Algorithms And Methods In Structural Bioinformatics

Author : Nurit Haspel,Filip Jagodzinski,Kevin Molloy
Publisher : Springer Nature
Page : 120 pages
File Size : 49,9 Mb
Release : 2022-09-01
Category : Science
ISBN : 9783031059148

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Algorithms and Methods in Structural Bioinformatics by Nurit Haspel,Filip Jagodzinski,Kevin Molloy Pdf

The three-dimensional structure and function of molecules present many challenges and opportunities for developing an understanding of biological systems. With the increasing availability of molecular structures and the advancing accuracy of structure predictions and molecular simulations, the space for algorithmic advancement on many analytical and predictive problems is both broad and deep. To support this field, a rich set of methods and algorithms are available, addressing a variety of important problems such as protein-protein interactions, the effect of mutations on protein structure and function, and protein structure determination. Despite recent advancements in the field, in particular in protein folding with the development of AlphaFold, many problems still remain unsolved. In this book we focus on a number of topics in Structural Bioinformatics: Cryo-EM structural detection, protein conformational exploration, elucidation of molecular binding surface using geometry, the effect of mutations, insertions and deletions on protein structural stability, and protein-ligand binding.

Author : Forbes J. Burkowski
Publisher : CRC Press
Page : 429 pages
File Size : 41,6 Mb
Release : 2008-10-30
Category : Science
ISBN : 9781420011791

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Structural Bioinformatics by Forbes J. Burkowski Pdf

The Beauty of Protein Structures and the Mathematics behind Structural Bioinformatics Providing the framework for a one-semester undergraduate course, Structural Bioinformatics: An Algorithmic Approach shows how to apply key algorithms to solve problems related to macromolecular structure. Helps Students Go Further in Their Study of Structural Biology Following some introductory material in the first few chapters, the text solves the longest common subsequence problem using dynamic programming and explains the science models for the Nussinov and MFOLD algorithms. It then reviews sequence alignment, along with the basic mathematical calculations needed for measuring the geometric properties of macromolecules. After looking at how coordinate transformations facilitate the translation and rotation of molecules in a 3D space, the author introduces structural comparison techniques, superposition algorithms, and algorithms that compare relationships within a protein. The final chapter explores how regression and classification are becoming more useful in protein analysis and drug design. At the Crossroads of Biology, Mathematics, and Computer Science Connecting biology, mathematics, and computer science, this practical text presents various bioinformatics topics and problems within a scientific methodology that emphasizes nature (the source of empirical observations), science (the mathematical modeling of the natural process), and computation (the science of calculating predictions and mathematical objects based on mathematical models).

Author : Ion Mandoiu,Alexander Zelikovsky
Publisher : John Wiley & Sons
Page : 528 pages
File Size : 52,8 Mb
Release : 2008-02-25
Category : Computers
ISBN : 9780470097731

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Bioinformatics Algorithms by Ion Mandoiu,Alexander Zelikovsky Pdf

Presents algorithmic techniques for solving problems in bioinformatics, including applications that shed new light on molecular biology This book introduces algorithmic techniques in bioinformatics, emphasizing their application to solving novel problems in post-genomic molecular biology. Beginning with a thought-provoking discussion on the role of algorithms in twenty-first-century bioinformatics education, Bioinformatics Algorithms covers: General algorithmic techniques, including dynamic programming, graph-theoretical methods, hidden Markov models, the fast Fourier transform, seeding, and approximation algorithms Algorithms and tools for genome and sequence analysis, including formal and approximate models for gene clusters, advanced algorithms for non-overlapping local alignments and genome tilings, multiplex PCR primer set selection, and sequence/network motif finding Microarray design and analysis, including algorithms for microarray physical design, missing value imputation, and meta-analysis of gene expression data Algorithmic issues arising in the analysis of genetic variation across human population, including computational inference of haplotypes from genotype data and disease association search in case/control epidemiologic studies Algorithmic approaches in structural and systems biology, including topological and structural classification in biochemistry, and prediction of protein-protein and domain-domain interactions Each chapter begins with a self-contained introduction to a computational problem; continues with a brief review of the existing literature on the subject and an in-depth description of recent algorithmic and methodological developments; and concludes with a brief experimental study and a discussion of open research challenges. This clear and approachable presentation makes the book appropriate for researchers, practitioners, and graduate students alike.

