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Computational Methods in Power System Analysis (Atlantis Studies in Scientific Computing in Electromagnetics #1)
by Reijer Idema Domenico J.P. LahayeThis book treats state-of-the-art computational methods for power flow studies and contingency analysis. In the first part the authors present the relevant computational methods and mathematical concepts. In the second part, power flow and contingency analysis are treated. Furthermore, traditional methods to solve such problems are compared to modern solvers, developed using the knowledge of the first part of the book. Finally, these solvers are analyzed both theoretically and experimentally, clearly showing the benefits of the modern approach.
Computational Methods in Protein Evolution (Methods in Molecular Biology #1851)
by Tobias SikosekThis volume presents a diverse collection of methodologies used to study various problems at the protein sequence and structure level. The chapters in this book look at issues ranging from broad concepts like protein space to specifics like antibody modeling. Topics include point mutations, gene duplication, de novo emergence of new genes, pairwise correlated mutations, ancestral protein reconstruction, homology modelling, protein stability and dynamics, and protein-protein interactions. The book also covers a wide range of computational approaches, including sequence and structure alignments, phylogenies, physics-based and mathematical approaches, machine learning, and more. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and prerequisites, step-by-step, readily reproducible computational protocols (using command line or graphical user interfaces, sometimes including computer code), and tips on troubleshooting and avoiding known pitfalls.Cutting-edge and authoritative, Computational Methods in Protein Evolution is a valuable resource that offers useful workflows and techniques that will help both novice and expert researchers working with proteins computationally.
Computational Methods in Surface and Colloid Science (Surfactant Science)
by Małgorzata BorówkoThis volume presents computer simulation methods and mathematical modelling of physical processes used in surface science research. It offers in-depth analysis of advanced theoretical approaches to behaviours of fluids in contact with porous, semiporous and nonporous solid surfaces. The book also explores interfacial systems for a wide variety of p
Computational Methods in Synthetic Biology (Methods in Molecular Biology #1244)
by Mario Andrea MarchisioThis volume provides complete coverage of the computational approaches currently used in Synthetic Biology. Chapters focus on computational methods and algorithms for the design of bio-components, insight on CAD programs, analysis techniques, and distributed systems. Written in the highly successful Methods in Molecular Biology series format, the chapters include the kind of detailed description and implementation advice that is crucial for getting optimal results in the laboratory. Authoritative and practical, Computational Methods in Synthetic Biology serves as a guide to plan in silico the in vivo or in vitro construction of a variety of synthetic bio-circuits.
Computational Methods in Synthetic Biology (Methods in Molecular Biology #2189)
by Mario Andrea MarchisioThis second edition book provides complete coverage of the computational approaches currently used in Synthetic Biology. New chapters detail computational methods and algorithms for the design of bio-components, insight on CAD programs, analysis techniques, and distributed systems. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, application details for both the expert and non-expert reader, and tips on troubleshooting and avoiding known pitfalls. Authoritative and practical, Computational Methods in Synthetic Biology, Second Edition aims to feature a broad overview of the research areas that can be met in the area of in silico Synthetic Biology.
Computational Methods in Systems Biology: 13th International Conference, CMSB 2015, Nantes, France, September 16-18, 2015, Proceedings (Lecture Notes in Computer Science #9308)
by Olivier Roux Jérémie BourdonThis book constitutes the refereed proceedings of the 13th International Conference on Computational Methods in Systems Biology, CMSB 2015, held in Nantes, France, in September 2015. The 20 full papers and 2 short papers presented were carefully reviewed and selected from 43 full and 4 short paper submissions. The papers cover a wide range of topics in the analysis of biological systems, networks and data such as model checking, stochastic analysis, hybrid systems, circadian clock, time series data, logic programming, and constraints solving ranging from intercellular to multiscale.
Computational Methods in Systems Biology: 14th International Conference, CMSB 2016, Cambridge, UK, September 21-23, 2016, Proceedings (Lecture Notes in Computer Science #9859)
by Ezio Bartocci Pietro Lio Nicola PaolettiThis book constitutes the refereed proceedings of the 14th International Conference on Computational Methods in Systems Biology, CMSB 2016, held in Cambridge, UK, in September 2016. The 20 full papers, 3 tool papers and 9 posters presented were carefully reviewed and selected from 37 regular paper submissions. The topics include formalisms for modeling biological processes; models and their biological applications; frameworks for model verification, validation, analysis, and simulation of biological systems; high-performance computational systems biology and parallel implementations; model inference from experimental data; model integration from biological databases; multi-scale modeling and analysis methods; and computational approaches for synthetic biology.
