ReviewTrends in genetics : TIG2014
'Particle genetics': treating every cell as unique.
Review in Trends in genetics : TIG, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 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
14 citing papers in PubMed.
- Article
- Cell-to-cell expression dispersion of B-cell surface proteins is linked to genetic variants in humans.Communications biology · 2020Article
- Transcriptional adaptation ineLife · 2020Article
- Poikilosis - pervasive biological variation.F1000Research · 2020Article
- WASABI: a dynamic iterative framework for gene regulatory network inference.BMC bioinformatics · 2019Article
- Resolving the Complex Genetic Basis of Phenotypic Variation and Variability of Cellular Growth.Genetics · 2017Article
- Single-Cell-Based Analysis Highlights a Surge in Cell-to-Cell Molecular Variability Preceding Irreversible Commitment in a Differentiation Process.PLoS biology · 2016Article
- Exploiting Single-Cell Quantitative Data to Map Genetic Variants Having Probabilistic Effects.PLoS genetics · 2016Article
- Variation is function: Are single cell differences functionally important?: Testing the hypothesis that single cell variation is required for aggregate function.BioEssays : news and reviews in molecular, cellular and developmental biology · 2016Review
- Pervasive robustness in biological systems.Nature reviews. Genetics · 2015Review
- Behavioral idiosyncrasy reveals genetic control of phenotypic variability.Proceedings of the National Academy of Sciences of the United States of America · 2015Article
- Stochastic developmental variation, an epigenetic source of phenotypic diversity with far-reaching biological consequences.Journal of biosciences · 2015Review
- Changing genetic paradigms: creating next-generation genetic databases as tools to understand the emerging complexities of genotype/phenotype relationships.Human genomics · 2014Article
- How does evolution tune biological noise?Frontiers in genetics · 2014Review
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
Genotype-phenotype relations are usually inferred from a deterministic point of view. For example, quantitative trait loci (QTL), which describe regions of the genome associated with a particular phenotype, are based on a mean trait difference between genotype categories. However, living systems comprise huge numbers of cells (the 'particles' of biology). Each cell can exhibit substantial phenotypic individuality, which can have dramatic consequences at the organismal level. Now, with technology capable of interrogating individual cells, it is time to consider how genotypes shape the probability laws of single cell traits. The possibility of mapping single cell probabilistic trait loci (PTL), which link genomic regions to probabilities of cellular traits, is a promising step in this direction. This approach requires thinking about phenotypes in probabilistic terms, a concept that statistical physicists have been applying to particles for a century. Here, I describe PTL and discuss their potential to enlarge our understanding of genotype-phenotype relations.
Indexed as
Identifiers
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.