Author : Jenny Gu,Philip E. Bourne
Publisher : John Wiley & Sons
Page : 1105 pages
File Size : 44,8 Mb
Release : 2011-09-20
Category : Science
ISBN : 9781118210567

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Structural Bioinformatics by Jenny Gu,Philip E. Bourne Pdf

Structural Bioinformatics was the first major effort to show the application of the principles and basic knowledge of the larger field of bioinformatics to questions focusing on macromolecular structure, such as the prediction of protein structure and how proteins carry out cellular functions, and how the application of bioinformatics to these life science issues can improve healthcare by accelerating drug discovery and development. Designed primarily as a reference, the first edition nevertheless saw widespread use as a textbook in graduate and undergraduate university courses dealing with the theories and associated algorithms, resources, and tools used in the analysis, prediction, and theoretical underpinnings of DNA, RNA, and proteins. This new edition contains not only thorough updates of the advances in structural bioinformatics since publication of the first edition, but also features eleven new chapters dealing with frontier areas of high scientific impact, including: sampling and search techniques; use of mass spectrometry; genome functional annotation; and much more. Offering detailed coverage for practitioners while remaining accessible to the novice, Structural Bioinformatics, Second Edition is a valuable resource and an excellent textbook for a range of readers in the bioinformatics and advanced biology fields. Praise for the previous edition: "This book is a gold mine of fundamental and practical information in an area not previously well represented in book form." —Biochemistry and Molecular Education "... destined to become a classic reference work for workers at all levels in structural bioinformatics...recommended with great enthusiasm for educators, researchers, and graduate students." —BAMBED "...a useful and timely summary of a rapidly expanding field." —Nature Structural Biology "...a terrific job in this timely creation of a compilation of articles that appropriately addresses this issue." —Briefings in Bioinformatics

Author : Thomas Hamelryck,Kanti Mardia,Jesper Ferkinghoff-Borg
Publisher : Springer
Page : 399 pages
File Size : 42,7 Mb
Release : 2012-03-23
Category : Medical
ISBN : 9783642272257

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Bayesian Methods in Structural Bioinformatics by Thomas Hamelryck,Kanti Mardia,Jesper Ferkinghoff-Borg Pdf

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.

Author : Huzefa Rangwala,George Karypis
Publisher : John Wiley & Sons
Page : 611 pages
File Size : 49,6 Mb
Release : 2011-03-16
Category : Science
ISBN : 9781118099469

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Introduction to Protein Structure Prediction by Huzefa Rangwala,George Karypis Pdf

A look at the methods and algorithms used to predict protein structure A thorough knowledge of the function and structure of proteins is critical for the advancement of biology and the life sciences as well as the development of better drugs, higher-yield crops, and even synthetic bio-fuels. To that end, this reference sheds light on the methods used for protein structure prediction and reveals the key applications of modeled structures. This indispensable book covers the applications of modeled protein structures and unravels the relationship between pure sequence information and three-dimensional structure, which continues to be one of the greatest challenges in molecular biology. With this resource, readers will find an all-encompassing examination of the problems, methods, tools, servers, databases, and applications of protein structure prediction and they will acquire unique insight into the future applications of the modeled protein structures. The book begins with a thorough introduction to the protein structure prediction problem and is divided into four themes: a background on structure prediction, the prediction of structural elements, tertiary structure prediction, and functional insights. Within those four sections, the following topics are covered: Databases and resources that are commonly used for protein structure prediction The structure prediction flagship assessment (CASP) and the protein structure initiative (PSI) Definitions of recurring substructures and the computational approaches used for solving sequence problems Difficulties with contact map prediction and how sophisticated machine learning methods can solve those problems Structure prediction methods that rely on homology modeling, threading, and fragment assembly Hybrid methods that achieve high-resolution protein structures Parts of the protein structure that may be conserved and used to interact with other biomolecules How the loop prediction problem can be used for refinement of the modeled structures The computational model that detects the differences between protein structure and its modeled mutant Whether working in the field of bioinformatics or molecular biology research or taking courses in protein modeling, readers will find the content in this book invaluable.

