Statistical Bioinformatics. For Biomedical and Life Science Researchers

This book is the first to be dedicated to the bioinformatics of carbohydrates and glycoproteins. It provides an introduction to this emerging field of science both for the experimentalist working in glycobiology and glycomics, and also for the computer scientist looking for background information for the development of highly sophisticated algorithmic approaches. The book provides an overview of the state-of-the-art in the field, with reviews on databases, and the tools in use for analysis, interpretation, and prediction of the structures of complex carbohydrates, and demonstrates the value of bioinformatics for glycobiology. The availability of comprehensive databases and corresponding bioinformatics tools, to access and analyse the large amounts of experimental data relating to the structure of carbohydrates, will be a prerequisite for the success of the large-scale glycomics projects that aim to decipher new, so far unknown, biological functions of glycans. Efficient bioinformatics descriptions and tools can considerably enhance the efficiency of glycomics research, in terms of data quality, analysis and experimental costs. For a complete understanding of the molecular processes in which carbohydrates are involved, such as protein–carbohydrate interactions and the impact of glycosylation on protein function, knowledge of the 3D structure of the carbohydrate, the protein–carbohydrate complex, or the glycoprotein is often indispensable. This book provides a thorough introduction into methods used for conformational analysis of carbohydrates. Key features: Describes bioinformatic approaches to handle carbohydrate-active enzymes and glycosylation. Provides an overview on bioinformatics tools that facilitate analysis of carbohydrate structures. Gives introduction into molecular modelling of carbohydrate 3D structure and carbohydrates contained in the Protein Databank. Assumes only a basic knowledge of biology and bioinformatics.

The Most Comprehensive and Cutting-Edge Guide to Statistical Applications in Biomedical Research With the increasing use of biotechnology in medical research and the sophisticated advances in computing, it has become essential for practitioners in the biomedical sciences to be fully educated on the role statistics plays in ensuring the accurate analysis of research findings. Statistical Advances in the Biomedical Sciences explores the growing value of statistical knowledge in the management and comprehension of medical research and, more specifically, provides an accessible introduction to the contemporary methodologies used to understand complex problems in the four major areas of modern-day biomedical science: clinical trials, epidemiology, survival analysis, and bioinformatics. Composed of contributions from eminent researchers in the field, this volume discusses the application of statistical techniques to various aspects of modern medical research and illustrates how these methods ultimately prove to be an indispensable part of proper data collection and analysis. A structural uniformity is maintained across all chapters, each beginning with an introduction that discusses general concepts and the biomedical problem under focus and is followed by specific details on the associated methods, algorithms, and applications. In addition, each chapter provides a summary of the main ideas and offers a concluding remarks section that presents novel ideas, approaches, and challenges for future research. Complete with detailed references and insight on the future directions of biomedical research, Statistical Advances in the Biomedical Sciences provides vital statistical guidance to practitioners in the biomedical sciences while also introducing statisticians to new, multidisciplinary frontiers of application. This text is an excellent reference for graduate- and PhD-level courses in various areas of biostatistics and the medical sciences and also serves as a valuable tool for medical researchers, statisticians, public health professionals, and biostatisticians.

Features a solid foundation of mathematical and computational tools to formulate and solve real-world PDE problems across various fields With a step-by-step approach to solving partial differential equations (PDEs), Differential Equation Analysis in Biomedical Science and Engineering: Partial Differential Equation Applications with R successfully applies computational techniques for solving real-world PDE problems that are found in a variety of fields, including chemistry, physics, biology, and physiology. The book provides readers with the necessary knowledge to reproduce and extend the computed numerical solutions and is a valuable resource for dealing with a broad class of linear and nonlinear partial differential equations. The author’s primary focus is on models expressed as systems of PDEs, which generally result from including spatial effects so that the PDE dependent variables are functions of both space and time, unlike ordinary differential equation (ODE) systems that pertain to time only. As such, the book emphasizes details of the numerical algorithms and how the solutions were computed. Featuring computer-based mathematical models for solving real-world problems in the biological and biomedical sciences and engineering, the book also includes: R routines to facilitate the immediate use of computation for solving differential equation problems without having to first learn the basic concepts of numerical analysis and programming for PDEs Models as systems of PDEs and associated initial and boundary conditions with explanations of the associated chemistry, physics, biology, and physiology Numerical solutions of the presented model equations with a discussion of the important features of the solutions Aspects of general PDE computation through various biomedical science and engineering applications Differential Equation Analysis in Biomedical Science and Engineering: Partial Differential Equation Applications with R is an excellent reference for researchers, scientists, clinicians, medical researchers, engineers, statisticians, epidemiologists, and pharmacokineticists who are interested in both clinical applications and interpretation of experimental data with mathematical models in order to efficiently solve the associated differential equations. The book is also useful as a textbook for graduate-level courses in mathematics, biomedical science and engineering, biology, biophysics, biochemistry, medicine, and engineering.

