ReviewAnnual review of biophysics2019
Figure 1 Theory Meets Figure 2 Experiments in the Study of Gene Expression.
Review in Annual review of biophysics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.
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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.
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Who cites it
33 citing papers in PubMed.
- Opportunities for artificial intelligence and synthetic biology in designing living drug delivery systems.Advanced drug delivery reviews · 2026Review
- Predictive modeling of gene expression and localization of DNA binding site using deep convolutional neural networks.PLoS computational biology · 2026Article
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- Article
- A differentiable Gillespie algorithm for simulating chemical kinetics, parameter estimation, and designing synthetic biological circuits.bioRxiv : the preprint server for biology · 2025Article
- A mathematical model clarifies the ABC Score formula used in enhancer-gene prediction.bioRxiv : the preprint server for biology · 2024Article
- Deciphering regulatory architectures of bacterial promoters from synthetic expression patterns.PLoS computational biology · 2024Article
- Optogenetic dissection of transcriptional repression in a multicellular organism.Nature communications · 2024Article
- Seeing with an extra sense.Current biology : CB · 2024Article
- Prevalence of and gene regulatory constraints on transcriptional adaptation in single cells.Genome biology · 2024Article
- Deciphering regulatory architectures from synthetic single-cell expression patterns.bioRxiv : the preprint server for biology · 2024Article
- Article
- Prevalence of and gene regulatory constraints on transcriptional adaptation in single cells.bioRxiv : the preprint server for biology · 2023Article
- Configurational entropy is an intrinsic driver of tissue structural heterogeneity.bioRxiv : the preprint server for biology · 2023Article
- Minimal synthetic enhancers reveal control of the probability of transcriptional engagement and its timing by a morphogen gradient.Cell systems · 2023Article
- Article
- A synthetic synthesis to explore animal evolution and development.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2022Review
- Quantifying the regulatory role of individual transcription factors in Escherichia coli.Cell reports · 2021Article
- Molecular competition can shape enhancer activity in theiScience · 2021Article
- Systematic dissection of σCell reports · 2021Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
It is tempting to believe that we now own the genome. The ability to read and rewrite it at will has ushered in a stunning period in the history of science. Nonetheless, there is an Achilles' heel exposed by all of the genomic data that has accrued: We still do not know how to interpret them. Many genes are subject to sophisticated programs of transcriptional regulation, mediated by DNA sequences that harbor binding sites for transcription factors, which can up- or down-regulate gene expression depending upon environmental conditions. This gives rise to an input-output function describing how the level of expression depends upon the parameters of the regulated gene-for instance, on the number and type of binding sites in its regulatory sequence. In recent years, the ability to make precision measurements of expression, coupled with the ability to make increasingly sophisticated theoretical predictions, has enabled an explicit dialogue between theory and experiment that holds the promise of covering this genomic Achilles' heel. The goal is to reach a predictive understanding of transcriptional regulation that makes it possible to calculate gene expression levels from DNA regulatory sequence. This review focuses on the canonical simple repression motif to ask how well the models that have been used to characterize it actually work. We consider a hierarchy of increasingly sophisticated experiments in which the minimal parameter set learned at one level is applied to make quantitative predictions at the next. We show that these careful quantitative dissections provide a template for a predictive understanding of the many more complex regulatory arrangements found across all domains of life.
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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.