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Elsevier

Books in Mathematical biosciences

The Mathematical Biosciences portfolio integrates advanced mathematical modelling, computational biology, systems biology, and data analysis. Featuring interdisciplinary research, these resources support scientists, bioinformaticians, and students in understanding complex biological processes, disease dynamics, and ecological systems. Emphasizing innovation in quantitative methods, the portfolio offers actionable insights for tackling global health issues, environmental challenges, and biotechnological advancements through rigorous, data-driven approaches.

  • Computational Modelling of Biomechanics and Biotribology in the Musculoskeletal System

    Biomaterials and Tissues
    • 2nd Edition
    • Z Jin + 2 more
    • English
    Computational Modelling of Biomechanics and Biotribology in the Musculoskeletal System: Biomaterials and Tissues, Second Edition reviews how a wide range of materials are modeled and applied. Chapters cover basic concepts for modeling of biomechanics and biotribology, the fundamentals of computational modeling of biomechanics in the musculoskeletal system, finite element modeling in the musculoskeletal system, computational modeling from a cells and tissues perspective, and computational modeling of the biomechanics and biotribology interactions, looking at complex joint structures. This book is a comprehensive resource for professionals in the biomedical market, materials scientists and biomechanical engineers, and academics in related fields. This important new edition provides an up-to-date overview of the most recent research and developments involving hydroxyapatite as a key material in medicine and its application, including new content on novel technologies, biomorphic hydroxyapatite and more.

  • Bioinformatics Algorithms

    Design and Implementation in Python
    • 1st Edition
    • Miguel Rocha + 1 more
    • English
    Bioinformatics Algorithms: Design and Implementation in Python provides a comprehensive book on many of the most important bioinformatics problems, putting forward the best algorithms and showing how to implement them. The book focuses on the use of the Python programming language and its algorithms, which is quickly becoming the most popular language in the bioinformatics field. Readers will find the tools they need to improve their knowledge and skills with regard to algorithm development and implementation, and will also uncover prototypes of bioinformatics applications that demonstrate the main principles underlying real world applications.

  • Personalized Predictive Modeling in Type 1 Diabetes

    • 1st Edition
    • Eleni I. Georga + 2 more
    • English
    Personalized Predictive Modeling in Diabetes features state-of-the-art methodologies and algorithmic approaches which have been applied to predictive modeling of glucose concentration, ranging from simple autoregressive models of the CGM time series to multivariate nonlinear regression techniques of machine learning. Developments in the field have been analyzed with respect to: (i) feature set (univariate or multivariate), (ii) regression technique (linear or non-linear), (iii) learning mechanism (batch or sequential), (iv) development and testing procedure and (v) scaling properties. In addition, simulation models of meal-derived glucose absorption and insulin dynamics and kinetics are covered, as an integral part of glucose predictive models. This book will help engineers and clinicians to: select a regression technique which can capture both linear and non-linear dynamics in glucose metabolism in diabetes, and which exhibits good generalization performance under stationary and non-stationary conditions; ensure the scalability of the optimization algorithm (learning mechanism) with respect to the size of the dataset, provided that multiple days of patient monitoring are needed to obtain a reliable predictive model; select a features set which efficiently represents both spatial and temporal dependencies between the input variables and the glucose concentration; select simulation models of subcutaneous insulin absorption and meal absorption; identify an appropriate validation procedure, and identify realistic performance measures.