The only single, up-to-date source for Grid issues in bioinformatics and biology Bioinformatics is fast emerging as an important discipline for academic research and industrial applications, creating a need for the use of Grid computing techniques for large-scale distributed applications. This book successfully presents Grid algorithms and their real-world applications, provides details on modern and ongoing research, and explores software frameworks that integrate bioinformatics and computational biology. Additional coverage includes: * Bio-ontology and data mining * Data visualization * DNA assembly, clustering, and mapping * Molecular evolution and phylogeny * Gene expression and micro-arrays * Molecular modeling and simulation * Sequence search and alignment * Protein structure prediction * Grid infrastructure, middleware, and tools for bio data Grid Computing for Bioinformatics and Computational Biology is an indispensable resource for professionals in several research and development communities including bioinformatics, computational biology, Grid computing, data mining, and more. It also serves as an ideal textbook for undergraduate- and graduate-level courses in bioinformatics and Grid computing.

This innovative book provides a completely fresh exploration of bioinformatics, investigating its complex interrelationship with biology and computer science. It approaches bioinformatics from a unique perspective, highlighting interdisciplinary gaps that often trap the unwary. The book considers how the need for biological databases drove the evolution of bioinformatics; it reviews bioinformatics basics (including database formats, data-types and current analysis methods), and examines key topics in computer science (including data-structures, identifiers and algorithms), reflecting on their use and abuse in bioinformatics. Bringing these disciplines together, this book is an essential read for those who wish to better understand the challenges for bioinformatics at the interface of biology and computer science, and how to bridge the gaps. It will be an invaluable resource for advanced undergraduate and postgraduate students, and for lecturers, researchers and professionals with an interest in this fascinating, fast-moving discipline and the knotty problems that surround it.

As individuals and companies realise the importance of their inventions, issues surrounding patent laws and practices are taking centre stage around the world. Patent Strategy introduces researchers to patent applications and patent portfolios. With minimum use of ‘legal jargon’ it provides the technical professional with the assistance and advice they require to understand the legal complexities that they may encounter before and during a patent application. It also discusses the responsibilities of the researcher after patent applications have been filed and the role the researcher can play in the maintenance of a global patent estate. This updated edition of the best selling book has been expanded to keep pace with modern day movements and addresses the global issue surrounding intellectual property. Including new information on areas such as software and biotechnology it shows the techniques that can be used by individuals and academic inventors to protect their work and is the ideal reference source. Bridges the gap between the legal system and scientific research and avoids legal jargon Details the reasons behind patents, their importance and relevance to all researchers and the strategy needed for filing for a patent Focuses on the strategy and reasons rather than just being a textbook of patent law Presents an overview of tools a researcher can use while working with a patent attorney or agent Adopts a readable style that explains the basics right up to developing a strategy Essential reading for all those who wish to keep pace and protect their work Reviews from previous edition: «…I can recommend it for technology managing types. Does a nice job of explaining many aspects of the patent system and patent strategies with a minimum of jargon and case citations…» —Internet Patent News «…provides an enlightened approach to a complex subject. It is relatively easy to read and follow…» – Polymers Paint and Colour Journal «This handy book provides the researcher with useful guidance on how to maximize the benefit of their inventiveness to themselves and their organization». —Journal of Chemical Technology and Biotechnology

