Transforming the study of organisms: Phenomic data models and knowledge bases

Anne E. Thessen, Ramona L. Walls, Lars Vogt, Jessica Singer, Robert Warren, Pier Luigi Buttigieg, James P. Balhoff, Christopher J. Mungall, Deborah L. McGuinness, Brian J. Stucky, Matthew J. Yoder, Melissa A. Haendel

Research output: Contribution to journalReview articlepeer-review

Abstract

The rapidly decreasing cost of gene sequencing has resulted in a deluge of genomic data from across the tree of life; however, outside a few model organism databases, genomic data are limited in their scientific impact because they are not accompanied by computable phenomic data. The majority of phenomic data are contained in countless small, heterogeneous phenotypic data sets that are very difficult or impossible to integrate at scale because of variable formats, lack of digitization, and linguistic problems. One powerful solution is to represent phenotypic data using data models with precise, computable semantics, but adoption of semantic standards for representing phenotypic data has been slow, especially in biodiversity and ecology. Some phenotypic and trait data are available in a semantic language from knowledge bases, but these are often not interoperable. In this review, we will compare and contrast existing ontology and data models, focusing on nonhuman phenotypes and traits. We discuss barriers to integration of phenotypic data and make recommendations for developing an operationally useful, semantically interoperable phenotypic data ecosystem.

Original languageEnglish (US)
Article numbere1008376
JournalPLoS computational biology
Volume16
Issue number11
DOIs
StatePublished - Nov 24 2020
Externally publishedYes

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Modeling and Simulation
  • Ecology
  • Molecular Biology
  • Genetics
  • Cellular and Molecular Neuroscience
  • Computational Theory and Mathematics

Fingerprint

Dive into the research topics of 'Transforming the study of organisms: Phenomic data models and knowledge bases'. Together they form a unique fingerprint.

Cite this