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Computational Spectroscopy of Polyatomic Molecules
by Sergey YurchenkoThis book provides a detailed description of the modern variational methods available for solving the nuclear motion Schrödinger equation to enable accurate theoretical spectroscopy of polyatomic molecules. These methods are currently used to provide important molecular data for spectroscopic studies of atmospheres of astronomical objects including solar and extrasolar planets as well as cool stars. This book has collected descriptions of quantum mechanical methods into one cohesive text, making the information more accessible to the scientific community, especially for young researchers, who would like to devote their scientific career to the field of computational molecular physics. The book addresses key aspects of the high-accuracy computational spectroscopy of the medium size polyatomic molecules. It aims to describe numerical algorithms for the construction and solution of the nuclear motion Schrödinger equations with the central idea of the modern computational spectroscopy of polyatomic molecules to include the construction of the complex kinetic energy operators (KEO) into the computation process of the numerical pipeline by evaluating the corresponding coefficients of KEO derivatives on-the-fly. The book details key aspects of variational solutions of the nuclear motion Schrödinger equations targeting high accuracy, including construction of rotational and vibrational basis functions, coordinate choice, molecular symmetry as well as of intensity calculations and refinement of potential energy functions. The goal of this book is to show how to build an accurate spectroscopic computational protocol in a pure numerical manner of a general black-box type algorithm. This book will be a valuable resource for researchers, both experts and not experts, working in the area of the computational and experimental spectroscopy; PhD students and early-career spectroscopists who would like to learn basics of the modern variational methods in the field of computational spectroscopy. It will also appeal to astrophysicists and atmospheric physicists who would like to assess data and perform calculations themselves. Key features: Supported by the latest research and based on the state-of-the-art computational methods in high-accuracy computational spectroscopy of molecules. Authored by an authority in the field. Accessible to both experts and non-experts working in the area of computational and experimental spectroscopy, in addition to graduate students.
Computational Statics and Dynamics: An Introduction Based on the Finite Element Method
by Andreas ÖchsnerThis book is the 2nd edition of an introduction to modern computational mechanics based on the finite element method. It includes more details on the theory, more exercises, and more consistent notation; in addition, all pictures have been revised. Featuring more than 100 pages of new material, the new edition will help students succeed in mechanics courses by showing them how to apply the fundamental knowledge they gained in the first years of their engineering education to more advanced topics. In order to deepen readers’ understanding of the equations and theories discussed, each chapter also includes supplementary problems. These problems start with fundamental knowledge questions on the theory presented in the respective chapter, followed by calculation problems. In total, over 80 such calculation problems are provided, along with brief solutions for each. This book is especially designed to meet the needs of Australian students, reviewing the mathematics covered in their first two years at university. The 13-week course comprises three hours of lectures and two hours of tutorials per week.
Computational Statics and Dynamics: An Introduction Based on the Finite Element Method
by Andreas ÖchsnerThis book is the 3rd edition of an introduction to modern computational mechanics based on the finite element method. This third edition is largely extended, adding many new examples to let the reader understand the principles better by performing calculations by hand, as well as numerical example to practice the finite element approach to engineering problems. The new edition comes together with a set of digital flash cards with questions and answers that improve learning success. Featuring over 100 more pages, the new edition will help students succeed in mechanics courses by showing them how to apply the fundamental knowledge they gained in the first years of their engineering education to more advanced topics. In order to deepen readers’ understanding of the equations and theories discussed, each chapter also includes supplementary problems. These problems start with fundamental knowledge questions on the theory presented in the respective chapter, followed by calculation problems. In total, over 80 such calculation problems are provided, along with brief solutions for each. Test your knowledge with questions and answers about the book in the Springer Nature Flashcards app.
Computational Statics Revision Course
by Andreas Öchsner Zia JavanbakhtThis revision and work book offers a very specific concept for learning the finite element method applying it to problems from statics of: It skips all the classical derivations and focusses only the essential final results. Based on these `essentials', fully solved example problems are presented. To facilitate the initial learning process, the authors compiled 10 recommended steps for a linear finite element solution procedure (`hand calculation') and all the solved examples follow this simple scheme. These 10 recommended steps help engineering students to master the finite element method and guide through fundamental standard problems, although there are neither 10 recommended steps for real-life engineering pro blems nor 10 standard problems that cover all possible problems that a young engineer may face during his first years of professional work. This revision course accompanies the textbook "Computational Statics and Dyn amics: An Introduction Based on the Finite Element Method" by the same authors.