“… this book was written from start to finish by one extremely dedicated and erudite individual. The author has done an excellent job of covering the many topics that fall under the umbrella of computational biology for vaccine design, demonstrating an admirable command of subject matter in fields as disparate as object-oriented databases and regulation of T cell response. Simply put, it has just the right breadth and depth, and it reads well. In fact, readability is one of its virtues—making the book enticing and useful, all at once…” Human Vaccines, 2010 «… This book has several strong points. Although there are many textbooks that deal with vaccinology, few attempts have been made to bring together descriptions of vaccines in history, basic bioinformatics, various computational solutions and challenges in vaccinology, detailed experimental methodologies, and cutting-edge technologies… This book may well serve as a first line of reference for all biologists and computer scientists…» –Virology Journal, 2009 Vaccines have probably saved more lives and reduced suffering in a greater number of people than any other medical intervention in human history, succeeding in eradicating smallpox and significantly reducing the mortality and incidence of other diseases. However, with the emergence of diseases such as SARS and the threat of biological warfare, vaccination has once again become a topic of major interest in public health. Vaccinology now has at its disposal an array of post-genomic approaches of great power. None has a more persuasive potential impact than the application of computational informatics to vaccine discovery; the recent expansion in genome data and the parallel increase in cheap computing power have placed the bioinformatics exploration of pathogen genomes centre stage for vaccine researchers. This is the first book to address the area of bioinformatics as applied to rational vaccine design, discussing the ways in which bioinformatics can contribute to improved vaccine development by introducing the subject of harnessing the mathematical and computing power inherent in bioinformatics to the study of vaccinology putting it into a historical and societal context, and exploring the scope of its methods and applications. Bioinformatics for Vaccinology is a one-stop introduction to computational vaccinology. It will be of particular interest to bioinformaticians with an interest in immunology, as well as to immunologists, and other biologists who need to understand how advances in theoretical and computational immunobiology can transform their working practices.

An in-depth look at the latest research, methods, and applications in the field of protein bioinformatics This book presents the latest developments in protein bioinformatics, introducing for the first time cutting-edge research results alongside novel algorithmic and AI methods for the analysis of protein data. In one complete, self-contained volume, Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics addresses key challenges facing both computer scientists and biologists, arming readers with tools and techniques for analyzing and interpreting protein data and solving a variety of biological problems. Featuring a collection of authoritative articles by leaders in the field, this work focuses on the analysis of protein sequences, structures, and interaction networks using both traditional algorithms and AI methods. It also examines, in great detail, data preparation, simulation, experiments, evaluation methods, and applications. Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics: Highlights protein analysis applications such as protein-related drug activity comparison Incorporates salient case studies illustrating how to apply the methods outlined in the book Tackles the complex relationship between proteins from a systems biology point of view Relates the topic to other emerging technologies such as data mining and visualization Includes many tables and illustrations demonstrating concepts and performance figures Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics is an essential reference for bioinformatics specialists in research and industry, and for anyone wishing to better understand the rich field of protein bioinformatics.

Nanotechnology for Biomedical Imaging and Diagnostics: From Nanoparticle Design to Clinical Applications reflects upon the increasing role of nanomaterials in biological and medical imaging, presenting a thorough description of current research as well as future directions. With contributions from experts in nanotechnology and imaging from academia, industry, and healthcare, this book provides a comprehensive coverage of the field, ranging from the architectural design of nanomaterials to their broad imaging applications in medicine. Grouped into three sections, the book: Elucidates all major aspects of nanotechnology and bioimaging Provides comprehensive coverage of the field, ranging from the architectural design of nanomaterials to their broad imaging applications in medicine Written by well-recognized experts in academia, industry, and healthcare, will be an excellence source of reference With a multidisciplinary approach and a balance of research and diagnostic topics, this book will appeal to students, scientiests, and healthcare professionals alike

In the current era of complete genome sequencing, Bioinformatics and Molecular Evolution provides an up-to-date and comprehensive introduction to bioinformatics in the context of evolutionary biology. This accessible text: provides a thorough examination of sequence analysis, biological databases, pattern recognition, and applications to genomics, microarrays, and proteomics emphasizes the theoretical and statistical methods used in bioinformatics programs in a way that is accessible to biological science students places bioinformatics in the context of evolutionary biology, including population genetics, molecular evolution, molecular phylogenetics, and their applications features end-of-chapter problems and self-tests to help students synthesize the materials and apply their understanding is accompanied by a dedicated website – www.blackwellpublishing.com/higgs – containing downloadable sequences, links to web resources, answers to self-test questions, and all artwork in downloadable format (artwork also available to instructors on CD-ROM). This important textbook will equip readers with a thorough understanding of the quantitative methods used in the analysis of molecular evolution, and will be essential reading for advanced undergraduates, graduates, and researchers in molecular biology, genetics, genomics, computational biology, and bioinformatics courses.