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    Garfinkel, A.
    Modeling Life [Electronic resource] / A. Garfinkel, J. Shevtsov, Y. Guo. - 1st ed. 2017. - [S. l. : s. n.]. - XV, 445 p. 353 illus., 299 illus. in color. - ISBN 9783319597317
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Рубрики: Biomathematics.
   Mathematical models.
   Differential equations.
   Mathematical and Computational Biology.
   Mathematical Modeling and Industrial Mathematics.
   Ordinary Differential Equations.
Анотація: From predator-prey populations in an ecosystem, to hormone regulation within the body, the natural world abounds in dynamical systems that affect us profoundly. This book develops the mathematical tools essential for students in the life sciences to describe these interacting systems and to understand and predict their behavior. Complex feedback relations and counter-intuitive responses are common in dynamical systems in nature; this book develops the quantitative skills needed to explore these interactions. Differential equations are the natural mathematical tool for quantifying change, and are the driving force throughout this book. The use of Euler’s method makes nonlinear examples tractable and accessible to a broad spectrum of early-stage undergraduates, thus providing a practical alternative to the procedural approach of a traditional Calculus curriculum. Tools are developed within numerous, relevant examples, with an emphasis on the construction, evaluation, and interpretation of mathematical models throughout. Encountering these concepts in context, students learn not only quantitative techniques, but how to bridge between biological and mathematical ways of thinking. Examples range broadly, exploring the dynamics of neurons and the immune system, through to population dynamics and the Google PageRank algorithm. Each scenario relies only on an interest in the natural world; no biological expertise is assumed of student or instructor. Building on a single prerequisite of Precalculus, the book suits a two-quarter sequence for first or second year undergraduates, and meets the mathematical requirements of medical school entry. The later material provides opportunities for more advanced students in both mathematics and life sciences to revisit theoretical knowledge in a rich, real-world framework. In all cases, the focus is clear: how does the math help us understand the science?
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    Innovative Algorithms and Analysis [Electronic resource] / ed.: Gosse, Laurent., Natalini, Roberto. - 1st ed. 2017. - [S. l. : s. n.]. - XVIII, 351 p. 70 illus., 60 illus. in color. - ISBN 9783319492629
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Рубрики: Applied mathematics.
   Engineering mathematics.
   Partial differential equations.
   Computer mathematics.
   Biomathematics.
   Differential geometry.
   Physics.
   Applications of Mathematics.
   Partial Differential Equations.
   Computational Mathematics and Numerical Analysis.
   Mathematical and Computational Biology.
   Differential Geometry.
   Mathematical Methods in Physics.
Анотація: This volume gathers contributions reflecting topics presented during an INDAM workshop held in Rome in May 2016. The event brought together many prominent researchers in both Mathematical Analysis and Numerical Computing, the goal being to promote interdisciplinary collaborations. Accordingly, the following thematic areas were developed: 1. Lagrangian discretizations and wavefront tracking for synchronization models; 2. Astrophysics computations and post-Newtonian approximations; 3. Hyperbolic balance laws and corrugated isometric embeddings; 4. “Caseology” techniques for kinetic equations; 5. Tentative computations of compressible non-standard solutions; 6. Entropy dissipation, convergence rates and inverse design issues. Most of the articles are presented in a self-contained manner; some highlight new achievements, while others offer snapshots of the “state of the art” in certain fields. The book offers a unique resource, both for young researchers looking to quickly enter a given area of application, and for more experienced ones seeking comprehensive overviews and extensive bibliographic references.
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    Kiss, István Z.
    Mathematics of Epidemics on Networks [Electronic resource] : from Exact to Approximate Models / / István Z. Kiss, Miller, Joel C., Simon, Péter L. ; . - 1st ed. 2017. - [S. l. : s. n.]. - XVIII, 413 p. 130 illus., 89 illus. in color. - ISBN 9783319508061
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Рубрики: Biomathematics.
   Dynamics.
   Ergodic theory.
   Physics.
   Epidemiology.
   Probabilities.
   Mathematical and Computational Biology.
   Dynamical Systems and Ergodic Theory.
   Applications of Graph Theory and Complex Networks.
   Epidemiology.
   Probability Theory and Stochastic Processes.
Анотація: This textbook provides an exciting new addition to the area of network science featuring a stronger and more methodical link of models to their mathematical origin and explains how these relate to each other with special focus on epidemic spread on networks. The content of the book is at the interface of graph theory, stochastic processes and dynamical systems. The authors set out to make a significant contribution to closing the gap between model development and the supporting mathematics. This is done by: Summarising and presenting the state-of-the-art in modeling epidemics on networks with results and readily usable models signposted throughout the book; Presenting different mathematical approaches to formulate exact and solvable models; Identifying the concrete links between approximate models and their rigorous mathematical representation; Presenting a model hierarchy and clearly highlighting the links between model assumptions and model complexity; Providing a reference source for advanced undergraduate students, as well as doctoral students, postdoctoral researchers and academic experts who are engaged in modeling stochastic processes on networks; Providing software that can solve the differential equation models or directly simulate epidemics in networks. Replete with numerous diagrams, examples, instructive exercises, and online access to simulation algorithms and readily usable code, this book will appeal to a wide spectrum of readers from different backgrounds and academic levels. Appropriate for students with or without a strong background in mathematics, this textbook can form the basis of an advanced undergraduate or graduate course in both mathematics and biology departments alike. .
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Miller, Joel C.; Simon, Péter L.; Kiss, István Z. \.\
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    Hadeler, Karl-Peter.
    Cellular Automata: Analysis and Applications [Electronic resource] / Karl-Peter. Hadeler, Müller, Johannes. ; . - 1st ed. 2017. - [S. l. : s. n.]. - XI, 467 p. 78 illus., 3 illus. in color. - ISBN 9783319530437
    Зміст:

