx.doi.org/10.13039/100000925 http://dx.doi.org/10.13039/100011419 |
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dig-ibe-es-10261-1125462018-10-03T10:17:11Z Evolved Modular Epistasis in Artificial Organisms Valverde, Sergi Solé, Ricard V. Elena, Santiago F. Ministerio de Ciencia e Innovación (España) John Templeton Foundation Santa Fe Institute (US) How does complexity evolve in artificial and natural systems? A central concept within genetic systems is epistasis, namely the modulation of the effects of a given gene by one or sev- eral other genes. Epistasis is known to have an impact on many features of organisms, from recombination and sex to the ruggedness of the underlying fitness landscapes. How- ever, the multi-scale nature of evolution and organisms makes often difficult to properly characterize epistatic interactions. Here we study the hierarchical organization of epistatic inter- actions between machine instructions in evolved digital or- ganisms. We present a new quantitative approach to discover epistatic interactions that is able to capture the presence and role of groups of epistatic modules. Therefore, it thus takes into account the intrinsic nested nature of individual complex- ity. We found evidences of modular epistasis in avidians, with some modules having a tendency toward antagonistic epis- tasis while others show the opposite epistatic sign. We also found that this modular organization was positively correlated to organismal robustness. This work was supported by the Spanish Ministerio de Ciencia e Innovación grants BFU2009-06993 (SFE) and FIS2009-12365 (RVS), the James McDonnell Foundation (RVS), the Marcelino Botin Foundation (RVS), the John Templeton Foundation (SFE), and the Santa Fe Institute (RVS andSFE). Peer Reviewed 2015-03-17T13:43:44Z 2015-03-17T13:43:44Z 2012 2015-03-17T13:43:44Z artículo http://purl.org/coar/resource_type/c_6501 doi: 10.7551/978-0-262-31050-5-ch016 issn: 1064-5462 e-issn: 1530-9185 Artificial Life 13: 111-115 (2012) http://hdl.handle.net/10261/112546 10.7551/978-0-262-31050-5-ch016 http://dx.doi.org/10.13039/501100004837 http://dx.doi.org/10.13039/100000925 http://dx.doi.org/10.13039/100011419 Publisher's version http://dx.doi.org/10.7551/978-0-262-31050-5-ch016 Sí open Massachusetts Institute of Technology |
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How does complexity evolve in artificial and natural systems? A central concept within genetic systems is epistasis, namely the modulation of the effects of a given gene by one or sev- eral other genes. Epistasis is known to have an impact on many features of organisms, from recombination and sex to the ruggedness of the underlying fitness landscapes. How- ever, the multi-scale nature of evolution and organisms makes often difficult to properly characterize epistatic interactions. Here we study the hierarchical organization of epistatic inter- actions between machine instructions in evolved digital or- ganisms. We present a new quantitative approach to discover epistatic interactions that is able to capture the presence and role of groups of epistatic modules. Therefore, it thus takes into account the intrinsic nested nature of individual complex- ity. We found evidences of modular epistasis in avidians, with some modules having a tendency toward antagonistic epis- tasis while others show the opposite epistatic sign. We also found that this modular organization was positively correlated to organismal robustness. |
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Ministerio de Ciencia e Innovación (España) |
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Ministerio de Ciencia e Innovación (España) Valverde, Sergi Solé, Ricard V. Elena, Santiago F. |
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Valverde, Sergi Solé, Ricard V. Elena, Santiago F. |
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Valverde, Sergi Solé, Ricard V. Elena, Santiago F. Evolved Modular Epistasis in Artificial Organisms |
author_sort |
Valverde, Sergi |
title |
Evolved Modular Epistasis in Artificial Organisms |
title_short |
Evolved Modular Epistasis in Artificial Organisms |
title_full |
Evolved Modular Epistasis in Artificial Organisms |
title_fullStr |
Evolved Modular Epistasis in Artificial Organisms |
title_full_unstemmed |
Evolved Modular Epistasis in Artificial Organisms |
title_sort |
evolved modular epistasis in artificial organisms |
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Massachusetts Institute of Technology |
publishDate |
2012 |
url |
http://hdl.handle.net/10261/112546 http://dx.doi.org/10.13039/501100004837 http://dx.doi.org/10.13039/100000925 http://dx.doi.org/10.13039/100011419 |
work_keys_str_mv |
AT valverdesergi evolvedmodularepistasisinartificialorganisms AT solericardv evolvedmodularepistasisinartificialorganisms AT elenasantiagof evolvedmodularepistasisinartificialorganisms |
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1777668589853081600 |