ArticlePLoS biology2015
Finding our way through phenotypes.
Article in PLoS biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 93 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
93 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Building phenotypic character matrices for phylogenetic inference: exploration of 35 years of practice.Biological reviews of the Cambridge Philosophical Society · 2026Pooled it
- Review
- Discovery of Goethe's amber ant: its phylogenetic and evolutionary implications.Scientific reports · 2026Article
- ODBAE: a high-performance model identifying complex phenotypes in high-dimensional biological datasets.Communications biology · 2025Article
- Wing spot in a tropical and a temperate drosophilid: C = C enrichment and conserved thermal response.BMC ecology and evolution · 2025Article
- The Value Proposition of Coordinated Population Cohorts Across Africa.Annual review of biomedical data science · 2024Review
- Roadmap for a European cancer data management and precision medicine infrastructure.Nature cancer · 2024Article
- GallOnt: An ontology for plant gall phenotypes.Biodiversity data journal · 2024Article
- Computable species descriptions and nanopublications: applying ontology-based technologies to dung beetles (Coleoptera, Scarabaeinae).Biodiversity data journal · 2024Article
- Comparing ant morphology measurements from microscope and online AntWeb.org 2D z-stacked images.Ecology and evolution · 2023Article
- Article
- Assessing Bayesian Phylogenetic Information Content of Morphological Data Using Knowledge From Anatomy Ontologies.Systematic biology · 2022Article
- Prenatal phenotyping: A community effort to enhance the Human Phenotype Ontology.American journal of medical genetics. Part C, Seminars in medical genetics · 2022Article
- Association of Pathogenic Variants in Hereditary Cancer Genes With Multiple Diseases.JAMA oncology · 2022Article
- Past and future uses of text mining in ecology and evolution.Proceedings. Biological sciences · 2022Review
- Pleiotropy data resource as a primer for investigating co-morbidities/multi-morbidities and their role in disease.Mammalian genome : official journal of the International Mammalian Genome Society · 2022Article
- The Agricultural Genome to Phenome Initiative (AG2PI): creating a shared vision across crop and livestock research communities.Genome biology · 2022Article
- The diversity, evolution, and development of setal morphologies in bumble bees (Hymenoptera: Apidae:PeerJ · 2022Article
- Formalizing Phenotypes of Regeneration.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Genome Fractionation and Loss of Heterozygosity in Hybrids and Polyploids: Mechanisms, Consequences for Selection, and Link to Gene Function.Molecular biology and evolution · 2021Article
33 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
74 authors.
Funding
Abstract
Despite a large and multifaceted effort to understand the vast landscape of phenotypic data, their current form inhibits productive data analysis. The lack of a community-wide, consensus-based, human- and machine-interpretable language for describing phenotypes and their genomic and environmental contexts is perhaps the most pressing scientific bottleneck to integration across many key fields in biology, including genomics, systems biology, development, medicine, evolution, ecology, and systematics. Here we survey the current phenomics landscape, including data resources and handling, and the progress that has been made to accurately capture relevant data descriptions for phenotypes. We present an example of the kind of integration across domains that computable phenotypes would enable, and we call upon the broader biology community, publishers, and relevant funding agencies to support efforts to surmount today's data barriers and facilitate analytical reproducibility.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.