  • Multi-Scale Approaches in Drug Discovery

    From Empirical Knowledge to In silico Experiments and Back
    • 1st Edition
    • Alejandro Speck-Planche
    • English
    Drug discovery is an expensive, time-consuming process and the modern drug discovery community is constantly challenged not only with discovering novel bioactive agents to combat resistance from known diseases and fight against new ones, but to do so in a way that is economically effective. Advances in both experimental and theoretical/computat... methods envisage that the greatest challenges in drug discovery can be most successfully addressed by using a multi-scale approach, drawing on the specialties of a whole host of different disciplines. Multi-Scale Approaches to Drug Discovery furnishes chemists with the detail they need to identify drug leads with the highest potential before isolating and synthesizing them to produce effective drugs with greater swiftness than classical methods may allow. This significantly speeds up the search for more efficient therapeutic agents. After an introduction to multi-scale approaches outlining the need for and benefits of their use, the book goes on to explore a range of useful techniques and research areas, and their potential applications to this process. Profiling drug binding by thermodynamics, machine learning for predicting enzyme sub-classes, and multitasking models for computer-aided design and virtual compound screening are discussed, before the book goes on to review Alkaloid Menispermaceae leads, natural chemotherapeutic agents and methods for speeding up the design and virtual screening of therapeutic peptides. Flavonoids as multi-target compounds are then explored, before the book concludes with a review of Quasi-SMILES as a novel tool. Collecting together reviews and original research contributions written by leading experts in the field, Multi-Scale Approaches to Drug Discovery highlights cutting-edge approaches and practical examples of their implementation for those involved in the drug discovery process at many different levels. Using the combined knowledge of medicinal, computational, pharmaceutical and bio- chemists, it aims to support growth in the multi-scale approach to promote greater success in the development of new drugs.

  • Mathematical Biology

    A Conference on Theoretical Aspects of Molecular Science
    • 1st Edition
    • T. A. Burton
    • English
    Mathematical Biology: A Conference on Theoretical Aspects of Molecular Science is a collection of papers that covers various investigations in mathematical biology. The text tackles a wide range of topics, from biological equation models up to electrical phenomena in biological systems. The coverage of the text includes existence of a periodic solution for a two predator-one prey ecosystem modeled on a chemostat; mathematical treatment of nerve conduction and cardiac purkinje fibers; and models of positional information. The book will be of great interest to students, researchers, and practitioners of biological sciences.

  • Computational Modelling of Biomechanics and Biotribology in the Musculoskeletal System

    Biomaterials and Tissues
    • 1st Edition
    • Z Jin
    • English
    Computational Modelling of Biomechanics and Biotribology in the Musculoskeletal System reviews how a wide range of materials are modelled and how this modelling is applied. Computational modelling is increasingly important in the design and manufacture of biomedical materials, as it makes it possible to predict certain implant-tissue reactions, degradation, and wear, and allows more accurate tailoring of materials' properties for the in vivo environment. Part I introduces generic modelling of biomechanics and biotribology with a chapter on the fundamentals of computational modelling of biomechanics in the musculoskeletal system, and a further chapter on finite element modelling in the musculoskeletal system. Chapters in Part II focus on computational modelling of musculoskeletal cells and tissues, including cell mechanics, soft tissues and ligaments, muscle biomechanics, articular cartilage, bone and bone remodelling, and fracture processes in bones. Part III highlights computational modelling of orthopedic biomaterials and interfaces, including fatigue of bone cement, fracture processes in orthopedic implants, and cementless cup fixation in total hip arthroplasty (THA). Finally, chapters in Part IV discuss applications of computational modelling for joint replacements and tissue scaffolds, specifically hip implants, knee implants, and spinal implants; and computer aided design and finite element modelling of bone tissue scaffolds. This book is a comprehensive resource for professionals in the biomedical market, materials scientists and mechanical engineers, and those in academia.

