What Evolutionary Biologists Can Learn from Artificial Life
| dc.centro | E.T.S.I. Informática | en_US |
| dc.contributor.author | Elena Fito, Santiago | |
| dc.date.accessioned | 2019-04-11T10:55:22Z | |
| dc.date.available | 2019-04-11T10:55:22Z | |
| dc.date.created | 2019-04-10 | |
| dc.date.issued | 2019-04-11 | |
| dc.departamento | Lenguajes y Ciencias de la Computación | |
| dc.description.abstract | Big questions in Evolutionary Biology and experimental limitations - The evolution of complex traits. - The role of neutral variation in adaptive evolution. - Selection for fitness vs selection for robustness. - The topography of adaptive landscapes and the evolution of landscapes. - Eco-evolutionary dynamics: how evolution changes ecology and how ecology modulates evolution. - Evolution of phenotype-genotype maps. - The evolution of genetic systems (sex, speciation, genome architecture). The advantages of microbial Experimental Evolution - They are easy to propagate and enumerate. - They reproduce quickly, which allows experiments to run for many generations. - They allow large populations in small spaces, which facilitates experimental replication. -They can be stored in suspended animation and later revived, which allows the direct comparison of ancestral and evolved types. -Many microbes reproduce asexually and the resulting clonality enhances the precision of experimental replication. -Asexuality also maintains linkage between a genetic marker and the genomic background into which it is placed, which facilitates fitness measurements. -It is easy to manipulate environmental variables, such as resources, as well as the genetic composition of founding populations. - There are abundant molecular and genomic data for many species, as well as techniques for their precise genetic analysis and manipulation. | en_US |
| dc.description.sponsorship | Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. BitLab (http://www.bitlab-es.com) Universidad de Málaga | en_US |
| dc.identifier.uri | https://hdl.handle.net/10630/17522 | |
| dc.language.iso | spa | en_US |
| dc.relation.eventdate | 10/4/2019 | en_US |
| dc.relation.eventplace | Málaga, España | en_US |
| dc.relation.eventtitle | Conferencia | en_US |
| dc.rights.accessRights | open access | en_US |
| dc.subject | Biología | en_US |
| dc.subject | Evolución | en_US |
| dc.subject | Bioinformática | en_US |
| dc.subject.other | Evolutionary | en_US |
| dc.subject.other | Biology | en_US |
| dc.subject.other | Bioinformatics | en_US |
| dc.title | What Evolutionary Biologists Can Learn from Artificial Life | en_US |
| dc.type | conference output | en_US |
| dspace.entity.type | Publication |
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