Computational Stem Cell Biology: Methods and Protocols (Methods in Molecular Biology #1975)
by Patrick CahanThis volume details methods and protocols to further the study of stem cells within the computational stem cell biology (CSCB) field. Chapters are divided into four sections covering the theory and practice of modeling of stem cell behavior, analyzing single cell genome-scale measurements, reconstructing gene regulatory networks, and metabolomics. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls.Authoritative and cutting-edge, Computational Stem Cell Biology: Methods and Protocols will be an invaluable guide to researchers as they explore stem cells from the perspective of computational biology.
Computational Stochastic Programming: Models, Algorithms, and Implementation (Springer Optimization and Its Applications #774)
by Lewis NtaimoThis book provides a foundation in stochastic, linear, and mixed-integer programming algorithms with a focus on practical computer algorithm implementation. The purpose of this book is to provide a foundational and thorough treatment of the subject with a focus on models and algorithms and their computer implementation. The book’s most important features include a focus on both risk-neutral and risk-averse models, a variety of real-life example applications of stochastic programming, decomposition algorithms, detailed illustrative numerical examples of the models and algorithms, and an emphasis on computational experimentation. With a focus on both theory and implementation of the models and algorithms for solving practical optimization problems, this monograph is suitable for readers with fundamental knowledge of linear programming, elementary analysis, probability and statistics, and some computer programming background. Several examples of stochastic programming applications areincluded, providing numerical examples to illustrate the models and algorithms for both stochastic linear and mixed-integer programming, and showing the reader how to implement the models and algorithms using computer software.
Computational Strategies for Spectroscopy
by Vincenzo BaroneComputational spectroscopy is a rapidly evolving field that is becoming a versatile and widespread tool for the assignment of experimental spectra and their interpretation as related to chemical physical effects. This book is devoted to the most significant methodological contributions in the field, and to the computation of IR, UV-VIS, NMR and EPR spectral parameters with reference to the underlying vibronic and environmental effects. Each section starts with a chapter written by an experimental spectroscopist dealing with present challenges in the different fields; comprehensive coverage of conventional and advanced spectroscopic techniques is provided by means of dedicated chapters written by experts. Computational chemists, analytical chemists and spectroscopists, physicists, materials scientists, and graduate students will benefit from this thorough resource.
Computational Strategies Towards Improved Protein Function Prophecy of Xylanases from Thermomyces lanuginosus (SpringerBriefs in Systems Biology #4)
by Pratyoosh Shukla Mvk KarthikThis Brief reports on the interplay of an amino-acid mutation towards substrate which could lead to enhanced effects on mutant. These effects need to be given consideration in the engineering processes of protein stability and further exploration of such learning are required to provide novel indication for selection of an enzymes. There are very few reports showing such stable, energy efficient model towards improved protein function prediction screening in-silico structure based mutagenesis of xylanases from Thermomyces lanuginosus
Computational Studies: From Molecules to Materials (Emerging Materials and Technologies)
by Ambrish Kumar SrivastavaThe book covers a diverse range of topics based on computational studies, including modeling and simulations based on quantum chemical studies and molecular dynamics (MD) simulations. It contains quantum chemical studies on several molecules, including biologically relevant molecules and liquid crystals and various aspects of superatomic clusters including superalkalis and superhalogens. It gives an overview of MD simulations and their applications on biomolecular systems such as HIV-1 protease and integrase.Features: Includes first principle methods, density functional theory, as well as molecular dynamics simulations. Explores quantum chemical studies on several molecules. Gives readers an overview of the power of computation. Discusses superatomic clusters, superalkalis, and superhalogens. Covers themes from molecules, clusters, materials, as well as biophysical systems. This book is aimed at researchers and graduate students in materials science and computational and theoretical chemistry.
