Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides an up-to-date overview of data driven and evidence-based empirical approaches in the efficient application of chemodescriptors and biodescriptors. Currently there is a steady increase in the use of data analytics and model-based decision support systems in basic and applied research in chemoinformatics, bioinformatics, pharmaceutical drug design, predictive toxicology, and computational biology. Since there are a plethora of modeling methods and a large number of chemodescriptors and biodescriptors available today, robust statistical and machine learning methods are applied throughout. In addition, the development of statistically robust predictive models in rank deficient cases using chemodescrip tors and biodescriptors is discussed. Readers are provided with an up-to-date overview of the theoretical background, calculation methods, and proper use of chemodescriptors and biodescriptors in model building, with special emphasis on computer-assisted organic synthesis, new drug discovery, hazard assessment of chemicals, and computational biology of emerging global pathogens. The book also discusses the applications of alignment-free sequence descriptors (AFSDs) in vaccine design and the characterization of emerging global pathogens such as the Zika virus and SARS-CoV-2. The utility of molecular fragment-based descriptors in building useful quantitative structure-activity relationship (Q)SAR) models is detailed as is the use of mathematical structural descriptors in chemical synthesis planning.
Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides an up-to-date overview of data driven and evidence-based empirical approaches in the efficient application of chemodescriptors and biodescriptors. Currently there is a steady increase in the use of data analytics and model-based decision support systems in basic and applied research in chemoinformatics, bioinformatics, pharmaceutical drug design, predictive toxicology, and computational biology. Since there are a plethora of modeling methods and a large number of chemodescriptors and biodescriptors available today, robust statistical and machine learning methods are applied throughout. In addition, the development of statistically robust predictive models in rank deficient cases using chemodescrip tors and biodescriptors is discussed. Readers are provided with an up-to-date overview of the theoretical background, calculation methods, and proper use of chemodescriptors and biodescriptors in model building, with special emphasis on computer-assisted organic synthesis, new drug discovery, hazard assessment of chemicals, and computational biology of emerging global pathogens. The book also discusses the applications of alignment-free sequence descriptors (AFSDs) in vaccine design and the characterization of emerging global pathogens such as the Zika virus and SARS-CoV-2. The utility of molecular fragment-based descriptors in building useful quantitative structure-activity relationship (Q)SAR) models is detailed as is the use of mathematical structural descriptors in chemical synthesis planning.
Taschenbuch. Zustand: Neu. Mathematical Descriptors of Molecules and Biomolecules | Applications in Chemistry, Drug Design, Chemical Toxicology, and Computational Biology | Subhash C. Basak | Taschenbuch | Synthesis Lectures on Mathematics & Statistics | ix | Englisch | 2025 | Springer | EAN 9783031678431 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
EUR 124,77
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In den WarenkorbZustand: New. In.
Sprache: Englisch
Verlag: Bentham Science Publishers, 2016
ISBN 10: 1681081989 ISBN 13: 9781681081984
Anbieter: Majestic Books, Hounslow, Vereinigtes Königreich
EUR 138,96
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In den WarenkorbZustand: New. pp. 370.
Sprache: Englisch
Verlag: Bentham Science Publishers, 2016
ISBN 10: 1681080532 ISBN 13: 9781681080536
Anbieter: Majestic Books, Hounslow, Vereinigtes Königreich
EUR 140,01
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In den WarenkorbZustand: New. pp. 344.
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
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In den WarenkorbPaperback. Zustand: Brand New. 354 pages. 9.00x7.50x0.75 inches. In Stock.
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In den WarenkorbPaperback. Zustand: Brand New. 376 pages. 9.00x7.50x0.75 inches. In Stock.
Anbieter: Majestic Books, Hounslow, Vereinigtes Königreich
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In den WarenkorbZustand: New. pp. 344.
Anbieter: preigu, Osnabrück, Deutschland
Taschenbuch. Zustand: Neu. Advances in Mathematical Chemistry and Applications: Volume 2 | Subhash C Basak (u. a.) | Taschenbuch | Englisch | 2016 | Elsevier Science | EAN 9781681080536 | Verantwortliche Person für die EU: Zeitfracht Medien GmbH, Ferdinand-Jühlke-Str. 7, 99095 Erfurt, produktsicherheit[at]zeitfracht[dot]de | Anbieter: preigu.
Anbieter: preigu, Osnabrück, Deutschland
Taschenbuch. Zustand: Neu. Advances in Mathematical Chemistry and Applications: Volume 1 | Subhash C Basak (u. a.) | Taschenbuch | Englisch | 2016 | Elsevier Science | EAN 9781681081984 | Verantwortliche Person für die EU: Zeitfracht Medien GmbH, Ferdinand-Jühlke-Str. 7, 99095 Erfurt, produktsicherheit[at]zeitfracht[dot]de | Anbieter: preigu.
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
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In den WarenkorbHardcover. Zustand: Brand New. 1st edition. 344 pages. 9.13x6.48x0.96 inches. In Stock.
Anbieter: Majestic Books, Hounslow, Vereinigtes Königreich
EUR 202,73
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In den WarenkorbZustand: New.
Sprache: Englisch
Verlag: NOVA SCIENCE PUBLISHERS INC, 2019
ISBN 10: 1536149705 ISBN 13: 9781536149708
Anbieter: BOOKIT!, Genève, Schweiz
Zustand: Used: Like New. LIVRE A L?ETAT DE NEUF. EXPEDIE SOUS 3 JOURS OUVRES. NUMERO DE SUIVI COMMUNIQUE AVANT ENVOI, EMBALLAGE RENFORCE. EAN:9781536149708.
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch. Zustand: Neu. Neuware - Explore the multidisciplinary nature of complex networks through machine learning techniquesStatistical and Machine Learning Approaches for Network Analysis provides an accessible framework for structurally analyzing graphs by bringing together known and novel approaches on graph classes and graph measures for classification. By providing different approaches based on experimental data, the book uniquely sets itself apart from the current literature by exploring the application of machine learning techniques to various types of complex networks.Comprised of chapters written by internationally renowned researchers in the field of interdisciplinary network theory, the book presents current and classical methods to analyze networks statistically. Methods from machine learning, data mining, and information theory are strongly emphasized throughout. Real data sets are used to showcase the discussed methods and topics, which include:\* A survey of computational approaches to reconstruct and partition biological networks\* An introduction to complex networks--measures, statistical properties, and models\* Modeling for evolving biological networks\* The structure of an evolving random bipartite graph\* Density-based enumeration in structured data\* Hyponym extraction employing a weighted graph kernelStatistical and Machine Learning Approaches for Network Analysis is an excellent supplemental text for graduate-level, cross-disciplinary courses in applied discrete mathematics, bioinformatics, pattern recognition, and computer science. The book is also a valuable reference for researchers and practitioners in the fields of applied discrete mathematics, machine learning, data mining, and biostatistics.
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
EUR 249,32
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In den WarenkorbZustand: New. In.
Anbieter: moluna, Greven, Deutschland
EUR 254,79
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In den WarenkorbZustand: New. Brings together the current knowledge on the most important aspects of big data, including analysis using deep learning and fuzzy logic, transparency and data protection, disparate data analytics, and scalability of the big data domain Cov.