ArticleAnnual review of condensed matter physics2015
Napoleon Is in Equilibrium.
Article in Annual review of condensed matter physics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 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.
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.
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Who cites it
32 citing papers in PubMed.
- Review
- Analyzing an organism's sensors using Maximum Entropy (MaxEnt) models with bias, variance, and confusion matrices.PloS one · 2026Article
- Fluctuation structure predicts genome-wide perturbation outcomes.Research square · 2025Article
- Fluctuation structure predicts genome-wide perturbation outcomes.bioRxiv : the preprint server for biology · 2025Article
- Revealing gene function with statistical inference at single-cell resolution.Nature reviews. Genetics · 2024Review
- Transcription factor competition facilitates self-sustained oscillations in single gene genetic circuits.PLoS computational biology · 2023Article
- Configurational entropy is an intrinsic driver of tissue structural heterogeneity.bioRxiv : the preprint server for biology · 2023Article
- How cells wrap around virus-like particles using extracellular filamentous protein structures.bioRxiv : the preprint server for biology · 2023Article
- How cells wrap around virus-like particles using extracellular filamentous protein structures.ArXiv · 2023Article
- Liquid-Liquid Phase Separation in Chromatin.Cold Spring Harbor perspectives in biology · 2022Review
- Anticipating response function in gene regulatory networks.Journal of the Royal Society, Interface · 2021Article
- Entanglement and Purification Transitions in Non-Hermitian Quantum Mechanics.Physical review letters · 2021Article
- In search of lost time: Enhancers as modulators of timing in lymphocyte development and differentiation.Immunological reviews · 2021Review
- Reconciling kinetic and thermodynamic models of bacterial transcription.PLoS computational biology · 2021Article
- First-principles prediction of the information processing capacity of a simple genetic circuit.Physical review. E · 2020Article
- Switchable crossed spin conductance in a graphene-based junction: The role of spin-orbit coupling.Scientific reports · 2020Article
- Multimodal transcriptional control of pattern formation in embryonic development.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- Predictive shifts in free energy couple mutations to their phenotypic consequences.Proceedings of the National Academy of Sciences of the United States of America · 2019Article
- Figure 1 Theory Meets Figure 2 Experiments in the Study of Gene Expression.Annual review of biophysics · 2019Review
- Article
Corrections and comments
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Authors and funding
1 author.
Funding
Abstract
It has been said that the cell is the test tube of the twenty-first century. If so, the theoretical tools needed to quantitatively and predictively describe what goes on in such test tubes lag sorely behind the stunning experimental advances in biology seen in the decades since the molecular biology revolution began. Perhaps surprisingly, one of the theoretical tools that has been used with great success on problems ranging from how cells communicate with their environment and each other to the nature of the organization of proteins and lipids within the cell membrane is statistical mechanics. A knee-jerk reaction to the use of statistical mechanics in the description of cellular processes is that living organisms are so far from equilibrium that one has no business even thinking about it. But such reactions are probably too hasty given that there are many regimes in which, because of a separation of timescales, for example, such an approach can be a useful first step. In this article, we explore the power of statistical mechanical thinking in the biological setting, with special emphasis on cell signaling and regulation. We show how such models are used to make predictions and describe some recent experiments designed to test them. We also consider the limits of such models based on the relative timescales of the processes of interest.
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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.