ReviewPhysical biology2015
From analog to digital models of gene regulation.
Review in Physical biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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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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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.
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Who cites it
10 citing papers in PubMed.
- The Information Theory of Aging.Nature aging · 2023Review
- Article
- Integration of a multi-omics stem cell differentiation dataset using a dynamical model.PLoS genetics · 2023Article
- Emergent phenomena in living systems:A statistical mechanical perspective.Journal of biosciences · 2022Review
- Boolean gene regulatory network model of centromere function in Saccharomyces cerevisiae.Journal of biological physics · 2019Article
- Multiplex RNA single molecule FISH of inducible mRNAs in single yeast cells.Scientific data · 2019Article
- Gene transcription in bursting: a unified mode for realizing accuracy and stochasticity.Biological reviews of the Cambridge Philosophical Society · 2019Article
- Haematopoietic stem cells: entropic landscapes of differentiation.Interface focus · 2018Article
- Identification of gene regulation models from single-cell data.Physical biology · 2018Article
- Integrating single-molecule experiments and discrete stochastic models to understand heterogeneous gene transcription dynamics.Methods (San Diego, Calif.) · 2015Review
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Recently, major progress has been made to develop computational models to predict and explain the mechanisms and behaviors of gene regulation. Here, we review progress on how these mechanisms and behaviors have been interpreted with analog models, where cell properties continuously modulate transcription, and digital models, where gene modulation involves discrete activation and inactivation events. We introduce recent experimental approaches, which measure these gene regulatory behaviors at single-cell and single-molecule resolution, and we discuss the integration of these approaches with computational models to reveal biophysical insight. By analyzing simple toy models in the context of existing experimental capabilities, we discuss the interplay between different experiments and different models to measure and interpret gene regulatory behaviors. Finally, we review recent successes in the development of predictive computational models for the control of gene regulation behaviors.
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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.