Рубрики: Dynamics.
   Ergodic theory.
   System theory.
   Mathematical physics.
   Biomathematics.
   Dynamical Systems and Ergodic Theory.
   Complex Systems.
   Mathematical Applications in the Physical Sciences.
   Mathematical and Computational Biology.
Анотація: This book focuses on a coherent representation of the main approaches to analyze the dynamics of cellular automata. Cellular automata are an inevitable tool in mathematical modeling. In contrast to classical modeling approaches as partial differential equations, cellular automata are straightforward to simulate but hard to analyze. In this book we present a review of approaches and theories that allow the reader to understand the behavior of cellular automata beyond simulations. The first part consists of an introduction of cellular automata on Cayley graphs, and their characterization via the fundamental Cutis-Hedlund-Lyndon theorems in the context of different topological concepts (Cantor, Besicovitch and Weyl topology). The second part focuses on classification results: What classification follows from topological concepts (Hurley classification), Lyapunov stability (Gilman classification), and the theory of formal languages and grammars (Kůrka classification). These classifications suggest to cluster cellular automata, similar to the classification of partial differential equations in hyperbolic, parabolic and elliptic equations. This part of the book culminates in the question, whether properties of cellular automata are decidable. Surjectivity, and injectivity are examined, and the seminal Garden of Eden theorems are discussed. The third part focuses on the analysis of cellular automata that inherit distinct properties, often based on mathematical modeling of biological, physical or chemical systems. Linearity is a concept that allows to define self-similar limit sets. Models for particle motion show how to bridge the gap between cellular automata and partial differential equations (HPP model and ultradiscrete limit). Pattern formation is related to linear cellular automata, to the Bar-Yam model for Turing pattern, and Greenberg-Hastings automata for excitable media. Also models for sandpiles, the dynamics of infectious diseases and evolution of predator-prey systems are discussed. Mathematicians find an overview about theory and tools for the analysis of cellular automata. The book contains an appendix introducing basic mathematical techniques and notations, such that also physicists, chemists and biologists interested in cellular automata beyond pure simulations will benefit.
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    Blasco, Agustín.
    Bayesian Data Analysis for Animal Scientists [Electronic resource] : the Basics / / Agustín. Blasco ; . - 1st ed. 2017. - [S. l. : s. n.]. - XVIII, 275 p. 160 illus., 151 illus. in color. - ISBN 9783319542744
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Рубрики: Agriculture.
   Veterinary medicine.
   Biomathematics.
   Animal genetics.
   Biostatistics.
   Agriculture.
   Veterinary Medicine/Veterinary Science.
   Mathematical and Computational Biology.
   Animal Genetics and Genomics.
   Biostatistics.
Анотація: In this book, we provide an easy introduction to Bayesian inference using MCMC techniques, making most topics intuitively reasonable and deriving to appendixes the more complicated matters. The biologist or the agricultural researcher does not normally have a background in Bayesian statistics, having difficulties in following the technical books introducing Bayesian techniques. The difficulties arise from the way of making inferences, which is completely different in the Bayesian school, and from the difficulties in understanding complicated matters such as the MCMC numerical methods. We compare both schools, classic and Bayesian, underlying the advantages of Bayesian solutions, and proposing inferences based in relevant differences, guaranteed values, probabilities of similitude or the use of ratios. We also give a scope of complex problems that can be solved using Bayesian statistics, and we end the book explaining the difficulties associated to model choice and the use of small samples. The book has a practical orientation and uses simple models to introduce the reader in this increasingly popular school of inference.
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    Diversity and Evolution of Butterfly Wing Patterns [Electronic resource] : an Integrative Approach / / ed.: Sekimura, Toshio., Nijhout, H. Frederik. - 1st ed. 2017. - [S. l. : s. n.]. - XII, 321 p. 103 illus., 89 illus. in color. - ISBN 9789811049569
    Зміст:

