Emerging Trends in Computational Biology, Bioinformatics, and Systems Biology discusses the latest developments in all aspects of computational biology, bioinformatics, and systems biology and the application of data-analytics and algorithms, mathematical modeling, and simu- lation techniques.
. Discusses the development and application of data-analytical and theoretical methods, mathematical modeling, and computational simulation techniques to the study of biological and behavioral systems, including applications in cancer research, computational intelligence and drug design, high-performance computing, and biology, as well as cloud and grid computing for the storage and access of big data sets.
. Presents a systematic approach for storing, retrieving, organizing, and analyzing biological data using software tools with applications to general principles of DNA/RNA structure, bioinformatics and applications, genomes, protein structure, and modeling and classification, as well as microarray analysis.
. Provides a systems biology perspective, including general guidelines and techniques for obtaining, integrating, and analyzing complex data sets from multiple experimental sources using computational tools and software. Topics covered include phenomics, genomics, epigenomics/epigenetics, metabolomics, cell cycle and checkpoint control, and systems biology and vaccination research.
. Explains how to effectively harness the power of Big Data tools when data sets are so large and complex that it is difficult to process them using conventional database management systems or traditional data processing applications.
- Discusses the development and application of data-analytical and theoretical methods, mathematical modeling and computational simulation techniques to the study of biological and behavioral systems.
- Presents a systematic approach for storing, retrieving, organizing and analyzing biological data using software tools with applications.
- Provides a systems biology perspective including general guidelines and techniques for obtaining, integrating and analyzing complex data sets from multiple experimental sources using computational tools and software.
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 Care Informatics
CHAPTER 15 Region Growing in Nonpictorial Data for Organ-Specific Toxicity Prediction
CHAPTER 16 Contribution of Noise Reduction Algorithms: Perception Versus Localization Simulation in the Case of Binaural Cochlear Implant (BCI) Coding
CHAPTER 17 Lowering the Fall Rate of the Elderly From Wheelchairs
CHAPTER 18 Occipital and Left Temporal EEG Correlates of Phenomenal Consciousness
CHAPTER 19 Chaotic Dynamical States in the Izhikevich Neuron Model
CHAPTER 20 Analogy, Mind, and Life
CHAPTER 21 Copy Number Networks to Guide Combinatorial Therapy of Cancer and Proliferative Disorders
CHAPTER 22 DNA Double-Strand Break-Based Nonmonotonic Logic
CHAPTER 23 An Updated Covariance Model for Rapid Annotation of Noncoding RNA
CHAPTER 24 SMIR: A Web Server to Predict Residues Involved in the Protein Folding Core
CHAPTER 25 Predicting Extinction of Biological Systems with Competition
CHAPTER 26 Methodologies for the Diagnosis of the Main Behavioral Syndromes for Parkinson's Disease with Bayesian Belief Networks
CHAPTER 27 Practical Considerations in Virtual Screening and Molecular Docking
CHAPTER 28 Knowledge Discovery in Proteomic Mass Spectrometry Data
CHAPTER 29 A Comparative Analysis of Read Mapping and Indel Calling Pipelines for Next-Generation Sequencing Data
CHAPTER 30 Two-Stage Evolutionary Quantification of In Vivo MRS Metabolites
CHAPTER 31 Keratoconus Disease and Three-Dimensional Simulation of the Cornea Throughout the Process of Cross-Linking Treatment
CHAPTER 32 Emerging Business Intelligence Framework for a Clinical Laboratory Through Big Data Analytics
CHAPTER 33 A Codon Frequency Obfuscation Heuristic for Raw Genomic Data Privacy
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).
Tran, Quoc Nam
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.