Masanari Asano · Andrei Khrennikov Masanori Ohya · Yoshiharu Tanaka Ichiro Yamato Quantum Adaptivity in Biology: From Genetics to Cognition Quantum Adaptivity in Biology: From Genetics to Cognition Masanari Asano • Andrei Khrennikov Masanori Ohya • Yoshiharu Tanaka Ichiro Yamato Quantum Adaptivity in Biology: From Genetics to Cognition 123 Masanari Asano Yoshiharu Tanaka Liberal Arts Division Information Science Tokuyama College of Technology Tokyo University of Science Tokuyama Tokyo Japan Japan Andrei Khrennikov Ichiro Yamato International Center for Mathematical Department of Biological Science Modeling in Physics and Cognitive and Technology Sciences Tokyo University of Science Linnaeus University Tokyo Växjö Japan Sweden Masanori Ohya Information Science Tokyo University of Science Tokyo Japan ISBN 978-94-017-9818-1 ISBN 978-94-017-9819-8 (eBook) DOI 10.1007/978-94-017-9819-8 Library of Congress Control Number: 2015933361 Springer Dordrecht Heidelberg New York London © Springer Science+Business Media Dordrecht 2015 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. Printed on acid-free paper Springer Science+Business Media B.V. Dordrecht is part of Springer Science+Business Media (www.springer.com) Science is beautiful when it makes simple explanations of phenomena or connections between different observations. Examples include the double helix in biology and the fundamental equations of physics. Stephen Hawking I’m fascinated by the idea that genetics is digital. A gene is a long sequence of coded letters, like computer information. Modern biology is becoming very much a branch of information technology. Richard Dawkins Foreword Unlike any other discipline in the natural sciences, Biology has benefitted tremendously from intriguing ideas and novel concepts from outside the subject’s area throughout the last century. The apparently distinct topics of chemistry, physics, mathematics and informatics became integral and indispensable matters of biological research that blended surprisingly well with organismal studies of the last centuries’ Biology. In this very aspect, Biology is reminiscent of the principal ideas of ancient Philosophy, as both fields specialize in their quest for understanding the essence of ‘life’, ‘meaning’ and ‘truth’. As an inherent consequence of organismal plasticity and diversity, ‘truth’ in biological findings is given support by studying the probability of a discrete or gradual trait in a population, which uses stochastic expressions of classical math- ematics. Here, again, striking similarities between biology and philosophy exist: While modern deductive biology uses mathematics to describe processes as pre- cisely as possible such as the dynamics of chemical reactions inside a cell or even growth and development of organs, pure mathematical formalism dominated phi- losophy and ruled deductive reasoning for almost two millennia. Established by Aristotle’s logic, especially in his theory of syllogism about 300 BC, the meaning of words and thoughts can be expressed in common mathematical formalism to deliver significance. This pure logic is bijective and unbiased from feelings or subjective observations. Besides its influence on natural sciences, Aristotle’s formal logic and the resulting Aristotelian philosophy had a great impact on theology, especially Islamic and Christian religion. In addition, he introduced deductive reasoning also into his own biological studies and, hence, Aristotle can be considered as the founder of modern deductive biology. He was even ambitious enough to adopt his theory of pure logic to the operational processes in the brain. Ironically, the period of Aristotle’s logic formalism faced an end during the epoch of Enlightenment that climaxed in Charles Darwin’s and Alfred R. Wallace’s biological ideas of speciation and evolution! During a period of almost 200 years, theories of modern mathematical logic and Aristotelian logic were seemingly incompatible. In recent years, however, it is stated that modern mathematical formalism and Aristotle’s theories of logic disclose vii viii Foreword striking similarities. Moreover, biological conceptions merged with these ideas and formed the current basis of modern biology that superficially splits into overlap- ping, but yet distinct disciplines such as bioethics, biochemistry, biophysics, biostatistics or bioinformatics. Modern biologists still aim at finding scientific ‘truth’, at identifying how ‘life’ functions or how nerve cells compute ‘meaning’. Intriguingly, with high-through- put methods at hand, biologists accumulate an enormous amount of data within a short period of time that gives a renaissance to descriptive biology of pre-Aristo- telian reasoning or of the epoch of Enlightenment. Methods of classical probability are imposed to mine all kinds of observables for statistical significance, but a large amount of information remains cryptic. Especially, next generation sequencing technologies provide strings of genomic DNA-sequences that encode for all the genetic make-up that determines an indi- vidual or a species at extraordinary speed. As a consequence, an overwhelming volume of genomic sequences is generated that await detailed analysis by bioin- formatics. This large amount of information produces huge problems in data storage and evaluation that might benefit from novel ground-breaking ideas or progress in technology. The present monograph by Masanari Asano, Andrei Khrennikov, Masanori Ohya, Yoshiharu Tanaka and Ichiro Yamato pursues such novel ground-breaking ideas in approaching phenomena of modern biology by quantum probabilistic formalism. Unlike the description of quantum physical processes at molecular scale, e.g. the processes of exciton transfer in photosynthesis or fluorescence resonance energy transfer between different molecules, the authors use the operational formalism of quantum theory to address biological problems at diverse macroscopic biological scales. They discuss and describe the application of quantum-like probability to various biological examples such as sequence and gene expression analysis, bacterial growth or epigenetics studies as well as cognitive science. The book highlights the similarities between mathematical formalism of quan- tum probability in physics and statistical experimental data by quantum bio-infor- matics. The authors carefully discuss current limitations of the general quantum information theory and propose that an extended formalism might be required to suit special biological problems. More importantly, however, they convincingly explain that some biological observations violate classical mathematic formalism, which might successfully be addressed by quantum-like probability or quantum bioinformatics. This monograph emphasizes the great potential of quantum-like probability in life science, especially for the many dynamical processes in biological studies. While classical stochastic formalism is rather static, quantum probability is more advanced and allows the representation of dynamical biological processes as different states in a framework of quantum fluctuations. Finally, the authors provide a vital debate about how evolutionary aspects can possibly be described by quantum-like models. Therefore, it is not surprising that the authors address how quantum-like formalism and probability can support bio- logical research in clarifying what ‘life’, ‘meaning’ and ‘truth’ is. Following Foreword ix Aristotelian logic, they concluded that quantum-like models hold the potential for unifying Neo-Darwinism and Neo-Lamarckism theories in modern deductive biology. Although this book does not solve the problems of modern biological data analysis, it constitutes an extraordinary attempt to show the applicability of quan- tum theory and quantum-like formalism to macroscopic observables, which is novel and a very stimulating read. Dierk Wanke Saarland University and University of Tübingen Germany Preface The aim of this book is to introduce a theoretical/conceptual principle (based on quantum information theory and non-Kolmogorov probability theory) to understand information processing phenomena in biology as a whole—the information biology —a new research field, which is based on the application of open quantum systems (and, more generally, adaptive dynamics [173, 26, 175]) outside of physics as a powerful tool. Thus this book is about information processing performed by bio- systems. Since quantum information theory generalizes classical information theory