Foreword -- Preface -- Contributors -- Part I. The Nympalid Groundplan (NGP) and Diversification -- Chapter1:The common developmental origin of eyespots and parafocal elements;And a new model-mechanism for color pattern formation -- Chapter2:Exploring color pattern diversification in early lineages of Satyrinae (Nymphalidae) -- Chapter3:Camouflage variation on a theme of the Nymphalid Ground Plan -- Chapter4:Morphological evolution repeatedly caused by mutations in signaling ligand genes -- Part II. Eyespots and Evolution -- Chapter5:Physiology and evolution of wing pattern plasticity in Bicyclus butterflies: a critical review ofthe literature -- Chapter6:Spatial variation in boundary conditions can govern selection and location of eyespots inbutterfly wings -- Chapter7:Self-Similarity, Distortion Waves, and the Essence of Morphogenesis: A Generalized View ofColor Pattern Formation in Butterfly Wings -- Part III. Developmental Genetics -- Chapter8:A practical guide to CRISPR/Cas9 genome editing in Lepidoptera -- Chapter9:What can we learn about adaptation from the wing pattern genetics of Heliconiusbutterflies? -- Chapter10:Molecular mechanism and evolutionary process underlying female-limited Batesian mimicry in Papilio polytes -- Part IV. Ecological Aspects and Adaptation -- Chapter11:Chemical Ecology of Poisonous Butterflies: Model or Mimic?— A Paradox of Sexual Dimorphisms in Müllerian Mimicry -- Chapter12:A model for population dynamics of the mimetic butterfly Papilio polytesin Sakishima Islands, Japan (II) -- Chapter13:Evolutionary trends in phenotypic elements of seasonal forms of the tribe Junoniini(Lepidoptera: Nymphalidae) -- Chapter14:Estimating the mating success of male butterflies in the field.-Part V. Color Patterns of Larva and Other Insects -- Chapter15:Molecular Mechanisms of Larval Color Pattern Switch in the Swallowtail Butterfly -- Chapter16:Drosophila guttifera as a model system for elucidating color pattern formation -- Chapter17:Molecular mechanisms underlying color vision and color formation in dragonflies.

