Protein Structure by Distance Analysis PDF Download

Author: Henrik Bohr
Publisher: IOS Press
ISBN: 9784274022630
Category : Distance geometry
Languages : en
Pages : 364

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Author: Dimitri P. Bertsekas
Publisher: Academic Press
ISBN: 148326047X
Category : Mathematics
Languages : en
Pages : 412

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Book Description
Computer Science and Applied Mathematics: Constrained Optimization and Lagrange Multiplier Methods focuses on the advancements in the applications of the Lagrange multiplier methods for constrained minimization. The publication first offers information on the method of multipliers for equality constrained problems and the method of multipliers for inequality constrained and nondifferentiable optimization problems. Discussions focus on approximation procedures for nondifferentiable and ill-conditioned optimization problems; asymptotically exact minimization in the methods of multipliers; duality framework for the method of multipliers; and the quadratic penalty function method. The text then examines exact penalty methods, including nondifferentiable exact penalty functions; linearization algorithms based on nondifferentiable exact penalty functions; differentiable exact penalty functions; and local and global convergence of Lagrangian methods. The book ponders on the nonquadratic penalty functions of convex programming. Topics include large scale separable integer programming problems and the exponential method of multipliers; classes of penalty functions and corresponding methods of multipliers; and convergence analysis of multiplier methods. The text is a valuable reference for mathematicians and researchers interested in the Lagrange multiplier methods.

Author:
Publisher:
ISBN: 9780815332183
Category : Cells
Languages : en
Pages : 0

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Author: Anders Liljas
Publisher: World Scientific
ISBN: 9813142499
Category : Science
Languages : en
Pages : 610

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Book Description
This book provides a comprehensive coverage of the basic principles of structural biology, as well as an up-to-date summary of some main directions of research in the field. The relationship between structure and function is described in detail for soluble proteins, membrane proteins, membranes, and nucleic acids.There are several books covering protein structure and function, but none that give a complete picture, including nucleic acids, lipids, membranes and carbohydrates, all being of central importance in structural biology.The book covers state-of-the-art research in various areas. It is unique for its breadth of coverage by experts in the fields. The book is richly illustrated with more than 400 color figures to highlight the wide range of structures.

Author: Kenneth M.Jr. Merz
Publisher: Springer Science & Business Media
ISBN: 1468468316
Category : Science
Languages : en
Pages : 585

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Book Description
A solution to the protein folding problem has eluded researchers for more than 30 years. The stakes are high. Such a solution will make 40,000 more tertiary structures available for immediate study by translating the DNA sequence information in the sequence databases into three-dimensional protein structures. This translation will be indispensable for the analy sis of results from the Human Genome Project, de novo protein design, and many other areas of biotechnological research. Finally, an in-depth study of the rules of protein folding should provide vital clues to the protein fold ing process. The search for these rules is therefore an important objective for theoretical molecular biology. Both experimental and theoretical ap proaches have been used in the search for a solution, with many promising results but no general solution. In recent years, there has been an exponen tial increase in the power of computers. This has triggered an incredible outburst of theoretical approaches to solving the protein folding problem ranging from molecular dynamics-based studies of proteins in solution to the actual prediction of protein structures from first principles. This volume attempts to present a concise overview of these advances. Adrian Roitberg and Ron Elber describe the locally enhanced sam pling/simulated annealing conformational search algorithm (Chapter 1), which is potentially useful for the rapid conformational search of larger molecular systems.

Author: Mohammed Zaki
Publisher: Springer Science & Business Media
ISBN: 1588297527
Category : Science
Languages : en
Pages : 338

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Book Description
This book covers elements of both the data-driven comparative modeling approach to structure prediction and also recent attempts to simulate folding using explicit or simplified models. Despite the unsolved mystery of how a protein folds, advances are being made in predicting the interactions of proteins with other molecules. Also rapidly advancing are the methods for solving the inverse folding problem, the problem of finding a sequence to fit a structure. This book focuses on the various computational methods for prediction, their successes and their limitations, from the perspective of their most well known practitioners.

