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Author : Marco Mernberger
Publisher :
ISBN 13 :
Total Pages : 229 pages
Book Rating : 4.:/5 (773 download)
Download or read book Graph-based Approaches to Protein Structure Comparison written by Marco Mernberger and published by . This book was released on 2011 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Henning Stehr
Publisher :
ISBN 13 :
Total Pages : 89 pages
Book Rating : 4.:/5 (811 download)
Download or read book Graph-based Approaches to Protein Structure- and Function Prediction written by Henning Stehr and published by . This book was released on 2011 with total page 89 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Thomas Fober
Publisher : Sudwestdeutscher Verlag Fur Hochschulschriften AG
ISBN 13 : 9783838134796
Total Pages : 404 pages
Book Rating : 4.1/5 (347 download)
Download or read book Geometric, Feature- and Graph-based Analysis of Protein Structures written by Thomas Fober and published by Sudwestdeutscher Verlag Fur Hochschulschriften AG. This book was released on 2013 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: The structural comparison of whole proteins or protein binding sites is usually performed by making use of graphs. Even though graphs exhibit a lot of interesting and useful properties, the usage of other representations can come along with several benefits. In this book the representation of a protein binding site is tackled. Three representations are considered namely the geometric, the feature-based and the graph-based representation. For all three types, some completely new algorithms are developed and presented. Moreover, existing methods are adapted to the application of protein binding sites' comparison. In addition, algorithms for the construction of multiple structural alignments are presented as a structural counterpart to multiple sequence alignment. By considering four different types of experiments, namely classification, similarity retrieval, clustering and construction of structural alignments, strengths and weaknesses of the proposed methods are detected and discussed. In addition a hybrid approach is presented which combines the benefits of a feature-based and a geometric method leading to a significant speed-up while still holding very good results.
Author : Noël Malod-Dognin
Publisher :
ISBN 13 :
Total Pages : 91 pages
Book Rating : 4.:/5 (69 download)
Download or read book Protein Structure Comparison written by Noël Malod-Dognin and published by . This book was released on 2010 with total page 91 pages. Available in PDF, EPUB and Kindle. Book excerpt: In molecular biology, a fruitful assumption is that proteins sharing close three dimensional structures may share a common function and in most cases derive from a same ancestor. Computing the similarity between two protein structures is therefore a crucial task and has been extensively investigated. Among all the proposed methods, we focus on the similarity measure called Contact Map Overlap maximisation (CMO), mainly because it provides scores which can be used for obtaining good automatic classifications of the protein structures. In this thesis, comparing two protein structures is modelled as finding specific sub-graphs in specific k-partite graphs called alignment graphs. Then, we model CMO as a kind of maximum edge induced sub-graph problem in alignment graphs, for which we conceive an exact solver which outperforms the other CMO algorithms from the literature. Even though we succeeded to accelerate CMO, the procedure still stays too much time consuming for large database comparisons. To further accelerate CMO, we propose a hierarchical approach for CMO which is based on the secondary structure of the proteins. Finally, although CMO is a very good scoring scheme, the alignments it provides frequently posses big root mean square deviation values. To overcome this weakness, we propose a new comparison method based on internal distances which we call DAST (for Distance-based Alignment Search Tool). It is modelled as a maximum clique problem in alignment graphs, for which we design a dedicated solver with very good performances.
Author : Ronald C. Read
Publisher : Mathematics
ISBN 13 : 9780198526506
Total Pages : 0 pages
Book Rating : 4.5/5 (265 download)
Download or read book An Atlas of Graphs written by Ronald C. Read and published by Mathematics. This book was released on 2004 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Ying Xu
Publisher : Springer Science & Business Media
ISBN 13 : 0387683720
Total Pages : 408 pages
Book Rating : 4.3/5 (876 download)
Download or read book Computational Methods for Protein Structure Prediction and Modeling written by Ying Xu and published by Springer Science & Business Media. This book was released on 2007-08-24 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: Volume One of this two-volume sequence focuses on the basic characterization of known protein structures, and structure prediction from protein sequence information. Eleven chapters survey of the field, covering key topics in modeling, force fields, classification, computational methods, and structure prediction. Each chapter is a self contained review covering definition of the problem and historical perspective; mathematical formulation; computational methods and algorithms; performance results; existing software; strengths, pitfalls, challenges, and future research.