Рубрики: Animal genetics.
   Evolutionary biology.
   Biomathematics.
   Developmental biology.
   Entomology.
   Animal Genetics and Genomics.
   Evolutionary Biology.
   Mathematical and Computational Biology.
   Developmental Biology.
   Entomology.
Анотація: This book facilitates an integrative understanding of the development, genetics and evolution of butterfly wing patterns. To develop a deep and realistic understanding of the diversity and evolution of butterfly wing patterns, it is essential and necessary to approach the problem from various kinds of key research fields such as “evo-devo,” “eco-devo,” ”developmental genetics,” “ecology and adaptation,” “food plants,” and “theoretical modeling.” The past decade-and-a-half has seen a veritable revolution in our understanding of the development, genetics and evolution of butterfly wing patterns. In addition, studies of how environmental and climatic factors affect the expression of color patterns has led to increasingly deeper understanding of the pervasiveness and underlying mechanisms of phenotypic plasticity. In recognition of the great progress in research on the biology, an international meeting titled “Integrative Approach to Understanding the Diversity of B utterfly Wing Patterns (IABP-2016)” was held at Chubu University, Japan in August 2016. This book consists of selected contributions from the meeting. Authors include main active researchers of new findings of corresponding genes as well as world leaders in both experimental and theoretical approaches to wing color patterns. The book provides excellent case studies for graduate and undergraduate classes in evolution, genetics/genomics, developmental biology, ecology, biochemistry, and also theoretical biology, opening the door to a new era in the integrative approach to the analysis of biological problems. This book is open access under a CC BY 4.0 license. .
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    Han, Xiaoying.
    Random Ordinary Differential Equations and Their Numerical Solution [Electronic resource] / Xiaoying. Han, Kloeden, Peter E. ; . - 1st ed. 2017. - [S. l. : s. n.]. - XVII, 250 p. 21 illus. in color. - ISBN 9789811062650
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Рубрики: Probabilities.
   Numerical analysis.
   Differential equations.
   Biomathematics.
   Probability Theory and Stochastic Processes.
   Numeric Computing.
   Ordinary Differential Equations.
   Mathematical and Computational Biology.
Анотація: This book is intended to make recent results on the derivation of higher order numerical schemes for random ordinary differential equations (RODEs) available to a broader readership, and to familiarize readers with RODEs themselves as well as the closely associated theory of random dynamical systems. In addition, it demonstrates how RODEs are being used in the biological sciences, where non-Gaussian and bounded noise are often more realistic than the Gaussian white noise in stochastic differential equations (SODEs). RODEs are used in many important applications and play a fundamental role in the theory of random dynamical systems. They can be analyzed pathwise with deterministic calculus, but require further treatment beyond that of classical ODE theory due to the lack of smoothness in their time variable. Although classical numerical schemes for ODEs can be used pathwise for RODEs, they rarely attain their traditional order since the solutions of RODEs do not have sufficient smoothness to have Taylor expansions in the usual sense. However, Taylor-like expansions can be derived for RODEs using an iterated application of the appropriate chain rule in integral form, and represent the starting point for the systematic derivation of consistent higher order numerical schemes for RODEs. The book is directed at a wide range of readers in applied and computational mathematics and related areas as well as readers who are interested in the applications of mathematical models involving random effects, in particular in the biological sciences.The level of this book is suitable for graduate students in applied mathematics and related areas, computational sciences and systems biology. A basic knowledge of ordinary differential equations and numerical analysis is required. .
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Kloeden, Peter E.; Han, Xiaoying. \.\
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    Börgers, Christoph.
    An Introduction to Modeling Neuronal Dynamics [Electronic resource] / Christoph. Börgers ; . - 1st ed. 2017. - [S. l. : s. n.]. - XIII, 457 p. 356 illus., 186 illus. in color. - ISBN 9783319511719
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Рубрики: Neural networks (Computer science) .
   Biomathematics.
   Neurosciences.
   Statistical physics.
   Vibration.
   Dynamical systems.
   Dynamics.
   Mathematical Models of Cognitive Processes and Neural Networks.
   Mathematical and Computational Biology.
   Neurosciences.
   Statistical Physics and Dynamical Systems.
   Vibration, Dynamical Systems, Control.
Анотація: This book is intended as a text for a one-semester course on Mathematical and Computational Neuroscience for upper-level undergraduate and beginning graduate students of mathematics, the natural sciences, engineering, or computer science. An undergraduate introduction to differential equations is more than enough mathematical background. Only a slim, high school-level background in physics is assumed, and none in biology. Topics include models of individual nerve cells and their dynamics, models of networks of neurons coupled by synapses and gap junctions, origins and functions of population rhythms in neuronal networks, and models of synaptic plasticity. An extensive online collection of Matlab programs generating the figures accompanies the book. .
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    Goriely, Alain.
    The Mathematics and Mechanics of Biological Growth [Electronic resource] / Alain. Goriely ; . - 1st ed. 2017. - [S. l. : s. n.]. - XXII, 646 p. 341 illus. - ISBN 9780387877105
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Рубрики: Biomathematics.
   Biophysics.
   Biological physics.
   Developmental biology.
   Cell physiology.
   Mechanics.
   Mathematical and Computational Biology.
   Biological and Medical Physics, Biophysics.
   Developmental Biology.
   Cell Physiology.
   Classical Mechanics.
Анотація: This monograph presents a general mechanical theory for biological growth. It provides both a conceptual and a technical foundation for the understanding and analysis of problems arising in biology and physiology. The theory and methods is illustrated on a wide range of examples and applications. A process of extreme complexity, growth plays a fundamental role in many biological processes and is considered to be the hallmark of life itself. Its description has been one of the fundamental problems of life sciences, but until recently, it has not attracted much attention from mathematicians, physicists, and engineers. The author herein presents the first major technical monograph on the problem of growth since D’Arcy Wentworth Thompson’s 1917 book On Growth and Form. The emphasis of the book is on the proper mathematical formulation of growth kinematics and mechanics. Accordingly, the discussion proceeds in order of complexity and the book is divided into five parts. First, a general introduction on the problem of growth from a historical perspective is given. Then, basic concepts are introduced within the context of growth in filamentary structures. These ideas are then generalized to surfaces and membranes and eventually to the general case of volumetric growth. The book concludes with a discussion of open problems and outstanding challenges. Thoughtfully written and richly illustrated to be accessible to readers of varying interests and background, the text will appeal to life scientists, biophysicists, biomedical engineers, and applied mathematicians alike.
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10.

    Wollkind, David J.
    Comprehensive Applied Mathematical Modeling in the Natural and Engineering Sciences [Electronic resource] : theoretical Predictions Compared with Data / / David J. Wollkind, Dichone, Bonni J. ; . - 1st ed. 2017. - [S. l. : s. n.]. - XXI, 607 p. 134 illus., 16 illus. in color. - ISBN 9783319735184
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Рубрики: Mathematical models.
   Biomathematics.
   Mathematical physics.
   Mathematical Modeling and Industrial Mathematics.
   Mathematical and Computational Biology.
   Mathematical Applications in the Physical Sciences.
Анотація: This text demonstrates the process of comprehensive applied mathematical modeling through the introduction of various case studies. The case studies are arranged in increasing order of complexity based on the mathematical methods required to analyze the models. The development of these methods is also included, providing a self-contained presentation. To reinforce and supplement the material introduced, original problem sets are offered involving case studies closely related to the ones presented. With this style, the text’s perspective, scope, and completeness of the subject matter are considered unique. Having grown out of four self-contained courses taught by the authors, this text will be of use in a two-semester sequence for advanced undergraduate and beginning graduate students, requiring rudimentary knowledge of advanced calculus and differential equations, along with a basic understanding of some simple physical and biological scientific principles. .
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11.