Computational Methods in Systems Biology: 19th International Conference, CMSB 2021, Bordeaux, France, September 22–24, 2021, Proceedings (Lecture Notes in Computer Science #12881)
by Eugenio Cinquemani Loïc PaulevéThis book constitutes the refereed proceedings of the 19th International Conference on Computational Methods in Systems Biology, CMSB 2021, held in Bordeaux, France, September 22–24, 2021.*The 13 full papers and 5 tool papers were carefully reviewed and selected from 32 submissions. The topics of interest include biological process modelling; biological system model verification, validation, analysis, and simulation; high-performance computational systems biology; model inference from experimental data; multi-scale modeling and analysis methods; computational approaches for synthetic biology; machine learning and data-driven approaches; microbial ecology modelling and analysis; methods and protocols for populations and their variability; models, applications, and case studies in systems and synthetic biology. The chapters "Microbial Community Decision Making Models in Batch", "Population design for synthetic gene circuits", "BioFVM-X: An MPI+OpenMP 3-D Simulator for Biological Systems" are published open access under a CC BY license (Creative Commons Attribution 4.0 International License). * The conference was held in a hybrid mode due to the COVID-19 pandemic.
Computational Methods in Systems Biology: 20th International Conference, CMSB 2022, Bucharest, Romania, September 14–16, 2022, Proceedings (Lecture Notes in Computer Science #13447)
by Ion Petre Andrei PăunThis book constitutes the refereed proceedings of the 20th International Conference on Computational Methods in Systems Biology, CMSB 2022, held in Bucharest, Romania, in September 2022.The 13 full papers and 4 tool papers were carefully reviewed and selected from 43 submissions. CMSB focuses on modeling, simulation, analysis, design and control of biological systems. The papers are arranged thematically as follows: Chemical reaction networks; Boolean networks; continuous and hybrid models; machine learning; software.
Computational Methods in Systems Biology: 21st International Conference, CMSB 2023, Luxembourg City, Luxembourg, September 13–15, 2023, Proceedings (Lecture Notes in Computer Science #14137)
by Jun Pang Joachim NiehrenThis book constitutes the refereed proceedings of the 21st International Conference on Computational Methods in Systems Biology, CMSB 2023, held in Luxembourg City, Luxembourg, during September 13–15, 2023. The 14 full papers and 3 tool papers presented in this book were carefully reviewed and selected from 28 submissions. CMSB focuses on modeling, simulation, analysis, design and control of biological systems and covers the broad field of computational methods and tools in systems and synthetic biology and their applications.
Computational Methods in Systems Biology: 22nd International Conference, CMSB 2024, Pisa, Italy, September 16–18, 2024, Proceedings (Lecture Notes in Computer Science #14971)
by Paolo Milazzo Mirco Tribastone Roberta GoriThis book constitutes the refereed proceedings of the 22nd International Conference on Computational Methods in Systems Biology, CMSB 2024, which took place in Pisa, Italy, during September 16-18, 2024. The 11 full papers included in this book were carefully reviewed and selected from 23 submissions. They deal with computational methods and tools in systems and synthetic biology and their applications, focusing on topics such as modeling and simulation; high-performance methods for computational systems biology; identification of biological systems; applications of machine learning; network modeling, analysis, and inference; automated parameter and model synthesis; model integration and biological databases; multiscale modeling and analysis methods; design, analysis, and verification methods for synthetic biology; methods for biomolecular computing and engineered molecular devices; data-based approaches for systems and synthetic biology; optimality and control of biological systems; modeling, analysis, and control of microbial communities. The conference welcomes new theoretical results with potential applications to systems and synthetic biology, as well as novel applications and case studies of existing methods, tools, or frameworks.
