Your browser doesn't support javascript.
loading
Emerging semantics to link phenotype and environment.
Thessen, Anne E; Bunker, Daniel E; Buttigieg, Pier Luigi; Cooper, Laurel D; Dahdul, Wasila M; Domisch, Sami; Franz, Nico M; Jaiswal, Pankaj; Lawrence-Dill, Carolyn J; Midford, Peter E; Mungall, Christopher J; Ramírez, Martín J; Specht, Chelsea D; Vogt, Lars; Vos, Rutger Aldo; Walls, Ramona L; White, Jeffrey W; Zhang, Guanyang; Deans, Andrew R; Huala, Eva; Lewis, Suzanna E; Mabee, Paula M.
Afiliação
  • Thessen AE; Ronin Institute for Independent Scholarship , Monclair, NJ , United States ; The Data Detektiv , Waltham, MA , United States.
  • Bunker DE; Department of Biological Sciences, New Jersey Institute of Technology , Newark, NJ , United States.
  • Buttigieg PL; HGF-MPG Group for Deep Sea Ecology and Technology, Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar-und Meeresforschung , Bremerhaven , Germany.
  • Cooper LD; Department of Botany and Plant Pathology, Oregon State University , Corvallis, OR , United States.
  • Dahdul WM; Department of Biology, University of South Dakota , Vermillion, SD , United States.
  • Domisch S; Department of Ecology and Evolutionary Biology, Yale University , New Haven, CT , United States.
  • Franz NM; School of Life Sciences, Arizona State University , Tempe, AZ , United States.
  • Jaiswal P; Department of Botany and Plant Pathology, Oregon State University , Corvallis, OR , United States.
  • Lawrence-Dill CJ; Departments of Genetics, Development and Cell Biology and Agronomy, Iowa State University , Ames, IA , United States.
  • Midford PE; Richmond, VA , United States.
  • Mungall CJ; Genomics Division, Lawrence Berkeley National Laboratory , Berkeley, CA , United States.
  • Ramírez MJ; Division of Arachnology, Museo Argentino de Ciencias Naturales-CONICET , Buenos Aires , Argentina.
  • Specht CD; Departments of Plant and Microbial Biology & Integrative Biology, University of California , Berkeley, CA , United States.
  • Vogt L; Institut für Evolutionsbiologie und Ökologie, Universität Bonn , Bonn , Germany.
  • Vos RA; Naturalis Biodiversity Center , Leiden , The Netherlands.
  • Walls RL; iPlant Collaborative, University of Arizona , Tucson, AZ , United States.
  • White JW; US Arid Land Agricultural Research Center, United States Department of Agriculture-ARS , Maricopa, AZ , United States.
  • Zhang G; School of Life Sciences, Arizona State University , Tempe, AZ , United States.
  • Deans AR; Department of Entomology, Pennsylvania State University , University Park, PA , United States.
  • Huala E; Phoenix Bioinformatics , Redwood City, CA , United States.
  • Lewis SE; Genomics Division, Lawrence Berkeley National Laboratory , Berkeley, CA , United States.
  • Mabee PM; Department of Biology, University of South Dakota , Vermillion, SD , United States.
PeerJ ; 3: e1470, 2015.
Article em En | MEDLINE | ID: mdl-26713234
ABSTRACT
Understanding the interplay between environmental conditions and phenotypes is a fundamental goal of biology. Unfortunately, data that include observations on phenotype and environment are highly heterogeneous and thus difficult to find and integrate. One approach that is likely to improve the status quo involves the use of ontologies to standardize and link data about phenotypes and environments. Specifying and linking data through ontologies will allow researchers to increase the scope and flexibility of large-scale analyses aided by modern computing methods. Investments in this area would advance diverse fields such as ecology, phylogenetics, and conservation biology. While several biological ontologies are well-developed, using them to link phenotypes and environments is rare because of gaps in ontological coverage and limits to interoperability among ontologies and disciplines. In this manuscript, we present (1) use cases from diverse disciplines to illustrate questions that could be answered more efficiently using a robust linkage between phenotypes and environments, (2) two proof-of-concept analyses that show the value of linking phenotypes to environments in fishes and amphibians, and (3) two proposed example data models for linking phenotypes and environments using the extensible observation ontology (OBOE) and the Biological Collections Ontology (BCO); these provide a starting point for the development of a data model linking phenotypes and environments.
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Idioma: En Revista: PeerJ Ano de publicação: 2015 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Base de dados: MEDLINE Idioma: En Revista: PeerJ Ano de publicação: 2015 Tipo de documento: Article País de afiliação: Estados Unidos