Computational Studies in Organometallic Chemistry (Structure and Bonding #167)
by Stuart A. Macgregor Odile EisensteinThe series Structure and Bonding publishes critical Reviews on Topics of Research concerned with chemical structure and bonding. The scope of the series spans the entire Periodic Table and addresses structure and bonding issues associated with all of the elements. It also focuses attention on new and developing areas of modern structural and theoretical chemistry such as nanostructures, molecular electronics, designed molecular solids, surfaces, metal clusters and supramolecular structures. Physical and spectroscopic techniques used to determine, examine and model structures fall within the purview of Structure and Bonding to the extent that the focus is on the scientific results obtained and not on specialist information concerning the techniques themselves. Issues associated with the development of bonding models and generalizations that illuminate the reactivity pathways and rates of chemical processes are also relevant. The individual volumes in the series are thematic. The goal of each volume is to give the reader, whether at a university or in industry, a comprehensive overview of an area where new insights are emerging that are of interest to a larger scientific audience. Thus each review within the volume critically surveys one aspect of that topic and places it within the context of the volume as a whole. The most significant developments of the last 5 to 10 years should be presented using selected examples to illustrate the principles discussed. A description of the physical basis of the experimental techniques that have been used to provide the primary data may also be appropriate, if it has not been covered in detail elsewhere. The coverage need not be exhaustive in data, but should rather be conceptual, concentrating on the new principles being developed that will allow the reader, who is not a specialist in the area covered, to understand the data presented. Discussion of possible future research directions in the area is welcomed.
Computational Studies of Transition Metal Nanoalloys (Springer Theses)
by Lauro Oliver BorbónThe focus of this thesis is the computational modelling of transition metal bimetallic (nanoalloy) clusters. More specifically, the study of Pd-Pt, Ag-Pt, Au-Au and Pd-Au as a few tens of atoms in the gas phase. The author used a combination of global optimization techniques - coupled with a Gupta-type empirical many-body potential - and Density Functional Theory (DFT) calculations to study the structures, bonding and chemical ordering, as well as investigate the chemisorptions of hydrogen and carbon monoxide on bimetallic clusters. This research is highly relevant to experimental catalytic studies and has resulted in more than seven publications in international journals.
Computational Systems Biology: Methods And Protocols (Methods In Molecular Biology #1754)
by Tao HuangThis volume introduces the reader to the latest experimental and bioinformatics methods for DNA sequencing, RNA sequencing, cell-free tumour DNA sequencing, single cell sequencing, single-cell proteomics and metabolomics. Chapters detail advanced analysis methods, such as Genome-Wide Association Studies (GWAS), machine learning, reconstruction and analysis of gene regulatory networks and differential coexpression network analysis, and gave a practical guide for how to choose and use the right algorithm or software to handle specific high throughput data or multi-omics data. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls.Authoritative and cutting-edge, Computational Systems Biology: Methods and Protocols aims to ensure successful results in the further study of this vital field.
Computational Systems Biology (Methods in Molecular Biology #541)
by Kristina Montgomery Roger Bumgarner Ram Samudrala Reneé Ireton Jason McdermottThe recent confluence of high throughput methodology for biological data gathering, genome-scale sequencing, and computational processing power has driven a reinvention and expansion of the way we identify, infer, model, and store relationships between molecules, pathways, and cells in living organisms. In Computational Systems Biology, expert investigators contribute chapters which bring together biological data and computational and/or mathematical models of the data to aid researchers striving to create a system that provides both predictive and mechanistic information for a model organism. The volume is organized into five major sections involving network components, network inference, network dynamics, function and evolutionary system biology, and computational infrastructure for systems biology. As a volume of the highly successful Methods in Molecular BiologyTM series, this work provides the kind of detailed description and implementation advice that is crucial for getting optimal results. Comprehensive and up-to-date, Computational Systems Biology serves to motivate and inspire all those who wish to develop a complete description of a biological system.
Computational Systems Biology in Medicine and Biotechnology: Methods and Protocols (Methods in Molecular Biology #2399)
by Miguel A. Aon Sonia CortassaThis volume addresses the latest state-of-the-art systems biology-oriented approaches that--driven by big data and bioinformatics--are utilized by Computational Systems Biology, an interdisciplinary field that bridges experimental tools with computational tools to tackle complex questions at the frontiers of knowledge in medicine and biotechnology. The chapters in this book are organized into six parts: systems biology of the genome, epigenome, and redox proteome; metabolic networks; aging and longevity; systems biology of diseases; spatiotemporal patterns of rhythms, morphogenesis, and complex dynamics; and genome scale metabolic modeling in biotechnology. In every chapter, readers will find varied methodological approaches applied at different levels, from molecular, cellular, organ to organisms, genome to phenome, and health and disease. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics; criteria utilized for applying specific methodologies; lists of the necessary materials, reagents, software, databases, algorithms, mathematical models, and dedicated analytical procedures; step-by-step, readily reproducible laboratory, bioinformatics, and computational protocols all delivered in didactic and clear style and abundantly illustrated with express case studies and tutorials; and tips on troubleshooting and advice for achieving reproducibility while avoiding mistakes and misinterpretations. The overarching goal driving this volume is to excite the expert and stimulate the newcomer to the field of Computational Systems Biology.Cutting-edge and authoritative, Computational Systems Biology in Medicine and Biotechnology: Methods and Protocols is a valuable resource for pre- and post-graduate students in medicine and biotechnology, and in diverse areas ranging from microbiology to cellular and organismal biology, as well as computational and experimental biologists, and researchers interested in utilizing comprehensive systems biology oriented methods.
