Computational Methods for Estimating the Kinetic Parameters of Biological Systems PDF Download

Author: Quentin Vanhaelen
Publisher: Humana
ISBN: 9781071617694
Category : Science
Languages : en
Pages : 0

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Book Description
This detailed book provides an overview of various classes of computational techniques, including machine learning techniques, commonly used for evaluating kinetic parameters of biological systems. Focusing on three distinct situations, the volume covers the prediction of the kinetics of enzymatic reactions, the prediction of the kinetics of protein-protein or protein-ligand interactions (binding rates, dissociation rates, binding affinities), and the prediction of relatively large set of kinetic rates of reactions usually found in quantitative models of large biological networks. Written for the highly successful Methods in Molecular Biology series, chapters include the kind of expert implementation advice that leads to successful results. Authoritative and practical, Computational Methods for Estimating the Kinetic Parameters of Biological Systems will be of great interest for researchers working through the challenge of identifying the best type of algorithm and who would like to use or develop a computational method for the estimation of kinetic parameters.

Author: Ralf Blossey
Publisher: CRC Press
ISBN: 1420010786
Category : Computers
Languages : en
Pages : 276

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Book Description
Quantitative methods have a particular knack for improving any field they touch. For biology, computational techniques have led to enormous strides in our understanding of biological systems, but there is still vast territory to cover. Statistical physics especially holds great potential for elucidating the structural-functional relationships in bi

Author: Monika Heiner
Publisher: Springer
ISBN: 3540885625
Category : Science
Languages : en
Pages : 413

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Book Description
This book constitutes the refereed proceedings of the 6th International Conference on Computational Methods in Systems Biology, CMSB 2008, held in Rostock, Germany, in September 2008. The 21 revised full papers presented together with the summaries of 5 invited papers were carefully reviewed and selected from more than 60 submissions. The papers cover theoretical or applied contributions that are motivated by a biological question focusing on modeling approaches, including process algebra, simulation approaches, analysis methods, in particular model checking and flux analysis, and case studies.

Author: Marco Pellegrini
Publisher: Frontiers Media SA
ISBN: 288963650X
Category :
Languages : en
Pages : 270

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Book Description
Network science has accelerated a deep and successful trend in research that influences a range of disciplines like mathematics, graph theory, physics, statistics, data science and computer science (just to name a few) and adapts the relevant techniques and insights to address relevant but disparate social, biological, technological questions. We are now in an era of 'big biological data' supported by cost-effective high-throughput genomic, transcriptomic, proteomic, metabolomic data collection techniques that allow one to take snapshots of the cells' molecular profiles in a systematic fashion. Moreover recently, also phenotypic data, data on diseases, symptoms, patients, etc. are being collected at nation-wide level thus giving us another source of highly related (causal) 'big data'. This wealth of data is usually modeled as networks (aka binary relations, graphs or webs) of interactions, (including protein-protein, metabolic, signaling and transcription-regulatory interactions). The network model is a key view point leading to the uncovering of mesoscale phenomena, thus providing an essential bridge between the observable phenotypes and 'omics' underlying mechanisms. Moreover, network analysis is a powerful 'hypothesis generation' tool guiding the scientific cycle of 'data gathering', 'data interpretation, 'hypothesis generation' and 'hypothesis testing'. A major challenge in contemporary research is the synthesis of deep insights coming from network science with the wealth of data (often noisy, contradictory, incomplete and difficult to replicate) so to answer meaningful biological questions, in a quantifiable way using static and dynamic properties of biological networks.

Author: Ezio Bartocci
Publisher: Springer
ISBN: 3319451774
Category : Computers
Languages : en
Pages : 361

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Book Description
This 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.

Author: Rupesh Kumar Gautam
Publisher: Elsevier
ISBN: 0323993737
Category : Medical
Languages : en
Pages : 364

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Book Description
Computational Approaches in Drug Discovery, Development and Systems Pharmacology provides detailed information on the use of computers in advancing pharmacology. Drug discovery and development is an expensive and time-consuming practice, and computer-assisted drug design (CADD) approaches are increasing in popularity in the pharmaceutical industry to accelerate the process. With the help of CADD, scientists can focus on the most capable compounds so that they can minimize the synthetic and biological testing pains. This book examines success stories of CADD in drug discovery, drug development and role of CADD in system pharmacology, additionally including a focus on the role of artificial intelligence (AI) and deep machine learning in pharmacology. Computational Approaches in Drug Discovery, Development and Systems Pharmacology will be useful to researchers and academics working in the area of CADD, pharmacology and Bioinformatics. - Explains computer use in pharmacology using real-life case studies - Provides information about biological activities using computer technology, thus allowing for the possible reduction of the number of animals used for research - Describes the role of AI in pharmacology and applications of CADD in various diseases

Author: Ion Petre
Publisher: Springer Nature
ISBN: 3031150341
Category : Science
Languages : en
Pages : 324

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Book Description
This 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.

Author: Luca Bortolussi
Publisher: Springer Nature
ISBN: 3030313042
Category : Computers
Languages : en
Pages : 396

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Book Description
This book constitutes the refereed proceedings of the 17th International Conference on Computational Methods in Systems Biology, CMSB 2019, held in Trieste, Italy, in September 2019. The 14 full papers, 7 tool papers and 11 posters were carefully reviewed and selected from 53 submissions. Topics of interest 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; computational approaches for synthetic biology; and case studies in systems and synthetic biology.

Author: Ying Xu
Publisher: World Scientific
ISBN: 1908979011
Category : Science
Languages : en
Pages : 494

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Book Description
Over 500 prokaryotic genomes have been sequenced to date, and thousands more have been planned for the next few years. While these genomic sequence data provide unprecedented opportunities for biologists to study the world of prokaryotes, they also raise extremely challenging issues such as how to decode the rich information encoded in these genomes. This comprehensive volume includes a collection of cohesively written chapters on prokaryotic genomes, their organization and evolution, the information they encode, and the computational approaches needed to derive such information. A comparative view of bacterial and archaeal genomes, and how information is encoded differently in them, is also presented. Combining theoretical discussions and computational techniques, the book serves as a valuable introductory textbook for graduate-level microbial genomics and informatics courses./a

Author: Richard S. Larson
Publisher:
ISBN: 9781617799655
Category : Bioinformatics
Languages : en
Pages : 374

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Book Description
Recent advances in drug discovery have been rapid. The second edition of Bioinformatics and Drug Discovery has been completely updated to include topics that range from new technologies in target identification, genomic analysis, cheminformatics, protein analysis, and network or pathway analysis. Each chapter provides an extended introduction that describes the theory and application of the technology. In the second part of each chapter, detailed procedures related to the use of these technologies and software have been incorporated. 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. Thorough and intuitive, Bioinformatics and Drug Discovery, Second Edition seeks to aid scientists in the further study of the rapidly expanding field of drug discovery.