Emerging Trends in Computational Biology, Bioinformatics, and Systems Biology

Informationen zum Autor Hamid R. Arabnia is currently a Full Professor of Computer Science at University of Georgia where he has been since October 1987. His research interests include Parallel and distributed processing techniques and algorithms, interconnection networks, and applications in Computational Science and Computational Intelligence (in particular, in image processing, medical imaging, bioinformatics, and other computational intensive problems). Dr. Arabnia is Editor-in-Chief of The Journal of is Associate Editor of IEEE Transactions on Information Technology in Biomedicine . He has over 300 publications (journals, proceedings, editorship) in his area of research in addition he has edited two titles Emerging Trends in ICT Security (Elsevier 2013), and Advances in Computational Biology (Springer 2012). Professor Quoc-Nam Tran is currently Chair and Full Professor of Computer Science at University of South Dakota. He previously served as Chair and Full Professor of Computer Science at the University of Texas at Tyler. His previous positions include: Professor of Computer Science at Lamar University; Visiting Professor at Rice University; Scientist at Wolfram Research, Champaign-Urbana ; and Assistant Professor at University of Linz (Linz, Austria). Professor Tran's research interests include: computational methods and algorithmic foundations; theory of Groebner bases; bioinformatics and computational biology. He has published extensively in his areas of expertise. He has co-edited a number of books, including: "Software Tools and Algorithms for Biological Systems" (2011) and "Advances in Computational Biology" (2010) (Springer) Professor Tran has served on a number of editorial boards and has organized and chaired sessions for premier conferences such as the IEEE International Conference on Bioinformatics and Biomedicine Workshop. Klappentext Emerging Trends in Computational Biology! Bioinformatics! and Systems Biology discusses the latest in all aspects of computational biology! bioinformatics! and systems biology and the application of data-analytical and algorithms! mathematical modeling and simulation techniques. Part I: Computational Biology discusses the development and application of data-analytical and theoretical methods! mathematical modeling and computational simulation techniques. Part II: Bioinformatics: Databases! Data Mining and Pattern Discovery focuses on how to use methods for storing! retrieving! organizing and analyzing biological data which are fundamentally extensions of techniques used in computing. Part III: Systems Biology explains how to obtain! integrate and analyze complex data sets from multiple experimental sources using interdisciplinary tools while taking into consideration the evolving nature of the field. Part IV: Big Data and Data Analytics in Computational Biology and Informatics presents strategies and techniques using robust Big Data tools for dealing with the collection of data sets so large and complex that they are difficult to process using conventional database management systems or traditional data processing applications. ...

Autorentext
Hamid R. Arabnia is currently a Full Professor of Computer Science at University of Georgia where he has been since October 1987. His research interests include Parallel and distributed processing techniques and algorithms, interconnection networks, and applications in Computational Science and Computational Intelligence (in particular, in image processing, medical imaging, bioinformatics, and other computational intensive problems). Dr. Arabnia is Editor-in-Chief of The Journal of is Associate Editor of IEEE Transactions on Information Technology in Biomedicine . He has over 300 publications (journals, proceedings, editorship) in his area of research in addition he has edited two titles Emerging Trends in ICT Security (Elsevier 2013), and Advances in Computational Biology (Springer 2012). Professor Quoc-Nam Tran is currently Chair and Full Professor of Computer Science at University of South Dakota. He previously served as Chair and Full Professor of Computer Science at the University of Texas at Tyler. His previous positions include: Professor of Computer Science at Lamar University; Visiting Professor at Rice University; Scientist at Wolfram Research, Champaign-Urbana ; and Assistant Professor at University of Linz (Linz, Austria). Professor Tran's research interests include: computational methods and algorithmic foundations; theory of Groebner bases; bioinformatics and computational biology. He has published extensively in his areas of expertise. He has co-edited a number of books, including: "Software Tools and Algorithms for Biological Systems" (2011) and "Advances in Computational Biology" (2010) (Springer) Professor Tran has served on a number of editorial boards and has organized and chaired sessions for premier conferences such as the IEEE International Conference on Bioinformatics and Biomedicine Workshop.

Klappentext
Emerging Trends in Computational Biology, Bioinformatics, and Systems Biology discusses the latest in all aspects of computational biology, bioinformatics, and systems biology and the application of data-analytical and algorithms, mathematical modeling and simulation techniques. Part I: Computational Biology discusses the development and application of data-analytical and theoretical methods, mathematical modeling and computational simulation techniques. Part II: Bioinformatics: Databases, Data Mining and Pattern Discovery focuses on how to use methods for storing, retrieving, organizing and analyzing biological data which are fundamentally extensions of techniques used in computing. Part III: Systems Biology explains how to obtain, integrate and analyze complex data sets from multiple experimental sources using interdisciplinary tools while taking into consideration the evolving nature of the field. Part IV: Big Data and Data Analytics in Computational Biology and Informatics presents strategies and techniques using robust Big Data tools for dealing with the collection of data sets so large and complex that they are difficult to process using conventional database management systems or traditional data processing applications.

Zusammenfassung
"This is a valuable resource for students, clinicians, and researchers who wish to keep abreast of the emerging trends in computational biology, bioinformatics, and systems biology. Score: 76 - 3 Stars" --Doody's

Inhalt

CHAPTER 1 Supervised Learning with the Artificial Neural Networks Algorithm for Modeling Immune Cell Differentiation

CHAPTER 2 Accelerating Techniques for Particle Filter

Implementations on FPGA

CHAPTER 3 Biological Study on Pulsatile Flow of Herschel-Bulkley Fluid in Tapered Blood Vessels

CHAPTER 4 Hierarchical k-Means: A Hybrid Clustering Algorithm and its Application to Study Gene Expression in Lung Adenocarcinoma

CHAPTER 5 Molecular Classification of N-Aryloxazolidinone-5- carboxamides as Human Immunodeficiency Virus Protease Inhibitors

CHAPTER 6 Review of Recent Protein-Protein Interaction Techniques

CHAPTER 7 Genetic Regulatory Networks: Focus on Attractors Of Their Dynamics

CHAPTER 8 Biomechanical Evaluation for Bone Allograft in Treating the Femoral Head Necrosis: Thorough Debridement or Not?

CHAPTER 9 Diels-Alderase Catalyzing the Cyclization Step In the Biosynthesis of Spinosyn A: Reality or Fantasy?

CHAPTER 10 CLAST: Clustering Biological Sequences

CHAPTER 11 Computational Platform for Integration and Analysis of MicroRNA Annotation

CHAPTER 12 Feature Selection and Analysis of Gene Expression Data Using Low-Dimensional Linear Programming

CHAPTER 13 The Big ORF Theory: Algorithmic, Computational, and Approximation Approaches to Open Reading Frames in Short- and Medium-Length dsDNA Sequences

CHAPTER 14 Intentionally Linked Entities: A Detailed Look At a Database System for Health …