Computational Systems Neurobiology
by N. Le NovèreComputational neurosciences and systems biology are among the main domains of life science research where mathematical modeling made a difference. This book introduces the many different types of computational studies one can develop to study neuronal systems. It is aimed at undergraduate students starting their research in computational neurobiology or more senior researchers who would like, or need, to move towards computational approaches. Based on their specific project, the readers would then move to one of the more specialized excellent textbooks available in the field. The first part of the book deals with molecular systems biology. Functional genomics is introduced through examples of transcriptomics and proteomics studies of neurobiological interest. Quantitative modelling of biochemical systems is presented in homogeneous compartments and using spatial descriptions. A second part deals with the various approaches to model single neuron physiology, and naturally moves to neuronal networks. A division is focused on the development of neurons and neuronal systems and the book closes on a series of methodological chapters. From the molecules to the organ, thinking at the level of systems is transforming biology and its impact on society. This book will help the reader to hop on the train directly in the tank engine.
Computational Techniques for Human Smile Analysis (SpringerBriefs in Computer Science)
by Hassan Ugail Ahmad Ali AldahoudIn this book, the authors discuss the recent developments in computational techniques for automated non-invasive facial emotion detection and analysis with particular focus on the smile. By way of applications, they discuss how genuine and non-genuine smiles can be inferred, how gender is encoded in a smile and how it is possible to use the dynamics of a smile itself as a biometric feature. It is often said that the face is a window to the soul. Bearing a metaphor of this nature in mind, one might find it intriguing to understand, if any, how the physical, behavioural as well as emotional characteristics of a person could be decoded from the face itself. With the increasing deductive power of machine learning techniques, it is becoming plausible to address such questions through the development of appropriate computational frameworks. Though there are as many as over twenty five categories of emotions one could express, regardless of the ethnicity, gender or social class, across humanity, there exist six common emotions – namely happiness, sadness, surprise, fear, anger and disgust - all of which can be inferred from facial expressions. Of these facial expressions, the smile is the most prominent in social interactions. The smile bears important ramifications with beliefs such as it makes one more attractive, less stressful in upsetting situations and employers tending to promote people who smile often. Even pockets of scientific research appear to be forthcoming to validate such beliefs and claims, e.g. the smile intensity observed in photographs positively correlates with longevity, the ability to win a fight and whether a couple would stay married. Thus, it appears that many important personality traits are encoded in the smile itself. Therefore, the deployment of computer based algorithms for studying the human smiles in greater detail is a plausible avenue for which the authors have dedicated the discussions in this book.
Computational Techniques for Process Simulation and Analysis Using MATLAB®
by Niket S. KaisareMATLAB® has become one of the prominent languages used in research and industry and often described as "the language of technical computing". The focus of this book will be to highlight the use of MATLAB® in technical computing; or more specifically, in solving problems in Process Simulations. This book aims to bring a practical approach to expounding theories: both numerical aspects of stability and convergence, as well as linear and nonlinear analysis of systems. The book is divided into three parts which are laid out with a "Process Analysis" viewpoint. First part covers system dynamics followed by solution of linear and nonlinear equations, including Differential Algebraic Equations (DAE) while the last part covers function approximation and optimization. Intended to be an advanced level textbook for numerical methods, simulation and analysis of process systems and computational programming lab, it covers following key points • Comprehensive coverage of numerical analyses based on MATLAB for chemical process examples. • Includes analysis of transient behavior of chemical processes. • Discusses coding hygiene, process animation and GUI exclusively. • Treatment of process dynamics, linear stability, nonlinear analysis and function approximation through contemporary examples. • Focus on simulation using MATLAB to solve ODEs and PDEs that are frequently encountered in process systems.