Computational Methods in Systems Biology: 23rd International Conference, CMSB 2025, Lyon, France, September 10–12, 2025, Proceedings (Lecture Notes in Computer Science #15959)
by François Fages Sabine PérèsThis book constitutes the refereed proceedings of the 23rd International Conference on Computational Methods in Systems Biology, CMSB 2025, which took place in Lyon, France, during September 10–12, 2025. The 21 full papers presented in this volume were carefully reviewed and selected from 34 submissions sent to reviews. They are grouped into the following topics: Boolean Networks; Continuous and Hybrid models; Rule-based models; Model inference and machine learning; Population models and control.
Computational Methods to Study the Structure and Dynamics of Biomolecules and Biomolecular Processes: From Bioinformatics to Molecular Quantum Mechanics (Springer Series on Bio- and Neurosystems #8)
by Adam LiwoThis book provides a comprehensive overview of modern computer-based techniques for analyzing the structure, properties and dynamics of biomolecules and biomolecular processes. It is organized in four main parts; the first one deals with methodology of molecular simulations; the second one with applications of molecular simulations; the third one introduces bioinformatics methods and the use of experimental information in molecular simulations; the last part reports on selected applications of molecular quantum mechanics. This second edition has been thoroughly revised and updated to include the latest progresses made in the respective field of research.
Computational Modeling and Data Analysis in COVID-19 Research (Emerging Trends in Biomedical Technologies and Health informatics)
by Chhabi Rani Panigrahi, Bibudhendu Pati, Mamata Rath and Rajkumar BuyyaThis book covers recent research on the COVID-19 pandemic. It includes the analysis, implementation, usage, and proposed ideas and models with architecture to handle the COVID-19 outbreak. Using advanced technologies such as artificial intelligence (AI) and machine learning (ML), techniques for data analysis, this book will be helpful to mitigate exposure and ensure public health. We know prevention is better than cure, so by using several ML techniques, researchers can try to predict the disease in its early stage and develop more effective medications and treatments. Computational technologies in areas like AI, ML, Internet of Things (IoT), and drone technologies underlie a range of applications that can be developed and utilized for this purpose. Because in most cases there is no one solution to stop the spreading of pandemic diseases, and the integration of several tools and tactics are needed. Many successful applications of AI, ML, IoT, and drone technologies already exist, including systems that analyze past data to predict and conclude some useful information for controlling the spread of COVID-19 infections using minimum resources. The AI and ML approach can be helpful to design different models to give a predictive solution for mitigating infection and preventing larger outbreaks. This book: Examines the use of artificial intelligence (AI), machine learning (ML), Internet of Things (IoT), and drone technologies as a helpful predictive solution for controlling infection of COVID-19 Covers recent research related to the COVID-19 pandemic and includes the analysis, implementation, usage, and proposed ideas and models with architecture to handle a pandemic outbreak Examines the performance, implementation, architecture, and techniques of different analytical and statistical models related to COVID-19 Includes different case studies on COVID-19 Dr. Chhabi Rani Panigrahi is Assistant Professor in the Department of Computer Science at Rama Devi Women’s University, Bhubaneswar, India. Dr. Bibudhendu Pati is Associate Professor and Head of the Department of Computer Science at Rama Devi Women’s University, Bhubaneswar, India. Dr. Mamata Rath is Assistant Professor in the School of Management (Information Technology) at Birla Global University, Bhubaneswar, India. Prof. Rajkumar Buyya is a Redmond Barry Distinguished Professor and Director of the Cloud Computing and Distributed Systems (CLOUDS) Laboratory at the University of Melbourne, Australia.
Computational Modeling and Simulation Examples in Bioengineering (IEEE Press Series on Biomedical Engineering)
by Nenad D. FilipovicA systematic overview of the quickly developing field of bioengineering—with state-of-the-art modeling software! Computational Modeling and Simulation Examples in Bioengineering provides a comprehensive introduction to the emerging field of bioengineering. It provides the theoretical background necessary to simulating pathological conditions in the bones, muscles, cardiovascular tissue, and cancers, as well as lung and vertigo disease. The methodological approaches used for simulations include the finite element, dissipative particle dynamics, and lattice Boltzman. The text includes access to a state-of-the-art software package for simulating the theoretical problems. In this way, the book enhances the reader's learning capabilities in the field of biomedical engineering. The aim of this book is to provide concrete examples of applied modeling in biomedical engineering. Examples in a wide range of areas equip the reader with a foundation of knowledge regarding which problems can be modeled with which numerical methods. With more practical examples and more online software support than any competing text, this book organizes the field of computational bioengineering into an accessible and thorough introduction. Computational Modeling and Simulation Examples in Bioengineering: Includes a state-of-the-art software package enabling readers to engage in hands-on modeling of the examples in the book Provides a background on continuum and discrete modeling, along with equations and derivations for three key numerical methods Considers examples in the modeling of bones, skeletal muscles, cartilage, tissue engineering, blood flow, plaque, and more Explores stent deployment modeling as well as stent design and optimization techniques Generates different examples of fracture fixation with respect to the advantages in medical practice applications Computational Modeling and Simulation Examples in Bioengineering is an excellent textbook for students of bioengineering, as well as a support for basic and clinical research. Medical doctors and other clinical professionals will also benefit from this resource and guide to the latest modeling techniques.
