Author: G. M. Crippen
Publisher: John Wiley & Sons
ISBN:
Category : Conformational analysis
Languages : en
Pages : 564

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Book Description

Author: Antonio Mucherino
Publisher: Springer
ISBN: 9781489985781
Category : Mathematics
Languages : en
Pages : 0

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Book Description
This volume is a collection of research surveys on the Distance Geometry Problem (DGP) and its applications. It will be divided into three parts: Theory, Methods and Applications. Each part will contain at least one survey and several research papers. The first part, Theory, will deal with theoretical aspects of the DGP, including a new class of problems and the study of its complexities as well as the relation between DGP and other related topics, such as: distance matrix theory, Euclidean distance matrix completion problem, multispherical structure of distance matrices, distance geometry and geometric algebra, algebraic distance geometry theory, visualization of K-dimensional structures in the plane, graph rigidity, and theory of discretizable DGP: symmetry and complexity. The second part, Methods, will discuss mathematical and computational properties of methods developed to the problems considered in the first chapter including continuous methods (based on Gaussian and hyperbolic smoothing, difference of convex functions, semidefinite programming, branch-and-bound), discrete methods (based on branch-and-prune, geometric build-up, graph rigidity), and also heuristics methods (based on simulated annealing, genetic algorithms, tabu search, variable neighborhood search). Applications will comprise the third part and will consider applications of DGP to NMR structure calculation, rational drug design, molecular dynamics simulations, graph drawing and sensor network localization. This volume will be the first edited book on distance geometry and applications. The editors are in correspondence with the major contributors to the field of distance geometry, including important research centers in molecular biology such as Institut Pasteur in Paris.

Author: G. M. Crippen
Publisher: John Wiley & Sons
ISBN:
Category : Conformational analysis
Languages : en
Pages : 562

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Book Description

Author: Kenny B. Lipkowitz
Publisher: John Wiley & Sons
ISBN: 0470126094
Category : Science
Languages : en
Pages : 482

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Book Description
Führende Experten auf dem Gebiet der Computer-Chemie präsentieren in dem fünften Band der erfolgreichen Reihe 'Reviews in Computational Chemistry' die neuesten Entwicklungen. Um den interessierten Chemiker auf dem aktuellen Stand zu halten, ist der Reihe im Anhang eine Liste mit der Software zum Thema beigefügt

Author: Leo Liberti
Publisher: Springer
ISBN: 3319607928
Category : Mathematics
Languages : en
Pages : 141

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Book Description
This textbook, the first of its kind, presents the fundamentals of distance geometry: theory, useful methodologies for obtaining solutions, and real world applications. Concise proofs are given and step-by-step algorithms for solving fundamental problems efficiently and precisely are presented in Mathematica®, enabling the reader to experiment with concepts and methods as they are introduced. Descriptive graphics, examples, and problems, accompany the real gems of the text, namely the applications in visualization of graphs, localization of sensor networks, protein conformation from distance data, clock synchronization protocols, robotics, and control of unmanned underwater vehicles, to name several. Aimed at intermediate undergraduates, beginning graduate students, researchers, and practitioners, the reader with a basic knowledge of linear algebra will gain an understanding of the basic theories of distance geometry and why they work in real life.

Author: G. M. Crippen
Publisher:
ISBN:
Category : Science
Languages : en
Pages : 566

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Book Description

Author: Carlile Lavor
Publisher: Springer
ISBN: 3319571834
Category : Computers
Languages : en
Pages : 59

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Book Description
This book is a pedagogical presentation aimed at advanced undergraduate students, beginning graduate students and professionals who are looking for an introductory text to the field of Distance Geometry, and some of its applications. This versions profits from feedback acquired at undergraduate/graduate courses in seminars and a number of workshops.

Author: Antonio Mucherino
Publisher: Springer Science & Business Media
ISBN: 1461451280
Category : Mathematics
Languages : en
Pages : 436

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Book Description
This volume is a collection of research surveys on the Distance Geometry Problem (DGP) and its applications. It will be divided into three parts: Theory, Methods and Applications. Each part will contain at least one survey and several research papers. The first part, Theory, will deal with theoretical aspects of the DGP, including a new class of problems and the study of its complexities as well as the relation between DGP and other related topics, such as: distance matrix theory, Euclidean distance matrix completion problem, multispherical structure of distance matrices, distance geometry and geometric algebra, algebraic distance geometry theory, visualization of K-dimensional structures in the plane, graph rigidity, and theory of discretizable DGP: symmetry and complexity. The second part, Methods, will discuss mathematical and computational properties of methods developed to the problems considered in the first chapter including continuous methods (based on Gaussian and hyperbolic smoothing, difference of convex functions, semidefinite programming, branch-and-bound), discrete methods (based on branch-and-prune, geometric build-up, graph rigidity), and also heuristics methods (based on simulated annealing, genetic algorithms, tabu search, variable neighborhood search). Applications will comprise the third part and will consider applications of DGP to NMR structure calculation, rational drug design, molecular dynamics simulations, graph drawing and sensor network localization. This volume will be the first edited book on distance geometry and applications. The editors are in correspondence with the major contributors to the field of distance geometry, including important research centers in molecular biology such as Institut Pasteur in Paris.

Author: Carlile Lavor
Publisher: Springer
ISBN: 3319906658
Category : Mathematics
Languages : en
Pages : 135

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Book Description
This book offers a gentle introduction to key elements of Geometric Algebra, along with their applications in Physics, Robotics and Molecular Geometry. Major applications covered are the physics of space-time, including Maxwell electromagnetism and the Dirac equation; robotics, including formulations for the forward and inverse kinematics and an overview of the singularity problem for serial robots; and molecular geometry, with 3D-protein structure calculations using NMR data. The book is primarily intended for graduate students and advanced undergraduates in related fields, but can also benefit professionals in search of a pedagogical presentation of these subjects.

Author: Pavlo O. Dral
Publisher: Elsevier
ISBN: 0323886043
Category : Science
Languages : en
Pages : 702

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Book Description
Quantum chemistry is simulating atomistic systems according to the laws of quantum mechanics, and such simulations are essential for our understanding of the world and for technological progress. Machine learning revolutionizes quantum chemistry by increasing simulation speed and accuracy and obtaining new insights. However, for nonspecialists, learning about this vast field is a formidable challenge. Quantum Chemistry in the Age of Machine Learning covers this exciting field in detail, ranging from basic concepts to comprehensive methodological details to providing detailed codes and hands-on tutorials. Such an approach helps readers get a quick overview of existing techniques and provides an opportunity to learn the intricacies and inner workings of state-of-the-art methods. The book describes the underlying concepts of machine learning and quantum chemistry, machine learning potentials and learning of other quantum chemical properties, machine learning-improved quantum chemical methods, analysis of Big Data from simulations, and materials design with machine learning. Drawing on the expertise of a team of specialist contributors, this book serves as a valuable guide for both aspiring beginners and specialists in this exciting field. - Compiles advances of machine learning in quantum chemistry across different areas into a single resource - Provides insights into the underlying concepts of machine learning techniques that are relevant to quantum chemistry - Describes, in detail, the current state-of-the-art machine learning-based methods in quantum chemistry