Quantum Bio Informatics

The purpose of this proceedings volume is to return to the starting point of bio-informatics and quantum information, fields that are growing rapidly at present, and to seriously attempt mutual interaction between the two, with a view to enumerating and solving the many fundamental problems they entail. For such a purpose, we look for interdisciplinary bridges in mathematics, physics, information and life sciences, in particular, research for new paradigm for information science and life science on the basis of quantum theory.

The purpose of this proceedings volume is to look for interdisciplinary bridges in mathematics, physics, information and life sciences, in particular, research for new paradigms for information and life sciences on the basis of quantum theory. The main areas in this volume are all related to one of the following subjects: (1) mathematical foundation of quantum mechanics, (2) quantum information, (3) quantum algorithm and computation, (4) quantum communication, (5) white noise analysis and quantum dynamics, (6) chaos dynamics and adaptive dynamics, (7) experimental studies of quantum computer, (8) bio-informatics and (9) genome analysis.

"Quantum Mechanics in Drug Discovery" is an illuminating guide that navigates the intersection of quantum mechanics and pharmaceutical research. Designed for scientists, researchers, and professionals in the field of drug discovery, this book explores the crucial role of quantum mechanics in understanding molecular interactions, electronic structures, and the behavior of chemical compounds. Covering principles such as quantum molecular modeling and computational chemistry, the book provides valuable insights into predicting and optimizing drug properties with precision. With clarity and practical relevance, it serves as an indispensable resource for those seeking a deeper understanding of how quantum mechanics contributes to the advancement of drug development and innovation.

This book is a self-contained, tutorial-based introduction to quantum information theory and quantum biology. It serves as a single-source reference to the topic for researchers in bioengineering, communications engineering, electrical engineering, applied mathematics, biology, computer science, and physics. The book provides all the essential principles of the quantum biological information theory required to describe the quantum information transfer from DNA to proteins, the sources of genetic noise and genetic errors as well as their effects. Integrates quantum information and quantum biology concepts; Assumes only knowledge of basic concepts of vector algebra at undergraduate level; Provides a thorough introduction to basic concepts of quantum information processing, quantum information theory, and quantum biology; Includes in-depth discussion of the quantum biological channel modelling, quantum biological channel capacity calculation, quantum models of aging, quantum models of evolution, quantum models on tumor and cancer development, quantum modeling of bird navigation compass, quantum aspects of photosynthesis, quantum biological error correction.

"A Handbook of Quantum Mechanics in Drug Discovery" is a comprehensive guide tailored for absolute beginners without a mathematical background, offering a clear and accessible introduction to the intricate realm of quantum mechanics as applied to the field of drug discovery. Through simplified explanations and practical examples, this handbook demystifies complex concepts, providing readers with a foundational understanding of quantum mechanics principles and their crucial role in modern pharmaceutical research. From elucidating the electronic structure of molecules to exploring quantum algorithms for drug design and prediction, this book equips readers with the essential knowledge and insights necessary to navigate the intersection of quantum mechanics and drug discovery with confidence and clarity.

The purpose of this volume is examine bio-informatics and quantum information, which are growing rapidly at present, and to attempt to connect the two, with a view to enumerating and solving the many fundamental problems they entail. To this end, we look for interdisciplinary bridges in mathematics, physics, and information and life sciences. In particular, research into a new paradigm for information science and life science on the basis of quantum theory is emphasized. Sample Chapter(s). Markov Fields on Graphs (599 KB). Contents: Markov Fields on Graphs (L Accardi & H Ohno); Some Aspects of Time Operators (A Arai); Time Optimal Quantum Control of Mixed States (A Carlini et al.); On a Quantum Model of the Recognition Process (K-H Fichtner et al.); Perspectives of White Noise Analysis (T Hida); Review on Quantum Chaos Algorithm and Generalized Quantum Turing Machine (S Iriyama & M Ohya); Cauchy Problems for Some Biological Systems OCo Modelling by Stochastic Differential Equations (A Jamiolkowski); On Non-Markovian Time Evolution in Open Quantum Systems (A Kossakowski & R Rebolledo); Adaptive Dynamics and Its Applications to Chaos and NPC Problem (M Ohya); Micro-Macro Duality and Emergence of Macroscopic Levels (I Ojima); Josephson Flux Qubit (H Takayanagi); Note on Quantum Mutual Entropy Type Measures (N Watanabe); Toward in Silico Biology (From Sequence to Systems) (I Yamato et al.); and other papers. Readership: Physicists, researchers in quantum information and bioinformatics.

This book examines information processing performed by bio-systems at all scales: from genomes, cells and proteins to cognitive and even social systems. It introduces a theoretical/conceptual principle based on quantum information and non-Kolmogorov probability theory to explain information processing phenomena in biology as a whole. The book begins with an introduction followed by two chapters devoted to fundamentals, one covering classical and quantum probability, which also contains a brief introduction to quantum formalism, and another on an information approach to molecular biology, genetics and epigenetics. It then goes on to examine adaptive dynamics, including applications to biology, and non-Kolmogorov probability theory. Next, the book discusses the possibility to apply the quantum formalism to model biological evolution, especially at the cellular level: genetic and epigenetic evolutions. It also presents a model of the epigenetic cellular evolution based on the mathematical formalism of open quantum systems. The last two chapters of the book explore foundational problems of quantum mechanics and demonstrate the power of usage of positive operator valued measures (POVMs) in biological science. This book will appeal to a diverse group of readers including experts in biology, cognitive science, decision making, sociology, psychology, and physics; mathematicians working on problems of quantum probability and information and researchers in quantum foundations.