  • Computational Neuroscience

    • 1st Edition
    • Volume 123
    • English
    Progress in Molecular Biology and Translational Science provides a forum for discussion of new discoveries, approaches, and ideas in molecular biology. It contains contributions from leaders in their fields and abundant references. This volume brings together different aspects of, and approaches to, molecular and multi-scale modeling, with applications to a diverse range of neurological diseases. Mathematical and computational modeling offers a powerful approach for examining the interaction between molecular pathways and ionic channels in producing neuron electrical activity. It is well accepted that non-linear interactions among diverse ionic channels can produce unexpected neuron behavior and hinder a deep understanding of how ion channel mutations bring about abnormal behavior and disease. Interactions with the diverse signaling pathways activated by G protein coupled receptors or calcium influx adds an additional level of complexity. Modeling is an approach to integrate myriad data sources into a cohesive and quantitative model in order to evaluate hypotheses about neuron function. In particular, a validated model developed using in vitro data allows simulations of the response to in vivo like spatio-temporal patterns of synaptic input. Incorporating molecular signaling pathways into an electrical model, allows a greater range of models to be developed, ones that can predict the response to pharmaceuticals, many of which target neuromodulator pathways.

  • Vapour–Liquid Equilibrium Data at Normal Pressures

    • 1st Edition
    • Eduard Hála + 2 more
    • English
    Vapour-Liquid Equilibrium Data at Normal Pressures presents the direct experimental data of a set of selected systems and correlates the data with the aid of equations expressing the dependence of the activity coefficients or separation functions on the composition of the liquid phase. In the last columns of the tables, the deviations of the calculated from the direct experimental data are presented which give information on the quality of the data and on the flexibility of the correlation relations used. The text also describes the correlation of data in two-, three-, four-, and more than four-component systems.

  • Logistics and Benefits of Using Mathematical Models of Hydrologic and Water Resource Systems

    Selected Papers with Summary of Discussions from the International Symposium on Logistics and Benefits of Using Mathematical Models of Hydrologic and Water Resource Systems, Pisa, Italy, 24—26 October 1978
    • 1st Edition
    • A.J. Askew + 2 more
    • English
    Logistics and Benefits of Using Mathematical Models of Hydrologic and Water Resource Systems is a collection of paper that details the experiences in the operational and logistical aspects of utilizing water resource models. The title provides the general report on model structure and classification; experiences of the hydrologic engineering center in maintaining widely used hydrologic and water resource computer models; and the operational experience of on-line hydrological simulation. The selection also covers the implementation and application of a suite for the simulation of complex water resource systems in evaluation and planning studies; and the use of a groundwater model in the design, performance; and the assessment, and operation of a river regulation scheme. The book will be of great use to researchers and practitioners of hydrological sciences.

  • Geometric Morphometrics for Biologists

    A Primer
    • 2nd Edition
    • Miriam Zelditch + 2 more
    • English
    The first edition of Geometric Morphometrics for Biologists has been the primary resource for teaching modern geometric methods of shape analysis to biologists who have a stronger background in biology than in multivariate statistics and matrix algebra. These geometric methods are appealing to biologists who approach the study of shape from a variety of perspectives, from clinical to evolutionary, because they incorporate the geometry of organisms throughout the data analysis. The second edition of this book retains the emphasis on accessible explanations, and the copious illustrations and examples of the first, updating the treatment of both theory and practice. The second edition represents the current state-of-the-art and adds new examples and summarizes recent literature, as well as provides an overview of new software and step-by-step guidance through details of carrying out the analyses.

  • Modern Computational Approaches to Traditional Chinese Medicine

    • 1st Edition
    • Zhaohui Wu + 2 more
    • English
    Recognized as an essential component of Chinese culture, Traditional Chinese Medicine (TCM) is both an ancient medical system and one still used widely in China today. TCM’s independently evolved knowledge system is expressed mainly in the Chinese language and the information is frequently only available through ancient classics and confidential family records, making it difficult to utilize. The major concern in TCM is how to consolidate and integrate the data, enabling efficient retrieval and discovery of novel knowledge from the dispersed data. Computational approaches such as data mining, semantic reasoning and computational intelligence have emerged as innovative approaches for the reservation and utilization of this knowledge system. Typically, this requires an inter-disciplinary approach involving Chinese culture, computer science, modern healthcare and life sciences. This book examines the computerization of TCM information and knowledge to provide intelligent resources and supporting evidences for clinical decision-making, drug discovery, and education. Recent research results from the Traditional Chinese Medicine Informatics Group of Zhejiang University are presented, gathering in one resource systematic approaches for massive data processing in TCM. These include the utilization of modern Semantic Web and data mining methods for more advanced data integration, data analysis and integrative knowledge discovery. This book will appeal to medical professionals, life sciences students, computer scientists, and those interested in integrative, complementary, and alternative medicine.