Author : Cedric Chauve
Publisher : Springer Science & Business Media
ISBN 13 : 1447152980
Total Pages : 329 pages
Book Rating : 4.4/5 (471 download)
Download or read book Models and Algorithms for Genome Evolution written by Cedric Chauve and published by Springer Science & Business Media. This book was released on 2013-09-17 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: This authoritative text/reference presents a review of the history, current status, and potential future directions of computational biology in molecular evolution. Gathering together the unique insights of an international selection of prestigious researchers, this must-read volume examines the latest developments in the field, the challenges that remain, and the new avenues emerging from the growing influx of sequence data. These viewpoints build upon the pioneering work of David Sankoff, one of the founding fathers of computational biology, and mark the 50th anniversary of his first scientific article. The broad spectrum of rich contributions in this essential collection will appeal to all computer scientists, mathematicians and biologists involved in comparative genomics, phylogenetics and related areas.
Author : Mourad Elloumi
Publisher : John Wiley & Sons
ISBN 13 : 1119078857
Total Pages : 655 pages
Book Rating : 4.1/5 (19 download)
Download or read book Pattern Recognition in Computational Molecular Biology written by Mourad Elloumi and published by John Wiley & Sons. This book was released on 2015-11-30 with total page 655 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive overview of high-performance pattern recognition techniques and approaches to Computational Molecular Biology This book surveys the developments of techniques and approaches on pattern recognition related to Computational Molecular Biology. Providing a broad coverage of the field, the authors cover fundamental and technical information on these techniques and approaches, as well as discussing their related problems. The text consists of twenty nine chapters, organized into seven parts: Pattern Recognition in Sequences, Pattern Recognition in Secondary Structures, Pattern Recognition in Tertiary Structures, Pattern Recognition in Quaternary Structures, Pattern Recognition in Microarrays, Pattern Recognition in Phylogenetic Trees, and Pattern Recognition in Biological Networks. Surveys the development of techniques and approaches on pattern recognition in biomolecular data Discusses pattern recognition in primary, secondary, tertiary and quaternary structures, as well as microarrays, phylogenetic trees and biological networks Includes case studies and examples to further illustrate the concepts discussed in the book Pattern Recognition in Computational Molecular Biology: Techniques and Approaches is a reference for practitioners and professional researches in Computer Science, Life Science, and Mathematics. This book also serves as a supplementary reading for graduate students and young researches interested in Computational Molecular Biology.
Author : Concettina Guerra
Publisher : Springer Science & Business Media
ISBN 13 : 3540401040
Total Pages : 161 pages
Book Rating : 4.5/5 (44 download)
Download or read book Mathematical Methods for Protein Structure Analysis and Design written by Concettina Guerra and published by Springer Science & Business Media. This book was released on 2003-06-25 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt: The papers collected in this volume reproduce contributions by leading sch- arstoaninternationalschoolandworkshopwhichwasorganizedandheldwith thegoaloftakinga snapshotofadiscipline undertumultuous growth. Indeed, the area of protein folding, docking and alignment is developing in response to needs for a mix of heterogeneous expertise spanning biology, chemistry, mathematics, computer science, and statistics, among others. Some of the problems encountered in this area are not only important for the scienti?c challenges they pose, but also for the opportunities they disclose intermsofmedicalandindustrialexploitation. Atypicalexampleiso?eredby protein-drug interaction (docking), a problem posing daunting computational problems at the crossroads of geometry, physics and chemistry, and, at the same time, a problem with unimaginable implications for the pharmacopoeia of the future. The schoolfocused on problems posed by the study of the mechanisms - hind protein folding, and explored di?erent ways of attacking these problems under objective evaluations of the methods. Together with a relatively small core of consolidated knowledge and tools, important re?ections were brought to this e?ort by studies in a multitude of directions and approaches. It is obviously impossible to predict which, if any, among these techniques will prove completely successful, but it is precisely the implicit dialectic among them that best conveys the current ?avor of the ?eld. Such unique diversity and richness inspired the format of the meeting, and also explains the slight departure of the present volume from the typical format in this series: the exposition of the current sediment is complemented here by a selection of quali?ed specialized contributions.