Computational Techniques in Neuroscience (Computational Methods for Industrial Applications)
by Kamal Malik Harsh Sadawarti Moolchand Sharma Umesh Gupta Prayag TiwariThe text discusses the techniques of deep learning and machine learning in the field of neuroscience, engineering approaches to study the brain structure and dynamics, convolutional networks for fast, energy-efficient neuromorphic computing, and reinforcement learning in feedback control. It showcases case studies in neural data analysis. Features: Focuses on neuron modeling, development, and direction of neural circuits to explain perception, behavior, and biologically inspired intelligent agents for decision making Showcases important aspects such as human behavior prediction using smart technologies and understanding the modeling of nervous systems Discusses nature-inspired algorithms such as swarm intelligence, ant colony optimization, and multi-agent systems Presents information-theoretic, control-theoretic, and decision-theoretic approaches in neuroscience. Includes case studies in functional magnetic resonance imaging (fMRI) and neural data analysis This reference text addresses different applications of computational neuro-sciences using artificial intelligence, deep learning, and other machine learning techniques to fine-tune the models, thereby solving the real-life problems prominently. It will further discuss important topics such as neural rehabili-tation, brain-computer interfacing, neural control, neural system analysis, and neurobiologically inspired self-monitoring systems. It will serve as an ideal reference text for graduate students and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, information technology, and biomedical engineering.
Computational Technologies in Materials Science (Science, Technology, and Management)
by Shubham Tayal Parveen Singla Ashutosh Nandi J. Paulo DavimAdvanced materials are essential for economic security and human well-being, with applications in industries aimed at addressing challenges in clean energy, national security, and human welfare. Yet, it can take years to move a material to the market after its initial discovery. Computational techniques have accelerated the exploration and development of materials, offering the chance to move new materials to the market quickly. Computational Technologies in Materials Science addresses topics related to AI, machine learning, deep learning, and cloud computing in materials science. It explores characterization and fabrication of materials, machine-learning-based models, and computational intelligence for the synthesis and identification of materials. This book • Covers material testing and development using computational intelligence • Highlights the technologies to integrate computational intelligence and materials science • Details case studies and detailed applications • Investigates challenges in developing and using computational intelligence in materials science • Analyzes historic changes that are taking place in designing materials. This book encourages material researchers and academics to develop novel theories and sustainable computational techniques and explores the potential for computational intelligence to replace traditional materials research.
Computational Thermodynamics of Materials
by Liu Zi-Kui Yi WangThis unique and comprehensive introduction offers an unrivalled and in-depth understanding of the computational-based thermodynamic approach and how it can be used to guide the design of materials for robust performances, integrating basic fundamental concepts with experimental techniques and practical industrial applications, to provide readers with a thorough grounding in the subject. Topics covered range from the underlying thermodynamic principles, to the theory and methodology of thermodynamic data collecting, analysis, modeling, and verification, with details on free energy, phase equilibrium, phase diagrams, chemical reactions, and electrochemistry. In thermodynamic modelling, the authors focus on the CALPHAD method and first-principles calculations. They also provide guidance for use of YPHON, a mixed-space phonon code developed by the authors for polar materials based on the supercell approach. Including worked examples, case studies, and end-of-chapter problems, this is an essential resource for students, researchers, and practitioners in materials science.
Computational Thinking and Coding for Every Student: The Teacher’s Getting-Started Guide
by Jane Krauss Kiki ProttsmanEmpower tomorrow’s tech innovators Our students are avid users and consumers of technology. Isn’t it time that they see themselves as the next technological innovators, too? Computational Thinking and Coding for Every Student is the beginner’s guide for K-12 educators who want to learn to integrate the basics of computer science into their curriculum. Readers will find Practical strategies for teaching computational thinking and the beginning steps to introduce coding at any grade level, across disciplines, and during out-of-school time Instruction-ready lessons and activities for every grade Specific guidance for designing a learning pathway for elementary, middle, or high school students Justification for making coding and computer science accessible to all A glossary with definitions of key computer science terms, a discussion guide with tips for making the most of the book, and companion website with videos, activities, and other resources Momentum for computer science education is growing as educators and parents realize how fundamental computing has become for the jobs of the future. This book is for educators who see all of their students as creative thinkers and active contributors to tomorrow’s innovations. "Kiki Prottsman and Jane Krauss have been at the forefront of the rising popularity of computer science and are experts in the issues that the field faces, such as equity and diversity. In this book, they’ve condensed years of research and practitioner experience into an easy to read narrative about what computer science is, why it is important, and how to teach it to a variety of audiences. Their ideas aren’t just good, they are research-based and have been in practice in thousands of classrooms…So to the hundreds and thousands of teachers who are considering, learning, or actively teaching computer science—this book is well worth your time." Pat Yongpradit Chief Academic Officer, Code.org