Author : Bruce R. Donald
Publisher : MIT Press
Page : 497 pages
File Size : 52,5 Mb
Release : 2023-08-15
Category : Science
ISBN : 9780262548793

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Algorithms in Structural Molecular Biology by Bruce R. Donald Pdf

An overview of algorithms important to computational structural biology that addresses such topics as NMR and design and analysis of proteins.Using the tools of information technology to understand the molecular machinery of the cell offers both challenges and opportunities to computational scientists. Over the past decade, novel algorithms have been developed both for analyzing biological data and for synthetic biology problems such as protein engineering. This book explains the algorithmic foundations and computational approaches underlying areas of structural biology including NMR (nuclear magnetic resonance); X-ray crystallography; and the design and analysis of proteins, peptides, and small molecules. Each chapter offers a concise overview of important concepts, focusing on a key topic in the field. Four chapters offer a short course in algorithmic and computational issues related to NMR structural biology, giving the reader a useful toolkit with which to approach the fascinating yet thorny computational problems in this area. A recurrent theme is understanding the interplay between biophysical experiments and computational algorithms. The text emphasizes the mathematical foundations of structural biology while maintaining a balance between algorithms and a nuanced understanding of experimental data. Three emerging areas, particularly fertile ground for research students, are highlighted: NMR methodology, design of proteins and other molecules, and the modeling of protein flexibility. The next generation of computational structural biologists will need training in geometric algorithms, provably good approximation algorithms, scientific computation, and an array of techniques for handling noise and uncertainty in combinatorial geometry and computational biophysics. This book is an essential guide for young scientists on their way to research success in this exciting field.

Author : Lukasz Kurgan
Publisher : World Scientific
Page : 378 pages
File Size : 54,8 Mb
Release : 2022-12-06
Category : Science
ISBN : 9789811258596

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Machine Learning In Bioinformatics Of Protein Sequences: Algorithms, Databases And Resources For Modern Protein Bioinformatics by Lukasz Kurgan Pdf

Machine Learning in Bioinformatics of Protein Sequences guides readers around the rapidly advancing world of cutting-edge machine learning applications in the protein bioinformatics field. Edited by bioinformatics expert, Dr Lukasz Kurgan, and with contributions by a dozen of accomplished researchers, this book provides a holistic view of the structural bioinformatics by covering a broad spectrum of algorithms, databases and software resources for the efficient and accurate prediction and characterization of functional and structural aspects of proteins. It spotlights key advances which include deep neural networks, natural language processing-based sequence embedding and covers a wide range of predictions which comprise of tertiary structure, secondary structure, residue contacts, intrinsic disorder, protein, peptide and nucleic acids-binding sites, hotspots, post-translational modification sites, and protein function. This volume is loaded with practical information that identifies and describes leading predictive tools, useful databases, webservers, and modern software platforms for the development of novel predictive tools.

Author : Mourad Elloumi,Albert Y. Zomaya
Publisher : John Wiley & Sons
Page : 1027 pages
File Size : 41,8 Mb
Release : 2011-04-04
Category : Science
ISBN : 9781118101988

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Algorithms in Computational Molecular Biology by Mourad Elloumi,Albert Y. Zomaya Pdf

This book represents the most comprehensive and up-to-date collection of information on the topic of computational molecular biology. Bringing the most recent research into the forefront of discussion, Algorithms in Computational Molecular Biology studies the most important and useful algorithms currently being used in the field, and provides related problems. It also succeeds where other titles have failed, in offering a wide range of information from the introductory fundamentals right up to the latest, most advanced levels of study.

