ReviewProceedings of the National Academy of Sciences of the United States of America2010
Colloquium papers: Numbering the hairs on our heads: the shared challenge and promise of phenomics.
Review in Proceedings of the National Academy of Sciences of the United States of America, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.
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
48 citing papers in PubMed.
- Quantification of facial skeletal shape variation in fibroblast growth factor receptor-related craniosynostosis syndromes.Birth defects research. Part A, Clinical and molecular teratology · 2014Trial
- Tissue-specific differences of gene expression variance in mutation accumulation lines of mice.Heredity · 2026Article
- Continent-wide differentiation of fitness traits and patterns of climate adaptation among European populations ofEvolution letters · 2025Article
- Regularized regression can improve estimates of multivariate selection in the face of multicollinearity and limited data.Evolution letters · 2024Article
- Noninvasive Detection of Salt Stress in Cotton Seedlings by Combining Multicolor Fluorescence-Multispectral Reflectance Imaging with EfficientNet-OB2.Plant phenomics (Washington, D.C.) · 2023Article
- Automated morphological phenotyping using learned shape descriptors and functional maps: A novel approach to geometric morphometrics.PLoS computational biology · 2023Article
- Unveiling the third dimension in morphometry with automated quantitative volumetric computations.Scientific reports · 2021Article
- Spectral phenotyping of embryonic development reveals integrative thermodynamic responses.BMC bioinformatics · 2021Article
- A CURE for a Major Challenge in Phenomics: A Practical Guide to Implementing a Quantitative Specimen-Based Undergraduate Research Experience.Integrative organismal biology (Oxford, England) · 2020Article
- The odonate phenotypic database, a new open data resource for comparative studies of an old insect order.Scientific data · 2019Article
- Clarifying dairy calf mortality phenotypes through postmortem analysis.Journal of dairy science · 2019Article
- Article
- A high-throughput and open-source platform for embryo phenomics.PLoS biology · 2018Article
- A simple developmental model recapitulates complex insect wing venation patterns.Proceedings of the National Academy of Sciences of the United States of America · 2018Article
- The Quantitative Genetic Control of Root Architecture in Maize.Plant & cell physiology · 2018Article
- Powerful and interpretable behavioural features for quantitative phenotyping ofPhilosophical transactions of the Royal Society of London. Series B, Biological sciences · 2018Article
- Article
- Phenome of pearl quality traits in the mollusc transplant model Pinctada margaritifera.Scientific reports · 2018Article
- Pleiotropy, constraint, and modularity in the evolution of life histories: insights from genomic analyses.Annals of the New York Academy of Sciences · 2017Review
- Genomic Characterization of the Evolutionary Potential of the Sea Urchin Strongylocentrotus droebachiensis Facing Ocean Acidification.Genome biology and evolution · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
Abstract
Evolution and medicine share a dependence on the genotype-phenotype map. Although genotypes exist and are inherited in a discrete space convenient for many sorts of analyses, the causation of key phenomena such as natural selection and disease takes place in a continuous phenotype space whose relationship to the genotype space is only dimly grasped. Direct study of genotypes with minimal reference to phenotypes is clearly insufficient to elucidate these phenomena. Phenomics, the comprehensive study of phenotypes, is therefore essential to understanding biology. For all of the advances in knowledge that a genomic approach to biology has brought, awareness is growing that many phenotypes are highly polygenic and susceptible to genetic interactions. Prime examples are common human diseases. Phenomic thinking is starting to take hold and yield results that reveal why it is so critical. The dimensionality of phenotypic data are often extremely high, suggesting that attempts to characterize phenotypes with a few key measurements are unlikely to be completely successful. However, once phenotypic data are obtained, causation can turn out to be unexpectedly simple. Phenotypic data can be informative about the past history of selection and unexpectedly predictive of long-term evolution. Comprehensive efforts to increase the throughput and range of phenotyping are an urgent priority.
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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.