Pattern Recognition in Computational Molecular Biology

Pattern Recognition in Computational Molecular Biology PDF Author: Mourad Elloumi
Publisher: John Wiley & Sons
ISBN: 1119078857
Category : Technology & Engineering
Languages : en
Pages : 655

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Book Description
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.

Pattern Recognition in Computational Molecular Biology

Pattern Recognition in Computational Molecular Biology PDF Author: Mourad Elloumi
Publisher: John Wiley & Sons
ISBN: 1119078857
Category : Technology & Engineering
Languages : en
Pages : 655

Get Book Here

Book Description
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.

Kernel Methods in Computational Biology

Kernel Methods in Computational Biology PDF Author: Bernhard Schölkopf
Publisher: MIT Press
ISBN: 9780262195096
Category : Computers
Languages : en
Pages : 428

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Book Description
A detailed overview of current research in kernel methods and their application to computational biology.

Artificial Intelligence and Molecular Biology

Artificial Intelligence and Molecular Biology PDF Author: Lawrence Hunter
Publisher:
ISBN:
Category : Computers
Languages : en
Pages : 484

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Book Description
These original contributions provide a current sampling of AI approaches to problems of biological significance; they are the first to treat the computational needs of the biology community hand-in-hand with appropriate advances in artificial intelligence. The enormous amount of data generated by the Human Genome Project and other large-scale biological research has created a rich and challenging domain for research in artificial intelligence. These original contributions provide a current sampling of AI approaches to problems of biological significance; they are the first to treat the computational needs of the biology community hand-in-hand with appropriate advances in artificial intelligence. Focusing on novel technologies and approaches, rather than on proven applications, they cover genetic sequence analysis, protein structure representation and prediction, automated data analysis aids, and simulation of biological systems. A brief introductory primer on molecular biology and Al gives computer scientists sufficient background to understand much of the biology discussed in the book. Lawrence Hunter is Director of the Machine Learning Project at the National Library of Medicine, National Institutes of Health.

Research in Computational Molecular Biology

Research in Computational Molecular Biology PDF Author: Vineet Bafna
Publisher: Springer
ISBN: 3642200362
Category : Computers
Languages : en
Pages : 595

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Book Description
This book constitutes the refereed proceedings of the 15th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2011, held in Vancouver, Canada, in March 2011. The 43 revised full papers were carefully reviewed and selected from 153 submissions. The papers cover a wide range of topics including molecular sequence analysis; recognition of genes and regulatory elements; molecular evolution; gene expression; biological networks; sequencing and genotyping technologies; genomics; population, statistical genetics; systems biology; imaging; computational proteomics; molecular structural biology.

Computational Intelligence

Computational Intelligence PDF Author: Kurosh Madani
Publisher: Springer Science & Business Media
ISBN: 3642275338
Category : Computers
Languages : en
Pages : 422

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Book Description
The present book includes a set of selected extended papers from the second International Joint Conference on Computational Intelligence (IJCCI 2010), held in Valencia, Spain, from 24 to 26 October 2010. The conference was composed by three co-located conferences: The International Conference on Fuzzy Computation (ICFC), the International Conference on Evolutionary Computation (ICEC), and the International Conference on Neural Computation (ICNC). Recent progresses in scientific developments and applications in these three areas are reported in this book. IJCCI received 236 submissions, from 49 countries, in all continents. After a double blind paper review performed by the Program Committee, only 30 submissions were accepted as full papers and thus selected for oral presentation, leading to a full paper acceptance ratio of 13%. Additional papers were accepted as short papers and posters. A further selection was made after the Conference, based also on the assessment of presentation quality and audience interest, so that this book includes the extended and revised versions of the very best papers of IJCCI 2010. Commitment to high quality standards is a major concern of IJCCI that will be maintained in the next editions, considering not only the stringent paper acceptance ratios but also the quality of the program committee, keynote lectures, participation level and logistics.

National Conference on Frontiers in Applied and Computational Mathematics (FACM-2005)

National Conference on Frontiers in Applied and Computational Mathematics (FACM-2005) PDF Author: Harvir Singh Kasana
Publisher: Allied Publishers
ISBN: 9788177647921
Category : Mathematics
Languages : en
Pages : 614

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Book Description


Computational Intelligence and Pattern Analysis in Biology Informatics

Computational Intelligence and Pattern Analysis in Biology Informatics PDF Author: Ujjwal Maulik
Publisher: John Wiley & Sons
ISBN: 9780470581599
Category : Medical
Languages : en
Pages : 0