  • Matlab® in Bioscience and Biotechnology

    • 1st Edition
    • Leonid Burstein
    • English
    MATLAB® in bioscience and biotechnology presents an introductory Matlab course oriented towards various collaborative areas of biotechnology and bioscience. It concentrates on Matlab fundamentals and gives examples of its application to a wide range of current bioengineering problems in computational biology, molecular biology, bio-kinetics, biomedicine, bioinformatics, and biotechnology. In the last decade Matlab has been presented to students as the first computer program they learn. Consequently, many non-programmer students, engineers and scientists have come to regard it as user-friendly and highly convenient in solving their specific problems. Numerous books are available on programming in Matlab for engineers in general, irrespective of their specialization, or for those specializing in some specific area, but none have been designed especially for such a wide, interdisciplinary, and topical area as bioengineering. Thus, in this book, Matlab is presented with examples and applications to various school-level and advanced bioengineering problems - from growing populations of microorganisms and population dynamics, reaction kinetics and reagent concentrations, predator-prey models, mass-transfer and flow problems, to sequence analysis and sequence statistics.

  • Computer Methods Part B

    • 1st Edition
    • Volume 467
    • English
    The combination of faster, more advanced computers and more quantitatively oriented biomedical researchers has recently yielded new and more precise methods for the analysis of biomedical data. These better analyses have enhanced the conclusions that can be drawn from biomedical data, and they have changed the way that experiments are designed and performed. This volume, along with previous and forthcoming Computer Methods volumes for the Methods in Enzymology serial, aims to inform biomedical researchers about recent applications of modern data analysis and simulation methods as applied to biomedical research.

  • Probabilistic Methods for Bioinformatics

    with an Introduction to Bayesian Networks
    • 1st Edition
    • Richard E. Neapolitan
    • English
    The Bayesian network is one of the most important architectures for representing and reasoning with multivariate probability distributions. When used in conjunction with specialized informatics, possibilities of real-world applications are achieved. Probabilistic Methods for BioInformatics explains the application of probability and statistics, in particular Bayesian networks, to genetics. This book provides background material on probability, statistics, and genetics, and then moves on to discuss Bayesian networks and applications to bioinformatics. Rather than getting bogged down in proofs and algorithms, probabilistic methods used for biological information and Bayesian networks are explained in an accessible way using applications and case studies. The many useful applications of Bayesian networks that have been developed in the past 10 years are discussed. Forming a review of all the significant work in the field that will arguably become the most prevalent method in biological data analysis.

  • In Silico

    3D Animation and Simulation of Cell Biology with Maya and MEL
    • 1st Edition
    • Jason Sharpe + 2 more
    • English
    In Silico introduces Maya programming into one of the most fascinating application areas of 3D graphics: biological visualization. In five building-block tutorials, this book prepares animators to work with visualization problems in cell biology. The book assumes no deep knowledge of cell biology or 3D graphics programming. An accompanying DVD-ROM includes code derived from the tutorials, the working Maya computer files, and sample animated movies.

  • Systems Biology

    Philosophical Foundations
    • 1st Edition
    • Fred Boogerd + 3 more
    • English
    Systems biology is a vigorous and expanding discipline, in many ways a successor to genomics and perhaps unprecedented in its combination of biology with a great many other sciences, from physics to ecology, from mathematics to medicine, and from philosophy to chemistry. Studying the philosophical foundations of systems biology may resolve a longer standing issue, i.e., the extent to which Biology is entitled to its own scientific foundations rather than being dominated by existing philosophies.

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