Description
Book SynopsisOffers important lessons about the opportunities for quantitative, physics-style experiments on diverse biological phenomena. This title emphasizes the unifying power of abstract physical principles to motivate advanced experiments on biological systems. It covers a range of biological phenomena from the physicist's perspective.
Trade ReviewWilliam Bialek, Winner of the 2013 Swartz Prize for Theoretical and Computational Neuroscience, Society for Neuroscience "[T]he book goes beyond being a structured material for readers to learn about biophysics; it takes readers on an incredible journey in discovering fascinating ways in which biological phenomena can be viewed and studied. The technical adroitness and more importantly, the unique way of thinking about biological problems, in the reviewer's opinion, makes the book a must-read for any aspiring biophysicists."--Angie Ma, Contemporary Physics "[P]hysicists who are seeking an exciting intellectual path through the complexity of biology will deeply appreciate Bialek's clear vision of the big ideas and his expert guidance through their many applications."--Stephen J. Hagen, Physics Today "The book is well crafted, linking the historic work of the 'giants', e.g. Helmholtz with his seminal view of vision and hearing, with latest and trendy research, exemplified by the use of information theory in biology."--Robert Endres, Biological Physics Group Newsletter
Table of ContentsAcknowledgments ix PART I EXPLORING THE PHENOMENA 1. Introduction 3 *1.1 About Our Subject 3 *1.2 About This Book 11 2. Photon Counting in Vision 17 *2.1 A First Look 17 *2.2 Dynamics of Single Molecules 51 *2.3 Biochemical Amplification 68 *2.4 The First Synapse and Beyond 97 *2.5 Coda 115 3. Lessons, Problems, Principles 117 PART II CANDIDATE PRINCIPLES 4. Noise Is Not Negligible 127 *4.1 Fluctuations and Chemical Reactions 127 *4.2 Motility and Chemotaxis in Bacteria 149 *4.3 Molecule Counting, More Generally 172 *4.4 More about Noise in Perception 192 *4.5 Proofreading and Active Noise Reduction 218 *4.6 Perspectives 245 5. No Fine Tuning 247 *5.1 Sequence Ensembles 248 *5.2 Ion Channels and Neuronal Dynamics 279 *5.3 The States of Cells 299 *5.4 Long Time Scales in Neural Networks 329 *5.5 Perspectives 349 6. Efficient Representation 353 *6.1 Entropy and Information 354 *6.2 Noise and Information Flow 369 *6.3 Does Biology Care about Bits? 395 *6.4 Optimizing Information Flow 421 *6.5 Gathering Information and Making Models 449 *6.6 Perspectives 467 7. Outlook 469 Appendix Some Further Topics 473 * A.1 Poisson Processes 473 * A.2 Correlations, Power Spectra, and All That 484 * A.3 Diffraction and Biomolecular Structure 495 * A.4 Electronic Transitions in Large Molecules 503 * A.5 The Kramers Problem 512 * A.6 Berg and Purcell, Revisited 521 * A.7 Maximum Entropy 533 * A.8 Measuring Information Transmission 545 Annotated Bibliography 557 Index 625
