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Life depends as much on the flow of information as on the flow of energy. Here we review the many efforts to make this intuition precise. Starting with the building blocks of information theory, we explore examples where it has been…

Quantitative Methods · Quantitative Biology 2014-12-31 Gašper Tkačik , William Bialek

Genetic regulatory networks enable cells to respond to the changes in internal and external conditions by dynamically coordinating their gene expression profiles. Our ability to make quantitative measurements in these biochemical circuits…

Biological Physics · Physics 2015-03-17 Aleksandra M Walczak , Gašper Tkačik

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

Changes in a cell's external or internal conditions are usually reflected in the concentrations of the relevant transcription factors. These proteins in turn modulate the expression levels of the genes under their control and sometimes need…

Molecular Networks · Quantitative Biology 2013-08-01 Gasper Tkacik , Curtis G Callan , William Bialek

Modelling gene regulatory networks not only requires a thorough understanding of the biological system depicted but also the ability to accurately represent this system from a mathematical perspective. Throughout this chapter, we aim to…

Quantitative Methods · Quantitative Biology 2018-05-04 Olivia Angelin-Bonnet , Patrick J. Biggs , Matthieu Vignes

In this Chapter, we ask questions (1) What is the right way to measure the quality of information processing in a biological system? and (2) What can real-life organisms do in order to improve their performance in information-processing…

Quantitative Methods · Quantitative Biology 2010-11-25 Ilya Nemenman

Computational intelligence is broadly defined as biologically-inspired computing. Usually, inspiration is drawn from neural systems. This article shows how to analyze neural systems using information theory to obtain constraints that help…

Neurons and Cognition · Quantitative Biology 2018-05-11 Michael Wibral , Joseph T. Lizier , Viola Priesemann

Understanding a complex system entails capturing the non-trivial collective phenomena that arise from interactions between its different parts. Information theory is a flexible and robust framework to study such behaviours, with several…

In biological systems, information is frequently transferred with Poisson like spike processes (shot noise) modulated in time by information-carrying signals. How then to quantify information transfer for the output for such nonstationary…

Biological Physics · Physics 2009-06-19 Igor Goychuk , Peter Hanggi

This document consists of lecture notes for a graduate course, which focuses on the relations between Information Theory and Statistical Physics. The course is aimed at EE graduate students in the area of Communications and Information…

Information Theory · Computer Science 2010-06-09 Neri Merhav

Information theory is a practical and theoretical framework developed for the study of communication over noisy channels. Its probabilistic basis and capacity to relate statistical structure to function make it ideally suited for studying…

Neurons and Cognition · Quantitative Biology 2015-01-09 Simon R. Schultz , Robin A. A. Ince , Stefano Panzeri

The last decade has witnessed a surge of theoretical and computational models to describe the dynamics of complex gene regulatory networks, and how these interactions can give rise to multistable and heterogeneous cell populations. As the…

Molecular Networks · Quantitative Biology 2023-06-28 Federico Bocci , Dongya Jia , Qing Nie , Mohit Kumar Jolly , Jose Onuchic

Oscillations lie at the core of many biological processes, from the cell cycle, to circadian oscillations and developmental processes. Time-keeping mechanisms are essential to enable organisms to adapt to varying conditions in environmental…

Machine Learning · Statistics 2015-04-27 D Trejo , AJ Millar , G Sanguinetti

We explore the critical behaviors in the dynamics of information transfer of a biologically-inspired system by an individual-based model. "Quorum response", a type of social interaction which has been recognized taxonomically in animal…

Physics and Society · Physics 2013-08-22 Collin Feng Hu

We quantify the influence of the topology of a transcriptional regulatory network on its ability to process environmental signals. By posing the problem in terms of information theory, we may do this without specifying the function…

Molecular Networks · Quantitative Biology 2015-06-26 Etay Ziv , Ilya Nemenman , Chris H. Wiggins

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

Stochastic processes offer a flexible mathematical formalism to model and reason about systems. Most analysis tools, however, start from the premises that models are fully specified, so that any parameters controlling the system's dynamics…

Systems and Control · Computer Science 2017-01-11 Luca Bortolussi , Guido Sanguinetti

Fluctuations in biochemical networks, e.g., in a living cell, have a complex origin that precludes a description of such systems in terms of bipartite or multipartite processes, as is usually done in the framework of stochastic and/or…

Statistical Mechanics · Physics 2020-01-29 R. Chétrite , M. L. Rosinberg , T. Sagawa , G. Tarjus

This paper provides a perspective on applying the concepts of information thermodynamics, developed recently in non-equilibrium statistical physics, to problems in theoretical neuroscience. Historically, information and energy in…

Neurons and Cognition · Quantitative Biology 2024-09-27 Jan Karbowski

We try to establish a unified information theoretic approach to learning and to explore some of its applications. First, we define {\em predictive information} as the mutual information between the past and the future of a time series,…

Data Analysis, Statistics and Probability · Physics 2007-05-23 Ilya Nemenman
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