Author: Paul Embrechts
Publisher: Springer Science & Business Media
ISBN: 3642334830
Category : Business & Economics
Languages : en
Pages : 657

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Book Description
"A reader's first impression on leafing through this book is of the large number of graphs and diagrams, used to illustrate shapes of distributions...and to show real data examples in various ways. A closer reading reveals a nice mix of theory and applications, with the copious graphical illustrations alluded to. Such a mixture is of course dear to the heart of the applied probabilist/statistician, and should impress even the most ardent theorists." --MATHEMATICAL REVIEWS

Author: Kristof T. Schütt
Publisher: Springer Nature
ISBN: 3030402452
Category : Science
Languages : en
Pages : 473

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Book Description
Designing molecules and materials with desired properties is an important prerequisite for advancing technology in our modern societies. This requires both the ability to calculate accurate microscopic properties, such as energies, forces and electrostatic multipoles of specific configurations, as well as efficient sampling of potential energy surfaces to obtain corresponding macroscopic properties. Tools that can provide this are accurate first-principles calculations rooted in quantum mechanics, and statistical mechanics, respectively. Unfortunately, they come at a high computational cost that prohibits calculations for large systems and long time-scales, thus presenting a severe bottleneck both for searching the vast chemical compound space and the stupendously many dynamical configurations that a molecule can assume. To overcome this challenge, recently there have been increased efforts to accelerate quantum simulations with machine learning (ML). This emerging interdisciplinary community encompasses chemists, material scientists, physicists, mathematicians and computer scientists, joining forces to contribute to the exciting hot topic of progressing machine learning and AI for molecules and materials. The book that has emerged from a series of workshops provides a snapshot of this rapidly developing field. It contains tutorial material explaining the relevant foundations needed in chemistry, physics as well as machine learning to give an easy starting point for interested readers. In addition, a number of research papers defining the current state-of-the-art are included. The book has five parts (Fundamentals, Incorporating Prior Knowledge, Deep Learning of Atomistic Representations, Atomistic Simulations and Discovery and Design), each prefaced by editorial commentary that puts the respective parts into a broader scientific context.

Author: Shirley Dowdy
Publisher: John Wiley & Sons
ISBN: 0471477427
Category : Mathematics
Languages : en
Pages : 646

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Book Description
Praise for the Second Edition "Statistics for Research has other fine qualities besides superior organization. The examples and the statistical methods are laid out with unusual clarity by the simple device of using special formats for each. The book was written with great care and is extremely user-friendly."—The UMAP Journal Although the goals and procedures of statistical research have changed little since the Second Edition of Statistics for Research was published, the almost universal availability of personal computers and statistical computing application packages have made it possible for today's statisticians to do more in less time than ever before. The Third Edition of this bestselling text reflects how the changes in the computing environment have transformed the way statistical analyses are performed today. Based on extensive input from university statistics departments throughout the country, the authors have made several important and timely revisions, including: Additional material on probability appears early in the text New sections on odds ratios, ratio and difference estimations, repeated measure analysis, and logistic regression New examples and exercises, many from the field of the health sciences Printouts of computer analyses on all complex procedures An accompanying Web site illustrating how to use SAS® and JMP® for all procedures The text features the most commonly used statistical techniques for the analysis of research data. As in the earlier editions, emphasis is placed on how to select the proper statistical procedure and how to interpret results. Whenever possible, to avoid using the computer as a "black box" that performs a mysterious process on the data, actual computational procedures are also given. A must for scientists who analyze data, professionals and researchers who need a self-teaching text, and graduate students in statistical methods, Statistics for Research, Third Edition brings the methodology up to date in a very practical and accessible way.

Author: Daniel John Rigden
Publisher: Springer Science & Business Media
ISBN: 1402090587
Category : Science
Languages : en
Pages : 330

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Book Description
Proteins lie at the heart of almost all biological processes and have an incredibly wide range of activities. Central to the function of all proteins is their ability to adopt, stably or sometimes transiently, structures that allow for interaction with other molecules. An understanding of the structure of a protein can therefore lead us to a much improved picture of its molecular function. This realisation has been a prime motivation of recent Structural Genomics projects, involving large-scale experimental determination of protein structures, often those of proteins about which little is known of function. These initiatives have, in turn, stimulated the massive development of novel methods for prediction of protein function from structure. Since model structures may also take advantage of new function prediction algorithms, the first part of the book deals with the various ways in which protein structures may be predicted or inferred, including specific treatment of membrane and intrinsically disordered proteins. A detailed consideration of current structure-based function prediction methodologies forms the second part of this book, which concludes with two chapters, focusing specifically on case studies, designed to illustrate the real-world application of these methods. With bang up-to-date texts from world experts, and abundant links to publicly available resources, this book will be invaluable to anyone who studies proteins and the endlessly fascinating relationship between their structure and function.