    Research in Computational Molecular Biology [Electronic resource] : 21st Annual International Conference, RECOMB 2017, Hong Kong, China, May 3-7, 2017, Proceedings / / ed. Sahinalp, S. Cenk. - 1st ed. 2017. - [S. l. : s. n.]. - XIV, 406 p. 104 illus. - ISBN 9783319569703
    Зміст:

Boosting alignment accuracy by adaptive local realignment -- A concurrent subtractive assembly approach for identification of disease associated sub-meta-genomes -- A flow procedure for the linearization of genome variation graphs -- Dynamic alignment-free and reference-free read compression -- A fast approximate algorithm for mapping long reads to large reference databases -- Determining the consistency of resolved triplets and fan triplets -- Progressive calibration and averaging for tandem mass spectrometry statistical confidence estimation: Why settle for a single decoy -- Resolving multi-copy duplications de novo using polyploid phasing -- A Bayesian active learning experimental design for inferring signaling networks -- BBK* (Branch and Bound over K*): A provable and efficient ensemble-based algorithm to optimize stability and binding affinity over large sequence spaces -- Super-bubbles, ultra-bubbles and cacti -- EPR-dictionaries: A practical and fast data structure for constant time searches in unidirectional and bidirectional FM indices -- A Bayesian framework for estimating cell type composition from DNA methylation without the need for methylation reference -- Towards recovering Allele-specific cancer genome graphs -- Using stochastic approximation techniques to efficiently construct confidence intervals for heritability -- Improved search of large transcriptomic sequencing databases using split sequence bloom trees -- All some sequence bloom trees -- Longitudinal genotype-phenotype association study via temporal structure auto-learning predictive model -- Improving imputation accuracy by inferring causal variants in genetic studies -- The copy-number tree mixture deconvolution problem and applications to multi-sample bulk sequencing tumor data -- Quantifying the impact of non-coding variants on transcription factor-DNA binding -- aBayesQR: A Bayesian method for reconstruction of viral populations characterized by low diversity -- BeWith: A between-within method for module discovery in cancer using integrated analysis of mutual exclusivity, co-occurrence and functional interactions -- K-mer Set Memory (KSM) motif representation enables accurate prediction of the impact of regulatory variants -- Network-based coverage of mutational profiles reveals cancer genes -- Ultra-accurate complex disorder prediction: case study of neurodevelopmental disorders -- Inference of the human polyadenylation Code -- Folding membrane proteins by deep transfer learning -- A network integration approach for drug-target interaction prediction and computational drug repositioning from heterogeneous information -- Epistasis in genomic and survival data of cancer patients -- Ultra-fast identity by descent detection in biobank-scale cohorts using positional burrows-wheeler transform -- Joker de Bruijn: sequence libraries to cover all k-mers using joker characters -- GATTACA: Lightweight metagenomic binning using kmer counting -- Species tree estimation using ASTRAL: how many genes are enough -- Reconstructing antibody repertoires from error-prone immune-sequencing datasets -- NetREX: Network rewiring using EXpression - Towards context specific regulatory networks -- E pluribus unum: United States of single cells -- ROSE: a deep learning based framework for predicting ribosome stalling. .

Рубрики: Bioinformatics.
   Biomathematics.
   Artificial intelligence.
   Optical data processing.
   Database management.
   Computational Biology/Bioinformatics.
   Mathematical and Computational Biology.
   Artificial Intelligence.
   Image Processing and Computer Vision.
   Database Management.
Анотація: This book constitutes the proceedings of the 21th Annual Conference on Research in Computational Molecular Biology, RECOMB 2017, held in Hong Kong, China, in May 2017. The 22 regular papers presented in this volume were carefully reviewed and selected from 184 submissions. 16 short abstracts are included in the back matter of the volume. They report on original research in all areas of computational molecular biology and bioinformatics.
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12.

    Zimmermann, Georg.
    From Basic Survival Analytic Theory to a Non-Standard Application [Electronic resource] / Georg. Zimmermann ; . - 1st ed. 2017. - [S. l. : s. n.]. - IX, 100 p. 9 illus. - ISBN 9783658177195
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Рубрики: Probabilities.
   Biomathematics.
   Probability Theory and Stochastic Processes.
   Mathematical and Computational Biology.
Анотація: Georg Zimmermann provides a mathematically rigorous treatment of basic survival analytic methods. His emphasis is also placed on various questions and problems, especially with regard to life expectancy calculations arising from a particular real-life dataset on patients with epilepsy. The author shows both the step-by-step analyses of that dataset and the theory the analyses are based on. He demonstrates that one may face serious and sometimes unexpected problems, even when conducting very basic analyses. Moreover, the reader learns that a practically relevant research question may look rather simple at first sight. Nevertheless, compared to standard textbooks, a more detailed account of the theory underlying life expectancy calculations is needed in order to provide a mathematically rigorous framework. Contents Regression Models for Survival Data Model Checking Procedures Life Expectancy Target Groups Researchers, lecturers, and students in the fields of mathematics and statistics Academics and experts working in the life sciences, especially in the medical field The Author Georg Zimmermann is a PhD student at the University of Salzburg and research associate at Christian-Doppler-Klinik, Salzburg.
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13.

