503,962 research outputs found

    Explorations Volume 3 Fall 2012

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    Explorations Volume 2 Fall 2011

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    Explorations Volume 4 Fall 2013

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    Explorations Volume 1 Fall 2010

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    The Morphogenesis Of Evolutionary Developmental Biology

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    The early studies of evolutionary developmental biology (Evo-Devo) come from several sources. Tributaries flowing into Evo-Devo came from such disciplines as embryology, developmental genetics, evolutionary biology, ecology, paleontology, systematics, medical embryology and mathematical modeling. This essay will trace one of the major pathways, that from evolutionary embryology to Evo-Devo and it will show the interactions of this pathway with two other sources of Evo-Devo: ecological developmental biology and medical developmental biology. Together, these three fields are forming a more inclusive evolutionary developmental biology that is revitalizing and providing answers to old and important questions involving the formation of biodiversity on Earth. The phenotype of Evo-Devo is limited by internal constraints on what could be known given the methods and equipment of the time and it has been framed by external factors that include both academic and global politics

    GMOD for Evolutionary Biology

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    The Generic Model Organism Database (GMOD, "http://gmod.org":http://gmod.org) project provides interoperable, open source software tools for managing, visualizing and annotating biological data. GMOD is also a community of people addressing common challenges with biological data. Some well known software in GMOD includes GBrowse and JBrowse for genome browsing, Apollo for genome annotation, Chado for managing data, CMap for comparative map viewing, Galaxy for workflow creation and persistence, and BioMart for warehousing biological data.

This talk will focus on three areas of particular interest to iEvoBio participants. 
1) GBrowse_syn comparative genomics viewer
2) Natural Diversity Module of the Chado database schema
3) GMOD evolutionary biology hackathon 

The GBrowse_syn comparative genomics viewer displays synteny between a reference and any number of related species. It shows inversions, duplications, and indels, and can show synteny across non-contiguous regions. It is built on the widely used GBrowse genome viewer. The Natural Diversity Module is an extension to GMOD’s Chado database schema to enable Chado to support natural diversity, population genomics, individuals, breeding, phenotypes and geolocation information. This module is the first extension to Chado to be designed by the community, rather than at one institution. We will close by soliciting nominations and ideas for a GMOD Evolutionary Biology Hackathon. This hackathon will be held November 8-12, at NESCent, which is sponsoring the event. There will be an open call for participation in August.

    Evolutionary Biology and Rape

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    This article queries whether an evolutionary analysis of rape may be more compelling in explaining a rape victim\u27s fear than a defendant\u27s sexual aggression. Such a victim-oriented approach could help legal decisionmakers assess the reasonableness of the victim\u27s fear when determining whether sex was forced or threatened. These ideas are explored in the context of two well-known rape trials, State v. Rusk and State v. Smith. This article concludes that evolutionary biology can contribute to an understanding of rape. However, the supposed evolutionary underpinnings of male sexual aggression should not justify such behavior or render it acceptable as a criminal defense. Moreover, evolutionary research must be evaluated in a social frame so that generalizations do not unfairly or inaccurately bias plaintiffs or defendants

    The Extended (Evolutionary) Synthesis Debate: Where Science Meets Philosophy

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    Recent debates between proponents of the modern evolutionary synthesis (the standard model in evolutionary biology) and those of a possible extended synthesis are a good example of the fascinating tangle among empirical, theoretical, and conceptual or philosophical matters that is the practice of evolutionary biology. In this essay, we briefly discuss two case studies from this debate, highlighting the relevance of philosophical thinking to evolutionary biologists in the hope of spurring further constructive cross-pollination between the two fields

    Conservation evo-devo: preserving biodiversity by understanding its origins

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    Unprecedented rates of species extinction increase the urgency for effective conservation biology management practices. Thus, any improvements in practice are vital and we suggest that conservation can be enhanced through recent advances in evolutionary biology, specifically advances put forward by evolutionary developmental biology (i.e., evo-devo). There are strong overlapping conceptual links between conservation and evo-devo whereby both fields focus on evolutionary potential. In particular, benefits to conservation can be derived from some of the main areas of evo-devo research, namely phenotypic plasticity, modularity and integration, and mechanistic investigations of the precise developmental and genetic processes that determine phenotypes. Using examples we outline how evo-devo can expand into conservation biology, an opportunity which holds great promise for advancing both fields

    Community content building for evolutionary biology: Lessons learned from LepTree and Encyclopedia of Life

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    Online resources to aid large-scale ecological and evolutionary biology are beginning to take root, only a decade behind fields such as genomics and molecular biology. One barrier has been a long tradition, in evolutionary biology at least, of work by individuals on the order of a few hundred of species rather than the thousands or hundreds of thousands necessary to understand the general evolutionary or ecological processes that explain species characteristics and distributions. Advances in collaborative and semantic software offer promise – it should be possible to develop high quality online species-level datasets for comparative analyses and even to integrate, via machine reasoning, across highly customized datasets. In this talk we will compare and contrast two approaches to assembling the data