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Gene expression is a stochastic process in which cells produce biomolecules essential to the function of life. Modern experimental methods allow for the measurement of biomolecules at single-cell and single-molecule resolution over time.…

Quantitative Methods · Quantitative Biology 2022-07-01 Zachary R Fox

I develop a framework for interpreting the forces that act on any population described by frequencies. The conservation of total frequency, or total probability, shapes the characteristics of force. I begin with Fisher's fundamental theorem…

Populations and Evolution · Quantitative Biology 2015-10-21 Steven A. Frank

Natural gradient descent, which preconditions a gradient descent update with the Fisher information matrix of the underlying statistical model, is a way to capture partial second-order information. Several highly visible works have…

Machine Learning · Computer Science 2020-06-09 Frederik Kunstner , Lukas Balles , Philipp Hennig

This review is an introduction to theoretical models and mathematical calculations for biological evolution, aimed at physicists. The methods in the field are naturally very similar to those used in statistical physics, although the…

Statistical Mechanics · Physics 2015-06-24 Barbara Drossel

Information is a key concept in evolutionary biology. Information is stored in biological organism's genomes, and used to generate the organism as well as to maintain and control it. Information is also "that which evolves". When a…

Populations and Evolution · Quantitative Biology 2012-07-25 Christoph Adami

Eukaryotic cell development has been optimized by natural selection to obey maximal intracellular flux of messenger proteins. This, in turn, implies maximum Fisher information on angular position about a target nuclear pore complex (NPR).…

Subcellular Processes · Quantitative Biology 2014-05-01 B. R. Frieden , R. A. Gatenby

We derive general upper bounds to pointwise mutual information in terms of stochastic Fisher information and show these bounds average to known results in the literature for bounds to mutual information in terms of Fisher information. These…

Quantum Physics · Physics 2026-05-22 Pedro B. Melo

In this paper, I model and study the process of natural selection between all possible mixed strategies in classical two-player two-strategy games. I derive and solve an equation that is a natural generalization of the Taylor-Jonker…

Populations and Evolution · Quantitative Biology 2018-02-21 Georgy Karev

An interactive stochastics, evaluated by an entropy functional (EF) of a random field and informational process' path functional (IPF), allows us modeling the evolutionary information processes and revealing regularities of evolution…

Information Theory · Computer Science 2011-09-15 Vladimir S. Lerner

The Fisher's information metric is introduced in order to find the real meaning of the probability distribution in classical and quantum systems described by Riemaniann non-degenerated superspaces. In particular, the physical r\^{o}le…

High Energy Physics - Theory · Physics 2012-12-04 Diego Julio Cirilo-Lombardo , Victor I. Afonso

We address the fundamental limits of learning unknown parameters of any stochastic process from time-series data, and discover exact closed-form expressions for how optimal inference scales with observation length. Given a parametrized…

Machine Learning · Computer Science 2023-10-09 Paul M. Riechers

Biologists measure information in different ways. Neurobiologists and researchers in bioinformatics often measure information using information-theoretic measures such as Shannon's entropy or mutual information. Behavioral biologists and…

Populations and Evolution · Quantitative Biology 2007-07-13 Carl T. Bergstrom , Michael Lachmann

In this era of Big Data, proficient use of data mining is the key to capture useful information from any dataset. As numerous data mining techniques make use of information theory concepts, in this paper, we discuss how Fisher information…

Information Theory · Computer Science 2016-11-17 Nasir Ahmad , Sybil Derrible , Tarsha Eason , Heriberto Cabezas

The Fisher infinitesimal model is a classical model of phenotypic trait inheritance in quantitative genetics. Here, we prove that it encompasses a remarkable convexity structure which is compatible with a selection function having a convex…

Probability · Mathematics 2025-07-30 Vincent Calvez , David Poyato , Filippo Santambrogio

The scheme of a unified Darwinian evolutionary theory for physical and biological systems is described. Every physical system is methodologically endowed with a classical information processor what turns every system into an agent being…

General Physics · Physics 2019-11-26 Carlos Baladron , Andrei Khrennikov

Biological organisms adapt to changes by processing informations from different sources, most notably from their ancestors and from their environment. We review an approach to quantify these informations by analyzing mathematical models of…

Populations and Evolution · Quantitative Biology 2016-03-23 Olivier Rivoire

We derive a Fisher matrix for the parameters characterising a population of gravitational-wave events. This provides a guide to the precision with which population parameters can be estimated with multiple observations, which becomes…

General Relativity and Quantum Cosmology · Physics 2022-12-14 Jonathan R. Gair , Andrea Antonelli , Riccardo Barbieri

The unavoidable interaction between a quantum system and the external noisy environment can be mimicked by a sequence of stochastic measurements whose outcomes are neglected. Here we investigate how this stochasticity is reflected in the…

Quantum Physics · Physics 2018-03-30 Matthias M. Müller , Stefano Gherardini , Augusto Smerzi , Filippo Caruso

We show that both the classical as well as the quantum definitions of the Fisher information faithfully identify resourceful quantum states in general quantum resource theories, in the sense that they can always distinguish between states…

Quantum Physics · Physics 2021-11-25 Kok Chuan Tan , Varun Narasimhachar , Bartosz Regula

Inference and learning are commonly cast in terms of optimisation, yet the fundamental constraints governing uncertainty reduction remain unclear. This work presents a first-principles framework inherent to Bayesian updating, termed…

Information Theory · Computer Science 2026-01-22 Takuya Isomura