    Suzuki, Takashi.
    Mathematical Methods for Cancer Evolution [Electronic resource] / Takashi. Suzuki ; . - 1st ed. 2017. - [S. l. : s. n.]. - VII, 144 p. 23 illus. - ISBN 9789811036712
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Рубрики: Biomathematics.
   Partial differential equations.
   Mathematical and Computational Biology.
   Partial Differential Equations.
Анотація: The purpose of this monograph is to describe recent developments in mathematical modeling and mathematical analysis of certain problems arising from cell biology. Cancer cells and their growth via several stages are of particular interest. To describe these events, multi-scale models are applied, involving continuously distributed environment variables and several components related to particles. Hybrid simulations are also carried out, using discretization of environment variables and the Monte Carlo method for the principal particle variables. Rigorous mathematical foundations are the bases of these tools. The monograph is composed of four chapters. The first three chapters are concerned with modeling, while the last one is devoted to mathematical analysis. The first chapter deals with molecular dynamics occurring at the early stage of cancer invasion. A pathway network model based on a biological scenario is constructed, and then its mathematical structures are determined. In the second chapter mathematical modeling is introduced, overviewing several biological insights, using partial differential equations. Transport and gradient are the main factors, and several models are introduced including the Keller‒Segel systems. The third chapter treats the method of averaging to model the movement of particles, based on mean field theories, employing deterministic and stochastic approaches. Then appropriate parameters for stochastic simulations are examined. The segment model is finally proposed as an application. In the fourth chapter, thermodynamic features of these models and how these structures are applied in mathematical analysis are examined, that is, negative chemotaxis, parabolic systems with non-local term accounting for chemical reactions, mass-conservative reaction-diffusion systems, and competitive systems of chemotaxis. The monograph concludes with the method of the weak scaling limit applied to the Smoluchowski‒Poisson equation.
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Suzuki, Takashi. \.\
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14.

    Algorithms for Computational Biology [Electronic resource] : 4th International Conference, AlCoB 2017, Aveiro, Portugal, June 5-6, 2017, Proceedings / / ed. Figueiredo, Daniel. [et al.]. - 1st ed. 2017. - [S. l. : s. n.]. - X, 181 p. 68 illus. - ISBN 9783319581637
    Зміст:

Рубрики: Bioinformatics.
   Algorithms.
   Computer science—Mathematics.
   Data mining.
   Biomathematics.
   Computational Biology/Bioinformatics.
   Algorithm Analysis and Problem Complexity.
   Discrete Mathematics in Computer Science.
   Data Mining and Knowledge Discovery.
   Mathematical and Computational Biology.
Анотація: This book constitutes the proceedings of the 4th InternationalConference on Algorithms for Computational Biology, AlCoB 2017, held in Aveiro, Portugal, in June 2017. The 10 full papers presented together with 2 invited papers were carefully reviewed and selected from 24 submissions. They are organized in the following topical sections: Graph Algorithms for Computational Biology; Phylogenetics; and Sequence Analysis and Other Biological Processes.
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Figueiredo, Daniel. \ed.\; Martín-Vide, Carlos. \ed.\; Pratas, Diogo. \ed.\; Vega-Rodríguez, Miguel A. \ed.\
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15.

    Computational Diffusion MRI [Electronic resource] : MICCAI Workshop, Athens, Greece, October 2016 / / ed. Fuster, Andrea. [et al.]. - 1st ed. 2017. - [S. l. : s. n.]. - XI, 212 p. 70 illus., 66 illus. in color. - ISBN 9783319541303
    Зміст:

Рубрики: Biomathematics.
   Mathematics.
   Visualization.
   Computer simulation.
   Optical data processing.
   Statistics .
   Mathematical and Computational Biology.
   Visualization.
   Simulation and Modeling.
   Image Processing and Computer Vision.
   Statistics for Life Sciences, Medicine, Health Sciences.
Анотація: This volume offers a valuable starting point for anyone interested in learning computational diffusion MRI and mathematical methods for brain connectivity, while also sharing new perspectives and insights on the latest research challenges for those currently working in the field. Over the last decade, interest in diffusion MRI has virtually exploded. The technique provides unique insights into the microstructure of living tissue and enables in-vivo connectivity mapping of the brain. Computational techniques are key to the continued success and development of diffusion MRI and to its widespread transfer into the clinic, while new processing methods are essential to addressing issues at each stage of the diffusion MRI pipeline: acquisition, reconstruction, modeling and model fitting, image processing, fiber tracking, connectivity mapping, visualization, group studies and inference. These papers from the 2016 MICCAI Workshop “Computational Diffusion MRI” – which was intended to provide a snapshot of the latest developments within the highly active and growing field of diffusion MR – cover a wide range of topics, from fundamental theoretical work on mathematical modeling, to the development and evaluation of robust algorithms and applications in neuroscientific studies and clinical practice. The contributions include rigorous mathematical derivations, a wealth of rich, full-color visualizations, and biologically or clinically relevant results. As such, they will be of interest to researchers and practitioners in the fields of computer science, MR physics, and applied mathematics. .
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Fuster, Andrea. \ed.\; Ghosh, Aurobrata. \ed.\; Kaden, Enrico. \ed.\; Rathi, Yogesh. \ed.\; Reisert, Marco. \ed.\
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16.