Author : Gulsah Altun
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (233 download)
Download or read book Machine Learning and Graph Theory Approaches for Classification and Prediction of Protein Structure written by Gulsah Altun and published by . This book was released on 2008 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Recently, many methods have been proposed for the classification and prediction problems in bioinformatics. One of these problems is the protein structure prediction. Machine learning approaches and new algorithms have been proposed to solve this problem. Among the machine learning approaches, Support Vector Machines (SVM) have attracted a lot of attention due to their high prediction accuracy. Since protein data consists of sequence and structural information, another most widely used approach for modeling this structured data is to use graphs. In computer science, graph theory has been widely studied; however it has only been recently applied to bioinformatics. In this work, we introduced new algorithms based on statistical methods, graph theory concepts and machine learning for the protein structure prediction problem. A new statistical method based on z-scores has been introduced for seed selection in proteins. A new method based on finding common cliques in protein data for feature selection is also introduced, which reduces noise in the data. We also introduced new binary classifiers for the prediction of structural transitions in proteins. These new binary classifiers achieve much higher accuracy results than the current traditional binary classifiers.
Author : Ilan Samish
Publisher : Humana
ISBN 13 : 9781493966356
Total Pages : 0 pages
Book Rating : 4.9/5 (663 download)
Download or read book Computational Protein Design written by Ilan Samish and published by Humana. This book was released on 2016-12-03 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim this volume is to present the methods, challenges, software, and applications of this widespread and yet still evolving and maturing field. Computational Protein Design, the first book with this title, guides readers through computational protein design approaches, software and tailored solutions to specific case-study targets. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, Computational Protein Design aims to ensure successful results in the further study of this vital field.
Author : Andrew J. W. Orry
Publisher : Humana Press
ISBN 13 : 9781617795879
Total Pages : 419 pages
Book Rating : 4.7/5 (958 download)
Download or read book Homology Modeling written by Andrew J. W. Orry and published by Humana Press. This book was released on 2012-02-10 with total page 419 pages. Available in PDF, EPUB and Kindle. Book excerpt: Knowledge about protein tertiary structure can guide experiments, assist in the understanding of structure-function relationships, and aid the design of new therapeutics for disease. Homology modeling is an in silico method that predicts the tertiary structure of an amino acid sequence based on a homologous experimentally determined structure. In, Homology Modelling: Methods and Protocols experts in the field describe each homology modeling step from first principles, provide case studies for challenging modeling targets and describe methods for the prediction of how other molecules such as drugs can interact with the protein. Written in the highly successful Methods in Molecular BiologyTM series format, the chapters include the kind of detailed description and implementation advice that is crucial for getting optimal results in the laboratory. Thorough and intuitive, Homology Modelling: Methods and Protocols guides scientists in the available homology modeling methods.