Computational Thinking and Coding for Every Student: The Teacher’s Getting-Started Guide
by Jane Krauss Kiki ProttsmanEmpower tomorrow’s tech innovators Our students are avid users and consumers of technology. Isn’t it time that they see themselves as the next technological innovators, too? Computational Thinking and Coding for Every Student is the beginner’s guide for K-12 educators who want to learn to integrate the basics of computer science into their curriculum. Readers will find Practical strategies for teaching computational thinking and the beginning steps to introduce coding at any grade level, across disciplines, and during out-of-school time Instruction-ready lessons and activities for every grade Specific guidance for designing a learning pathway for elementary, middle, or high school students Justification for making coding and computer science accessible to all A glossary with definitions of key computer science terms, a discussion guide with tips for making the most of the book, and companion website with videos, activities, and other resources Momentum for computer science education is growing as educators and parents realize how fundamental computing has become for the jobs of the future. This book is for educators who see all of their students as creative thinkers and active contributors to tomorrow’s innovations. "Kiki Prottsman and Jane Krauss have been at the forefront of the rising popularity of computer science and are experts in the issues that the field faces, such as equity and diversity. In this book, they’ve condensed years of research and practitioner experience into an easy to read narrative about what computer science is, why it is important, and how to teach it to a variety of audiences. Their ideas aren’t just good, they are research-based and have been in practice in thousands of classrooms…So to the hundreds and thousands of teachers who are considering, learning, or actively teaching computer science—this book is well worth your time." Pat Yongpradit Chief Academic Officer, Code.org
Computational Toxicology: Risk Assessment for Chemicals
by Sean EkinsA key resource for toxicologists across a broad spectrum of fields, this book offers a comprehensive analysis of molecular modelling approaches and strategies applied to risk assessment for pharmaceutical and environmental chemicals.• Provides a perspective of what is currently achievable with computational toxicology and a view to future developments• Helps readers overcome questions of data sources, curation, treatment, and how to model / interpret critical endpoints that support 21st century hazard assessment• Assembles cutting-edge concepts and leading authors into a unique and powerful single-source reference• Includes in-depth looks at QSAR models, physicochemical drug properties, structure-based drug targeting, chemical mixture assessments, and environmental modeling• Features coverage about consumer product safety assessment and chemical defense along with chapters on open source toxicology and big data
Computational Toxicology: Methods and Protocols (Methods in Molecular Biology #2834)
by Orazio NicolottiThis second eidtion explores new and updated techniques used to understand solid target-specific models in computational toxicology. Chapters are divided into four sections, detailing molecular descriptors, QSAR and read-across, molecular and data modeling techniques, computational toxicology in drug discovery, molecular fingerprints, AI techniques, and safe drug design. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and key tips on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, Computational Toxicology: Methods and Protocols, Second Editon aims to ensure successful results in the further study of this vital field.
Computational Toxicology, Volume I: Volume I (Methods in Molecular Biology #929)
by Arthur N. Mayeno Brad ReisfeldRapid advances in computer science, biology, chemistry, and other disciplines are enabling powerful new computational tools and models for toxicology and pharmacology. These computational tools hold tremendous promise for advancing science, from streamlining drug efficacy and safety testing, to increasing the efficiency and effectiveness of risk assessment for environmental chemicals. Computational Toxicology provides biomedical and quantitative scientists with essential background, context, examples, useful tips, and an overview of current developments in the field. Divided into four sections, Volume I covers a wide array of methodologies and topics. Opening with an introduction to the field of computational toxicology and its current and potential applications, the volume continues with 'best practices' in mathematical and computational modeling, followed by chemoinformatics and the use of computational techniques and databases to predict chemical properties and toxicity, as well as an overview of molecular dynamics. The final section is a compilation of the key elements and main approaches used in pharmacokinetic and pharmacodynamic modeling, including the modeling of absorption, compartment and non-compartmental modeling, physiologically based pharmacokinetic modeling, interspecies extrapolation, and population effects. Written in the successful Methods in Molecular BiologyTM series format where possible, chapters include introductions to their respective topics, lists of the materials and software tools used, methods, and notes on troubleshooting.<P><P> Authoritative and easily accessible, Computational Toxicology will allow motivated readers to participate in this exciting field and undertake a diversity of realistic problems of interest.