    Algorithms for Next-Generation Sequencing Data [Electronic resource] : techniques, Approaches, and Applications / / ed. Elloumi, Mourad. - 1st ed. 2017. - [S. l. : s. n.]. - XIII, 355 p. 108 illus., 3 illus. in color. - ISBN 9783319598260
Рубрики: Bioinformatics.
   Biomathematics.
   Algorithms.
   Computational Biology/Bioinformatics.
   Mathematical and Computational Biology.
   Bioinformatics.
   Algorithm Analysis and Problem Complexity.
Анотація: The 14 contributed chapters in this book survey the most recent developments in high-performance algorithms for NGS data, offering fundamental insights and technical information specifically on indexing, compression and storage; error correction; alignment; and assembly. The book will be of value to researchers, practitioners and students engaged with bioinformatics, computer science, mathematics, statistics and life sciences.
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Elloumi, Mourad. \ed.\
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17.

    Smirnova, Olga A.
    Environmental Radiation Effects on Mammals [Electronic resource] : a Dynamical Modeling Approach / / Olga A. Smirnova ; . - 2nd ed. 2017. - [S. l. : s. n.]. - XXIII, 359 p. 203 illus., 4 illus. in color. - ISBN 9783319457611
    Зміст:

Рубрики: Biophysics.
   Biological physics.
   Occupational medicine.
   Aerospace engineering.
   Astronautics.
   Radiology.
   Animal physiology.
   Biomathematics.
   Biological and Medical Physics, Biophysics.
   Occupational Medicine/Industrial Medicine.
   Aerospace Technology and Astronautics.
   Imaging / Radiology.
   Animal Physiology.
   Mathematical and Computational Biology.
Анотація: Dr. Smirnova's updated text is devoted to the theoretical studies of radiation effects on mammals. It summarizes 35 years of results the author obtained from analyzing dose rate equivalents for the Galactic Cosmic Rays (GCR) and for Solar Particles Events (SPE). This edition also includes two new chapters on skin epidermal epithelium and risk assessment for myeloid leukemia, as well as extended revisions addressing the radiation effects on the blood-forming system. Mathematical models are used to explain the effects of both acute and chronic irradiation on the dynamics of vital body systems, like the hematopoietic system, the development of autoimmune diseases, and the mortality dynamics in homogeneous and nonhomogeneous mammalian populations. The proposed methodology of these studies, the models themselves, and the obtained results are of a great theoretical significance and can find wide practical use. .
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Smirnova, Olga A. \.\
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18.

    Scherer, Philipp O. J.
    Theoretical Molecular Biophysics [Electronic resource] / Philipp O. J. Scherer, Fischer, Sighart F. ; . - 2nd ed. 2017. - [S. l. : s. n.]. - XVI, 513 p. 226 illus., 27 illus. in color. - ISBN 9783662556719
    Зміст:

Рубрики: Biophysics.
   Biological physics.
   Biomathematics.
   Biomedical engineering.
   Proteins .
   Biochemical engineering.
   Biological and Medical Physics, Biophysics.
   Mathematical and Computational Biology.
   Biomedical Engineering and Bioengineering.
   Protein Science.
   Biochemical Engineering.
Анотація: This book gives an introduction to molecular biophysics. It starts from material properties at equilibrium related to polymers, dielectrics and membranes. Electronic spectra are developed for the understanding of elementary dynamic processes in photosynthesis including proton transfer and dynamics of molecular motors. Since the molecular structures of functional groups of bio-systems were resolved, it has become feasible to develop a theory based on the quantum theory and statistical physics with emphasis on the specifics of the high complexity of bio-systems. This introduction to molecular aspects of the field focuses on solvable models. Elementary biological processes provide as special challenge the presence of partial disorder in the structure which does not destroy the basic reproducibility of the processes. Apparently the elementary molecular processes are organized in a way to optimize the efficiency. Learning from nature by means exploring the relation between structure and function may even help to build better artificial solar cells. The reader is exposed to basic concepts in modern biophysics, such as entropic forces, phase separation, potential of mean force, electron and proton transfer, heterogeneous reactions, coherent and incoherent energy transfer as well as molecular motors. Basic knowledge in classical and Quantum mechanics, electrostatics and statistical physics is desirable. Simplified models are presented which can be solved in limited cases analytically from the guiding lines to generate the basis for a fundamental understanding of the more complex biophysical systems. Chapters close with challenging problems whose solutions are provided at the end of the book to complete the pedagogical treatment in the book. To the second edition several new chapters were added. The medium polarization is treated self-consistently using basic elements of polaron theory and more advanced nonlinear Schrödinger equations to describe the dynamics of solvation. Ion transport through a membrane was extended by the discussion of cooperative effects. Intramolecular transitions are now discussed in the new edition in much more detail, including also radiationless transitions. Very recent developments in spectroscopy are included, especially two-dimensional and hole-burning spectroscopy. The discussion of charge transfer processes was extended by including recent results of hole transfer in DNA in connection with the super-exchange mechanism. The chapter on molecular motors was rewritten to include the most recent developments of new models. The book is a useful text for students and researchers wanting to go through the mathematical derivations in the theories presented. This book attracts a group of applied mathematically oriented students and scholars to the exciting field of molecular biophysics. .
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Fischer, Sighart F.; Scherer, Philipp O.J. \.\
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19.