Author : Francisco Azuaje
Publisher : John Wiley & Sons
ISBN 13 : 0470094400
Total Pages : 284 pages
Book Rating : 4.4/5 (7 download)
Download or read book Data Analysis and Visualization in Genomics and Proteomics written by Francisco Azuaje and published by John Wiley & Sons. This book was released on 2005-06-24 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Analysis and Visualization in Genomics and Proteomics is the first book addressing integrative data analysis and visualization in this field. It addresses important techniques for the interpretation of data originating from multiple sources, encoded in different formats or protocols, and processed by multiple systems. One of the first systematic overviews of the problem of biological data integration using computational approaches This book provides scientists and students with the basis for the development and application of integrative computational methods to analyse biological data on a systemic scale Places emphasis on the processing of multiple data and knowledge resources, and the combination of different models and systems
Author : William L. William L. Hamilton
Publisher : Springer Nature
ISBN 13 : 3031015886
Total Pages : 141 pages
Book Rating : 4.0/5 (31 download)
Download or read book Graph Representation Learning written by William L. William L. Hamilton and published by Springer Nature. This book was released on 2022-06-01 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt: Graph-structured data is ubiquitous throughout the natural and social sciences, from telecommunication networks to quantum chemistry. Building relational inductive biases into deep learning architectures is crucial for creating systems that can learn, reason, and generalize from this kind of data. Recent years have seen a surge in research on graph representation learning, including techniques for deep graph embeddings, generalizations of convolutional neural networks to graph-structured data, and neural message-passing approaches inspired by belief propagation. These advances in graph representation learning have led to new state-of-the-art results in numerous domains, including chemical synthesis, 3D vision, recommender systems, question answering, and social network analysis. This book provides a synthesis and overview of graph representation learning. It begins with a discussion of the goals of graph representation learning as well as key methodological foundations in graph theory and network analysis. Following this, the book introduces and reviews methods for learning node embeddings, including random-walk-based methods and applications to knowledge graphs. It then provides a technical synthesis and introduction to the highly successful graph neural network (GNN) formalism, which has become a dominant and fast-growing paradigm for deep learning with graph data. The book concludes with a synthesis of recent advancements in deep generative models for graphs—a nascent but quickly growing subset of graph representation learning.
Author : Stephen Schuh
Publisher :
ISBN 13 :
Total Pages : 40 pages
Book Rating : 4.:/5 (757 download)
Download or read book A Graph-based Algorithm to Determine Protein Structure from Cryo-EM Data written by Stephen Schuh and published by . This book was released on 2011 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : De-Shuang Huang
Publisher : Springer Science & Business Media
ISBN 13 : 3642149316
Total Pages : 701 pages
Book Rating : 4.6/5 (421 download)
Download or read book Advanced Intelligent Computing Theories and Applications: With Aspects of Artificial Intelligence written by De-Shuang Huang and published by Springer Science & Business Media. This book was released on 2010-07-30 with total page 701 pages. Available in PDF, EPUB and Kindle. Book excerpt: The International Conference on Intelligent Computing (ICIC) was formed to provide an annual forum dedicated to the emerging and challenging topics in artificial intel- gence, machine learning, pattern recognition, image processing, bioinformatics, and computational biology. It aims to bring together researchers and practitioners from both academia and industry to share ideas, problems, and solutions related to the m- tifaceted aspects of intelligent computing. ICIC 2010, held in Changsha, China, August 18–21, 2010, constituted the 6th - ternational Conference on Intelligent Computing. It built upon the success of ICIC 2009, ICIC 2008, ICIC 2007, ICIC 2006, and ICIC 2005, that were held in Ulsan, Korea, Shanghai, Qingdao, Kunming, and Hefei, China, respectively. This year, the conference concentrated mainly on the theories and methodologies as well as the emerging applications of intelligent computing. Its aim was to unify the picture of contemporary intelligent computing techniques as an integral concept that highlights the trends in advanced computational intelligence and bridges theoretical research with applications. Therefore, the theme for this conference was “Advanced Intelligent Computing Technology and Applications.” Papers focusing on this theme were solicited, addressing theories, methodologies, and applications in science and technology.
Author : Henry Horng-Shing Lu
Publisher : Springer Science & Business Media
ISBN 13 : 3642163459
Total Pages : 621 pages
Book Rating : 4.6/5 (421 download)
Download or read book Handbook of Statistical Bioinformatics written by Henry Horng-Shing Lu and published by Springer Science & Business Media. This book was released on 2011-05-17 with total page 621 pages. Available in PDF, EPUB and Kindle. Book excerpt: Numerous fascinating breakthroughs in biotechnology have generated large volumes and diverse types of high throughput data that demand the development of efficient and appropriate tools in computational statistics integrated with biological knowledge and computational algorithms. This volume collects contributed chapters from leading researchers to survey the many active research topics and promote the visibility of this research area. This volume is intended to provide an introductory and reference book for students and researchers who are interested in the recent developments of computational statistics in computational biology.
