ReviewGenetics, selection, evolution : GSE2021
Phenomes: the current frontier in animal breeding.
Review in Genetics, selection, evolution : GSE, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 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
17 citing papers in PubMed.
- A guide to plant breeding for animal breeders.G3 (Bethesda, Md.) · 2026Review
- Impact of Trait Measurement Error on Quantitative Genetic Analysis of Computer Vision-Derived Traits.Genes · 2026Article
- Unlocking the potential of computer vision in precision pig farming: a call for a collaborative data and AI models platform.Animal frontiers : the review magazine of animal agriculture · 2026Article
- Daily feed intake patterns of purebred nucleus boars as genetic indicators for disease resilience of crossbred barrows under a natural polymicrobial disease challenge.Journal of animal science · 2026Article
- Advancements in Animal Breeding: From Mendelian Genetics to Machine Learning.International journal of molecular sciences · 2025Review
- Heterogeneity of Variances in Milk Yield in Murrah Buffaloes.Animals : an open access journal from MDPI · 2025Article
- "Why don't we just add a camera?": a psycho-genetic perspective on precision livestock farming in pigs.Porcine health management · 2024Article
- Pleiotropy, epistasis and the genetic architecture of quantitative traits.Nature reviews. Genetics · 2024Review
- Clustering of countries based on dairy productivity characteristics of Holstein cattle for breeding material selection.Veterinary world · 2024Article
- Inertial measurement unit technology for gait detection: a comprehensive evaluation of gait traits in two Italian horse breeds.Frontiers in veterinary science · 2024Article
- Editorial: Increasing sustainability in livestock production systems through high-throughput phenotyping approaches.Frontiers in genetics · 2024Article
- Incorporating new technologies in breeding plans for South African goats in harsh environments.Animal frontiers : the review magazine of animal agriculture · 2023Article
- Digital Phenotyping: A Game Changer for the Broiler Industry.Animals : an open access journal from MDPI · 2023Review
- Genomic evaluation methods to include intermediate correlated features such as high-throughput or omics phenotypes.JDS communications · 2023Review
- Phenomics as an approach to Comparative Developmental Physiology.Frontiers in physiology · 2023Article
- Use of Milk Infrared Spectral Data as Environmental Covariates in Genomic Prediction Models for Production Traits in Canadian Holstein.Animals : an open access journal from MDPI · 2022Article
- Applications of Omics Technology for Livestock Selection and Improvement.Frontiers in genetics · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Improvements in genomic technologies have outpaced the most optimistic predictions, allowing industry-scale application of genomic selection. However, only marginal gains in genetic prediction accuracy can now be expected by increasing marker density up to sequence, unless causative mutations are identified. We argue that some of the most scientifically disrupting and industry-relevant challenges relate to 'phenomics' instead of 'genomics'. Thanks to developments in sensor technology and artificial intelligence, there is a wide range of analytical tools that are already available and many more will be developed. We can now address some of the pressing societal demands on the industry, such as animal welfare concerns or efficiency in the use of resources. From the statistical and computational point of view, phenomics raises two important issues that require further work: penalization and dimension reduction. This will be complicated by the inherent heterogeneity and 'missingness' of the data. Overall, we can expect that precision livestock technologies will make it possible to collect hundreds of traits on a continuous basis from large numbers of animals. Perhaps the main revolution will come from redesigning animal breeding schemes to explicitly allow for high-dimensional phenomics. In the meantime, phenomics data will definitely enlighten our knowledge on the biological basis of phenotypes.
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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.