    Louie, A. H.
    Intangible Life [Electronic resource] : functorial Connections in Relational Biology / / A. H. Louie ; . - 1st ed. 2017. - [S. l. : s. n.]. - XXIII, 264 p. 4 illus. - ISBN 9783319654096
    Зміст:

Рубрики: Biomathematics.
   Biology—Philosophy.
   Category theory (Mathematics).
   Homological algebra.
   Life sciences.
   Physics.
   Mathematical and Computational Biology.
   Philosophy of Biology.
   Category Theory, Homological Algebra.
   Life Sciences, general.
   Applications of Graph Theory and Complex Networks.
Анотація: This rare publication continues an exploratory journey in relational biology, a study of biology in terms of the organization of networked connections in living systems. It builds on the author’s two earlier monographs which looked at the epistemology of life and the ontogeny of life. Here the emphasis is on the intangibility of life, that the real nature of living systems is conveyed not by their tangible material basis but by their intangible inherent processes. Relational biology is the approach that hails ‘function dictates structure’; it is mathematics decoded into biological realizations. Therefore, the work begins with a concise introduction to category theory, equiping the reader with the mathematical metalanguage of relation biology. The book is organized around three parts: Part I is a comprehensive study of the most important functor in relational biology, the power set functor. The author lays the set-theoretic foundations of the functorial connections in relational biology, exploring relations, mappings, and set-valued mappings. In Part II, Natural Law receives a new mathematical formulation founded on two axioms: ‘Everything is a set.’ and ‘Every process is a set-valued mapping.’ The reader sees how Metabolism–Repair networks, equipped with set-valued processors, expand their role from models of biological entities to generic models of all natural systems. Part III expounds the various shades of invertibility in general, and the inversion of encoding to decoding in particular. A plethora of mathematical and biological examples illustrate the category-theoretic concepts of equivalence and adjunction. This book's algebraic approach to biological models will appeal to researchers and graduate students in mathematics, biology, and the philosophy of science.
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Louie, A.H. \.\
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20.

    Scott, L. Ridgway.
    A Mathematical Approach to Protein Biophysics [Electronic resource] / L. Ridgway. Scott, Fernández, Ariel. ; . - 1st ed. 2017. - [S. l. : s. n.]. - XI, 290 p. 110 illus., 27 illus. in color. - ISBN 9783319660325
    Зміст:

Рубрики: Biomathematics.
   Systems biology.
   Biological systems.
   Proteins .
   Medical biochemistry.
   Mathematical and Computational Biology.
   Systems Biology.
   Protein Science.
   Medical Biochemistry.
Анотація: This book explores quantitative aspects of protein biophysics and attempts to delineate certain rules of molecular behavior that make atomic scale objects behave in a digital way. This book will help readers to understand how certain biological systems involving proteins function as digital information systems despite the fact that underlying processes are analog in nature. The in-depth explanation of proteins from a quantitative point of view and the variety of level of exercises (including physical experiments) at the end of each chapter will appeal to graduate and senior undergraduate students in mathematics, computer science, mechanical engineering, and physics, wanting to learn about the biophysics of proteins. L. Ridgway Scott has been Professor of Computer Science and of Mathematics at the University of Chicago since 1998, and the Louis Block Professor since 2001. He obtained a B.S. degree (Magna Cum Laude) from Tulane University in 1969 and a PhD degree in Mathematics from the Massachusetts Institute of Technology in 1973. Professor Scott has published over 130 papers and three books, extending over biophysics, parallel computing and fundamental computing aspects of structural mechanics, fluid dynamics, nuclear engineering, and computational chemistry. Ariel Fernández (born Ariel Fernández Stigliano) is an Argentinian-American physical chemist and mathematician. He obtained his Ph. D. degree in Chemical Physics from Yale University and held the Karl F. Hasselmann Endowed Chair Professorship in Bioengineering at Rice University. He is currently involved in research and entrepreneurial activities at various consultancy firms. Ariel Fernández authored three books on translational medicine and biophysics, and published 360 papers in professional journals. He holds two patents in the field of biotechnology.
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Fernández, Ariel.; Scott, L. Ridgway. \.\
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