Author : Yi Pan,Min Li,Jianxin Wang
Publisher : John Wiley & Sons
Page : 534 pages
File Size : 42,8 Mb
Release : 2013-10-07
Category : Medical
ISBN : 9781118567814

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Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics by Yi Pan,Min Li,Jianxin Wang Pdf

Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics An in-depth look at the latest research, methods, and applications in the field of protein bioinformatics This book presents the latest developments in protein bioinformatics, introducing for the first time cutting-edge research results alongside novel algorithmic and AI methods for the analysis of protein data. In one complete, self-contained volume, Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics addresses key challenges facing both computer scientists and biologists, arming readers with tools and techniques for analyzing and interpreting protein data and solving a variety of biological problems. Featuring a collection of authoritative articles by leaders in the field, this work focuses on the analysis of protein sequences, structures, and interaction networks using both traditional algorithms and AI methods. It also examines, in great detail, data preparation, simulation, experiments, evaluation methods, and applications. Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics: Highlights protein analysis applications such as protein-related drug activity comparison Incorporates salient case studies illustrating how to apply the methods outlined in the book Tackles the complex relationship between proteins from a systems biology point of view Relates the topic to other emerging technologies such as data mining and visualization Includes many tables and illustrations demonstrating concepts and performance figures Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics is an essential reference for bioinformatics specialists in research and industry, and for anyone wishing to better understand the rich field of protein bioinformatics.

Author : Ben Raphael,Jijun Tang
Publisher : Springer
Page : 454 pages
File Size : 48,8 Mb
Release : 2012-08-29
Category : Computers
ISBN : 9783642331220

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Algorithms in Bioinformatics by Ben Raphael,Jijun Tang Pdf

This book constitutes the refereed proceedings of the 12th International Workshop on Algorithms in Bioinformatics, WABI 2012, held in Ljubljana, Slovenia, in September 2012. WABI 2012 is one of six workshops which, along with the European Symposium on Algorithms (ESA), constitute the ALGO annual meeting and focuses on algorithmic advances in bioinformatics, computational biology, and systems biology with a particular emphasis on discrete algorithms and machine-learning methods that address important problems in molecular biology. The 35 full papers presented were carefully reviewed and selected from 92 submissions. The papers include algorithms for a variety of biological problems including phylogeny, DNA and RNA sequencing and analysis, protein structure, and others.

Author : Rita Casadio
Publisher : Springer Science & Business Media
Page : 446 pages
File Size : 52,9 Mb
Release : 2005-09-27
Category : Computers
ISBN : 9783540290087

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Algorithms in Bioinformatics by Rita Casadio Pdf

This book constitutes the refereed proceedings of the 5th International Workshop on Algorithms in Bioinformatics, WABI 2005, held in Mallorca, Spain, in September 2005 as part of the ALGO 2005 conference meetings. The 34 revised full papers presented were carefully reviewed and selected from 95 submissions. All current issues of algorithms in bioinformatics are addressed with special focus on statistical and probabilistic algorithms in the field of molecular and structural biology. The papers are organized in topical sections on expression (hybrid methods and time patterns), phylogeny (quartets, tree reconciliation, clades and haplotypes), networks, genome rearrangements (transposition model and other models), sequences (strings, multi-alignment and clustering, clustering and representation), and structure (threading and folding).

Author : Anonim
Publisher : Unknown
Page : 128 pages
File Size : 42,9 Mb
Release : 2024-05-20
Category : Electronic
ISBN : 9789814472418

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Computational Structural Biology by Anonim Pdf

Author : Steffen Schulze-Kremer
Publisher : Walter de Gruyter
Page : 324 pages
File Size : 43,5 Mb
Release : 1996
Category : Business & Economics
ISBN : 3110141132

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Molecular Bioinformatics by Steffen Schulze-Kremer Pdf

Author : Dariusz Mrozek
Publisher : Springer
Page : 109 pages
File Size : 44,8 Mb
Release : 2014-06-04
Category : Computers
ISBN : 9783319069715

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High-Performance Computational Solutions in Protein Bioinformatics by Dariusz Mrozek Pdf

Recent developments in computer science enable algorithms previously perceived as too time-consuming to now be efficiently used for applications in bioinformatics and life sciences. This work focuses on proteins and their structures, protein structure similarity searching at main representation levels and various techniques that can be used to accelerate similarity searches. Divided into four parts, the first part provides a formal model of 3D protein structures for functional genomics, comparative bioinformatics and molecular modeling. The second part focuses on the use of multithreading for efficient approximate searching on protein secondary structures. The third and fourth parts concentrate on finding 3D protein structure similarities with the support of GPUs and cloud computing. Parts three and four both describe the acceleration of different methods. The text will be of interest to researchers and software developers working in the field of structural bioinformatics and biomedical databases.