Emerging semantics to link phenotype and environment

Anne E. Thessen, Daniel E. Bunker, Pier Luigi Buttigieg, Laurel D. Cooper, Wasila M. Dahdul, Sami Domisch, Nico M. Franz, Pankaj Jaiswal, Carolyn J. Lawrence-Dill, Peter E. Midford, Christopher J. Mungall, Martin J. Ramírez, Chelsea D. Specht, Lars Vogt, Rutger Aldo Vos, Ramona L. Walls, Jeffrey W. White, Guanyang Zhang, Andrew R. Deans, Eva HualaSuzanna E. Lewis, Paula M. Mabee

Research output: Contribution to journalArticlepeer-review

19 Scopus citations

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.

Original languageEnglish (US)
Article numbere1470
JournalPeerJ
Volume2015
Issue number12
DOIs
StatePublished - 2015

All Science Journal Classification (ASJC) codes

  • General Neuroscience
  • General Biochemistry, Genetics and Molecular Biology
  • General Agricultural and Biological Sciences

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