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Book Description
An invaluable tool in Bioinformatics, this unique volume provides both theoretical and experimental results, and describes basic principles of computational intelligence and pattern analysis while deepening the reader's understanding of the ways in which these principles can be used for analyzing biological data in an efficient manner. This book synthesizes current research in the integration of computational intelligence and pattern analysis techniques, either individually or in a hybridized manner. The purpose is to analyze biological data and enable extraction of more meaningful information and insight from it. Biological data for analysis include sequence data, secondary and tertiary structure data, and microarray data. These data types are complex and advanced methods are required, including the use of domain-specific knowledge for reducing search space, dealing with uncertainty, partial truth and imprecision, efficient linear and/or sub-linear scalability, incremental approaches to knowledge discovery, and increased level and intelligence of interactivity with human experts and decision makers Chapters authored by leading researchers in CI in biology informatics. Covers highly relevant topics: rational drug design; analysis of microRNAs and their involvement in human diseases. Supplementary material included: program code and relevant data sets correspond to chapters.

Multiple Biological Sequence Alignment

Multiple Biological Sequence Alignment PDF Author: Ken Nguyen
Publisher: John Wiley & Sons
ISBN: 1119273757
Category : Science
Languages : en
Pages : 272

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Book Description
Covers the fundamentals and techniques of multiple biological sequence alignment and analysis, and shows readers how to choose the appropriate sequence analysis tools for their tasks This book describes the traditional and modern approaches in biological sequence alignment and homology search. This book contains 11 chapters, with Chapter 1 providing basic information on biological sequences. Next, Chapter 2 contains fundamentals in pair-wise sequence alignment, while Chapters 3 and 4 examine popular existing quantitative models and practical clustering techniques that have been used in multiple sequence alignment. Chapter 5 describes, characterizes and relates many multiple sequence alignment models. Chapter 6 describes how traditionally phylogenetic trees have been constructed, and available sequence knowledge bases can be used to improve the accuracy of reconstructing phylogeny trees. Chapter 7 covers the latest methods developed to improve the run-time efficiency of multiple sequence alignment. Next, Chapter 8 covers several popular existing multiple sequence alignment server and services, and Chapter 9 examines several multiple sequence alignment techniques that have been developed to handle short sequences (reads) produced by the Next Generation Sequencing technique (NSG). Chapter 10 describes a Bioinformatics application using multiple sequence alignment of short reads or whole genomes as input. Lastly, Chapter 11 provides a review of RNA and protein secondary structure prediction using the evolution information inferred from multiple sequence alignments. • Covers the full spectrum of the field, from alignment algorithms to scoring methods, practical techniques, and alignment tools and their evaluations • Describes theories and developments of scoring functions and scoring matrices •Examines phylogeny estimation and large-scale homology search Multiple Biological Sequence Alignment: Scoring Functions, Algorithms and Applications is a reference for researchers, engineers, graduate and post-graduate students in bioinformatics, and system biology and molecular biologists. Ken Nguyen, PhD, is an associate professor at Clayton State University, GA, USA. He received his PhD, MSc and BSc degrees in computer science all from Georgia State University. His research interests are in databases, parallel and distribute computing and bioinformatics. He was a Molecular Basis of Disease fellow at Georgia State and is the recipient of the highest graduate honor at Georgia State, the William M. Suttles Graduate Fellowship. Xuan Guo, PhD, is a postdoctoral associate at Oak Ridge National Lab, USA. He received his PhD degree in computer science from Georgia State University in 2015. His research interests are in bioinformatics, machine leaning, and cloud computing. He is an editorial assistant of International Journal of Bioinformatics Research and Applications. Yi Pan, PhD, is a Regents' Professor of Computer Science and an Interim Associate Dean and Chair of Biology at Georgia State University. He received his BE and ME in computer engineering from Tsinghua University in China and his PhD in computer science from the University of Pittsburgh. Dr. Pan's research interests include parallel and distributed computing, optical networks, wireless networks and bioinformatics. He has published more than 180 journal papers with about 60 papers published in various IEEE/ACM journals. He is co-editor along with Albert Y. Zomaya of the Wiley Series in Bioinformatics.

Algorithms for Next-Generation Sequencing Data

Algorithms for Next-Generation Sequencing Data PDF Author: Mourad Elloumi
Publisher: Springer
ISBN: 3319598260
Category : Computers
Languages : en
Pages : 356

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Book Description
The 14 contributed chapters in this book survey the most recent developments in high-performance algorithms for NGS data, offering fundamental insights and technical information specifically on indexing, compression and storage; error correction; alignment; and assembly. The book will be of value to researchers, practitioners and students engaged with bioinformatics, computer science, mathematics, statistics and life sciences.

Advances in Computational Biology

Advances in Computational Biology PDF Author: H.O. Villar
Publisher: Elsevier
ISBN: 008052611X
Category : Science
Languages : en
Pages : 281

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Book Description
The second volume in a series which aims to focus on advances in computational biology. This volume discusses such topics as: statistical analysis of protein sequences; progress in large-scale sequence analysis; and the architecture of loops in proteins.