This book constitutes the refereed proceedings of the Third International Symposium on Bioinformatics Research and Applications, ISBRA 2007, held in Atlanta, GA, USA in May 2007. The 55 revised full papers presented together with three invited talks cover a wide range of topics, including clustering and classification, gene expression analysis, gene networks, genome analysis, motif finding, pathways, protein structure prediction, protein domain interactions, phylogenetics, and software tools.

This volume constitutes the refereed proceedings of the 7th International Symposium on Bioinformatics Research and Applications, ISBRA 2011, held in Changsha, China, in May 2011. The 36 revised full papers presented together with 4 invited talks were carefully reviewed and selected from 92 submissions. Topics presented span all areas of bioinformatics and computational biology, including the development of experimental or commercial systems.

This book constitutes the refereed proceedings of the 11th International Symposium on Bioinformatics Research and Applications, ISBRA 2015, held in Norfolk, VA, USA, in June 2015. The 34 revised full papers and 14 two-page papers included in this volume were carefully reviewed and selected from 98 submissions. The papers cover a wide range of topics in bioinformatics and computational biology and their applications.

Nucleocapsid Proteins—Advances in Research and Application: 2012 Edition is a ScholarlyEditions™ eBook that delivers timely, authoritative, and comprehensive information about Nucleocapsid Proteins. The editors have built Nucleocapsid Proteins—Advances in Research and Application: 2012 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Nucleocapsid Proteins in this eBook to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Nucleocapsid Proteins—Advances in Research and Application: 2012 Edition has been produced by the world’s leading scientists, engineers, analysts, research institutions, and companies. All of the content is from peer-reviewed sources, and all of it is written, assembled, and edited by the editors at ScholarlyEditions™ and available exclusively from us. You now have a source you can cite with authority, confidence, and credibility. More information is available at http://www.ScholarlyEditions.com/.

The delivery and availability of information resources is a vital concern to professionals across multiple fields. This is particularly vital to data intensive professions, where easy accessibility to high-quality information is a crucial component of their research. Library and Information Services for Bioinformatics Education and Research is an authoritative reference source for the latest scholarly material on the role of libraries for the effective delivery of information resources to optimize the study of biological data. Highlighting innovative perspectives across a range of topics, such as user assessment, collection development, and information accessibility, this publication is ideally designed for professionals, managers, computer scientists, graduate students, and practitioners actively involved in the field of bioinformatics.

The field of SMART technologies is an interdependent discipline. It involves the latest burning issues ranging from machine learning, cloud computing, optimisations, modelling techniques, Internet of Things, data analytics, and Smart Grids among others, that are all new fields. It is an applied and multi-disciplinary subject with a focus on Specific, Measurable, Achievable, Realistic & Timely system operations combined with Machine intelligence & Real-Time computing. It is not possible for any one person to comprehensively cover all aspects relevant to SMART Computing in a limited-extent work. Therefore, these conference proceedings address various issues through the deliberations by distinguished Professors and researchers. The SMARTCOM 2020 proceedings contain tracks dedicated to different areas of smart technologies such as Smart System and Future Internet, Machine Intelligence and Data Science, Real-Time and VLSI Systems, Communication and Automation Systems. The proceedings can be used as an advanced reference for research and for courses in smart technologies taught at graduate level.

Research on the problem of clustering tends to be fragmented across the pattern recognition, database, data mining, and machine learning communities. Addressing this problem in a unified way, Data Clustering: Algorithms and Applications provides complete coverage of the entire area of clustering, from basic methods to more refined and complex data clustering approaches. It pays special attention to recent issues in graphs, social networks, and other domains. The book focuses on three primary aspects of data clustering: Methods, describing key techniques commonly used for clustering, such as feature selection, agglomerative clustering, partitional clustering, density-based clustering, probabilistic clustering, grid-based clustering, spectral clustering, and nonnegative matrix factorization Domains, covering methods used for different domains of data, such as categorical data, text data, multimedia data, graph data, biological data, stream data, uncertain data, time series clustering, high-dimensional clustering, and big data Variations and Insights, discussing important variations of the clustering process, such as semisupervised clustering, interactive clustering, multiview clustering, cluster ensembles, and cluster validation In this book, top researchers from around the world explore the characteristics of clustering problems in a variety of application areas. They also explain how to glean detailed insight from the clustering process—including how to verify the quality of the underlying clusters—through supervision, human intervention, or the automated generation of alternative clusters.

Developments in the areas of biology and bioinformatics are continuously evolving and creating a plethora of data that needs to be analyzed and decrypted. Since it can be difficult to decipher the multitudes of data within these areas, new computational techniques and tools are being employed to assist researchers in their findings. The Handbook of Research on Computational Intelligence Applications in Bioinformatics examines emergent research in handling real-world problems through the application of various computation technologies and techniques. Featuring theoretical concepts and best practices in the areas of computational intelligence, artificial intelligence, big data, and bio-inspired computing, this publication is a critical reference source for graduate students, professionals, academics, and researchers.

Bioinformatics in Agriculture: Next Generation Sequencing Era is a comprehensive volume presenting an integrated research and development approach to the practical application of genomics to improve agricultural crops. Exploring both the theoretical and applied aspects of computational biology, and focusing on the innovation processes, the book highlights the increased productivity of a translational approach. Presented in four sections and including insights from experts from around the world, the book includes: Section I: Bioinformatics and Next Generation Sequencing Technologies; Section II: Omics Application; Section III: Data mining and Markers Discovery; Section IV: Artificial Intelligence and Agribots. Bioinformatics in Agriculture: Next Generation Sequencing Era explores deep sequencing, NGS, genomic, transcriptome analysis and multiplexing, highlighting practices forreducing time, cost, and effort for the analysis of gene as they are pooled, and sequenced. Readers will gain real-world information on computational biology, genomics, applied data mining, machine learning, and artificial intelligence. This book serves as a complete package for advanced undergraduate students, researchers, and scientists with an interest in bioinformatics. - Discusses integral aspects of molecular biology and pivotal tool sfor molecular breeding - Enables breeders to design cost-effective and efficient breeding strategies - Provides examples ofinnovative genome-wide marker (SSR, SNP) discovery - Explores both the theoretical and practical aspects of computational biology with focus on innovation processes - Covers recent trends of bioinformatics and different tools and techniques