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Añadir al carritoTaschenbuch. Condición: Neu. Bayesian Methods in Structural Bioinformatics | Thomas Hamelryck (u. a.) | Taschenbuch | Statistics for Biology and Health | xxii | Englisch | 2014 | Springer | EAN 9783642439889 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Idioma: Inglés
Publicado por Springer Berlin Heidelberg, 2014
ISBN 10: 3642439888 ISBN 13: 9783642439889
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Añadir al carritoTaschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book is an edited volume, the goal of which is to provide an overview of the current state-of-the-art in statistical methods applied to problems in structural bioinformatics (and in particular protein structure prediction, simulation, experimental structure determination and analysis). It focuses on statistical methods that have a clear interpretation in the framework of statistical physics, rather than ad hoc, black box methods based on neural networks or support vector machines. In addition, the emphasis is on methods that deal with biomolecular structure in atomic detail. The book is highly accessible, and only assumes background knowledge on protein structure, with a minimum of mathematical knowledge. Therefore, the book includes introductory chapters that contain a solid introduction to key topics such as Bayesian statistics and concepts in machine learning and statistical physics.
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Publicado por Springer Berlin Heidelberg Apr 2014, 2014
ISBN 10: 3642439888 ISBN 13: 9783642439889
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book is an edited volume, the goal of which is to provide an overview of the current state-of-the-art in statistical methods applied to problems in structural bioinformatics (and in particular protein structure prediction, simulation, experimental structure determination and analysis). It focuses on statistical methods that have a clear interpretation in the framework of statistical physics, rather than ad hoc, black box methods based on neural networks or support vector machines. In addition, the emphasis is on methods that deal with biomolecular structure in atomic detail. The book is highly accessible, and only assumes background knowledge on protein structure, with a minimum of mathematical knowledge. Therefore, the book includes introductory chapters that contain a solid introduction to key topics such as Bayesian statistics and concepts in machine learning and statistical physics. 408 pp. Englisch.
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Añadir al carritoCondición: New. Print on Demand pp. 408 86 Illus. (7 Col.).
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Añadir al carritoCondición: New. PRINT ON DEMAND pp. 408.
Idioma: Inglés
Publicado por Springer Berlin Heidelberg, 2014
ISBN 10: 3642439888 ISBN 13: 9783642439889
Librería: moluna, Greven, Alemania
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Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. First book on Bayesian methods in structural bioinformatics, defining an important emerging fieldHigh profile contributorsUnlike other edited volumes, the book forms a solid unity, with nearly 100 pages introductory materialProvides .
Idioma: Inglés
Publicado por Springer Berlin Heidelberg, Springer Berlin Heidelberg Apr 2014, 2014
ISBN 10: 3642439888 ISBN 13: 9783642439889
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 106,99
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book is an edited volume, the goal of which is to provide an overview of the current state-of-the-art in statistical methods applied to problems in structural bioinformatics (and in particular protein structure prediction, simulation, experimental structure determination and analysis). It focuses on statistical methods that have a clear interpretation in the framework of statistical physics, rather than ad hoc, black box methods based on neural networks or support vector machines. In addition, the emphasis is on methods that deal with biomolecular structure in atomic detail. The book is highly accessible, and only assumes background knowledge on protein structure, with a minimum of mathematical knowledge. Therefore, the book includes introductory chapters that contain a solid introduction to key topics such as Bayesian statistics and concepts in machine learning and statistical physics.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 408 pp. Englisch.