Computational Modeling in Biomechanics
by Suvranu De Farshid Guilak Mohammad MofradAvailability of advanced computational technology has fundamentally altered the investigative paradigm in the field of biomechanics. Armed with sophisticated computational tools, researchers are seeking answers to fundamental questions by exploring complex biomechanical phenomena at the molecular, cellular, tissue and organ levels. The computational armamentarium includes such diverse tools as the ab initio quantum mechanical and molecular dynamics methods at the atomistic scales and the finite element, boundary element, meshfree as well as immersed boundary and lattice-Boltzmann methods at the continuum scales. Multiscale methods that link various scales are also being developed. While most applications require forward analysis, e.g., finding deformations and stresses as a result of loading, others involve determination of constitutive parameters based on tissue imaging and inverse analysis. This book provides a glimpse of the diverse and important roles that modern computational technology is playing in various areas of biomechanics including biofluids and mass transfer, cardiovascular mechanics, musculoskeletal mechanics, soft tissue mechanics, and biomolecular mechanics.
Computational Modeling in Tissue Engineering: A Computational Modeling Approach (Studies in Mechanobiology, Tissue Engineering and Biomaterials #10)
by Liesbet GerisOne of the major challenges in tissue engineering is the translation of biological knowledge on complex cell and tissue behavior into a predictive and robust engineering process. Mastering this complexity is an essential step towards clinical applications of tissue engineering. This volume discusses computational modeling tools that allow studying the biological complexity in a more quantitative way. More specifically, computational tools can help in: (i) quantifying and optimizing the tissue engineering product, e.g. by adapting scaffold design to optimize micro-environmental signals or by adapting selection criteria to improve homogeneity of the selected cell population; (ii) quantifying and optimizing the tissue engineering process, e.g. by adapting bioreactor design to improve quality and quantity of the final product; and (iii) assessing the influence of the in vivo environment on the behavior of the tissue engineering product, e.g. by investigating vascular ingrowth. The book presents examples of each of the above mentioned areas of computational modeling. The underlying tissue engineering applications will vary from blood vessels over trachea to cartilage and bone. For the chapters describing examples of the first two areas, the main focus is on (the optimization of) mechanical signals, mass transport and fluid flow encountered by the cells in scaffolds and bioreactors as well as on the optimization of the cell population itself. In the chapters describing modeling contributions in the third area, the focus will shift towards the biology, the complex interactions between biology and the micro-environmental signals and the ways in which modeling might be able to assist in investigating and mastering this complexity. The chapters cover issues related to (multiscale/multiphysics) model building, training and validation, but also discuss recent advances in scientific computing techniques that are needed to implement these models as well as new tools that can be used to experimentally validate the computational results.
Computational Modeling of Biological Systems: From Molecules to Pathways (Biological and Medical Physics, Biomedical Engineering)
by Nikolay V DokholyanComputational modeling is emerging as a powerful new approach to study and manipulate biological systems. Multiple methods have been developed to model, visualize, and rationally alter systems at various length scales, starting from molecular modeling and design at atomic resolution to cellular pathways modeling and analysis. Higher time and length scale processes, such as molecular evolution, have also greatly benefited from new breeds of computational approaches. This book provides an overview of the established computational methods used for modeling biologically and medically relevant systems.
Computational Modeling of Inorganic Nanomaterials (Series in Materials Science and Engineering)
by Stefan T. Bromley Martijn A. ZwijnenburgComputational Modeling of Inorganic Nanomaterials provides an accessible, unified introduction to a variety of methods for modeling inorganic materials as their dimensions approach the nanoscale. With contributions from a team of international experts, the book guides readers on choosing the most appropriate models and methods for studying the stru
Computational Modeling of Polymer Composites: A Study of Creep and Environmental Effects (Applied and Computational Mechanics)
by Samit Roy J.N. ReddyThis book provides a better understanding of the theories associated with finite element models of elastic and viscoelastic response of polymers and polymer composites. It covers computational modeling and life-prediction of polymers and polymeric composites in aggressive environments. It begins with a review of mathematical preliminaries, equations of anisotropic elasticity, and then presents finite element analysis of viscoelasticity and the diffusion process in polymers and polymeric composites. The book provides a reference for engineers and scientists and can be used as a textbook in graduate courses.
Computational Modeling of Pulverized Coal Fired Boilers
by Vivek V. Ranade Devkumar F. GuptaHarness State-of-the-Art Computational Modeling Tools Computational Modeling of Pulverized Coal Fired Boilers successfully establishes the use of computational modeling as an effective means to simulate and enhance boiler performance. This text factors in how computational flow models can provide a framework for developing a greater understanding o
Computational Modeling of Signaling Networks (Methods in Molecular Biology #2634)
by Lan K. NguyenThis volume focuses on the computational modeling of cell signaling networks and the application of these models and model-based analysis to systems and personalized medicine. Chapters guide readers through various modeling approaches for signaling networks, new methods and techniques that facilitate model development and analysis, and new applications of signaling network modeling towards systems and personalized treatment of cancer. Written in the format of the highly successful Methods in Molecular Biology series, each chapter includes an introduction to the topic, lists necessary materials and methods, includes tips on troubleshooting and known pitfalls, and step-by-step, readily reproducible protocols. Authoritative and cutting-edge, Computational Modeling of Signaling Networks aims to benefit a wide spectrum of readers including researchers from the biological as well as computational systems biology communities.
Computational Modeling of Signaling Networks (Methods in Molecular Biology #880)
by Xuedong Liu Meredith D. BettertonSignaling networks are composed of numerous signaling pathways and each has its own intricate component parts. Signaling outputs are dynamic, extraordinarily complex and yet highly specific. In, Computational Modeling of Signaling Networks: Methods and Protocols, expert researchers in the field provide key techniques to study signaling networks. Focusing on Systems of ODEs, parameterization of signaling models, signaling pathways, mass-action kinetics and ODEs, and how to use modeling to plan experiments. Written in the highly successful Methods in Molecular BiologyTM series format, the chapters include the kind of detailed description and implementation advice that is crucial for getting optimal results in the laboratory. Thorough and intuitive, Computational Modeling of Signaling Networks: Methods and Protocols aids scientists in continuing study of how signaling networks behave in space and time to generate specific biological responses and how those responses impact biology and medicine.
Computational Modeling of Tensegrity Structures: Art, Nature, Mechanical and Biological Systems
by Buntara Sthenly GanThis book provides an in-depth, numerical investigation of tensegrity systems from a structural point of view, using the laws of fundamental mechanics for general pin-jointed systems with self-stressed mechanisms. Tensegrity structures have been known for decades, mostly as an art of form for monuments in architectural design. In Computational Modeling of Tensegrity Structures, Professor Buntara examines these formations, integrating perspectives from mechanics, robotics, and biology, emphasizing investigation of tensegrity structures for both inherent behaviors and their apparent ubiquity in nature. The author offers numerous examples and illustrative applications presented in detail and with relevant MATLAB codes. Combining a chapter on the analyses of tensegrity structures along with sections on computational modeling, design, and the latest applications of tensegrity structures, the book is ideal for R&D engineers and students working in a broad range of disciplines interested in structural design.
Computational Modeling of Underground Coal Gasification
by Vivek V. Ranade Sanjay M Mahajani Ganesh Arunkumar SamdaniThe book deals with development of comprehensive computational models for simulating underground coal gasification (UCG). It starts with an introduction to the UCG process and process modelling inputs in the form of reaction kinetics, flow patterns, spalling rate, and transport coefficient that are elaborated with methods to generate the same are described with illustrations. All the known process models are reviewed, and relative merits and limitations of the modeling approaches are highlighted and compared. The book describes all the necessary steps required to determine the techno-economic feasibility of UCG process for a given coal reserve, through modeling and simulation.