Molecular Bioinformatics

Bioinformatics for Beginners: Genes, Genomes, Molecular Evolution, Databases and Analytical Tools provides a coherent and friendly treatment of bioinformatics for any student or scientist within biology who has not routinely performed bioinformatic analysis. The book discusses the relevant principles needed to understand the theoretical underpinnings of bioinformatic analysis and demonstrates, with examples, targeted analysis using freely available web-based software and publicly available databases. Eschewing non-essential information, the work focuses on principles and hands-on analysis, also pointing to further study options. Avoids non-essential coverage, yet fully describes the field for beginners Explains the molecular basis of evolution to place bioinformatic analysis in biological context Provides useful links to the vast resource of publicly available bioinformatic databases and analysis tools Contains over 100 figures that aid in concept discovery and illustration

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.

Molecular bioinformatics as a newly emerging interdisciplinary research area, comprises the development and application of algorithms for the purpose of analysis, interpretation and prediction of data and for the design of experiments in the biosciences. The heterogeneous collection of original research presented in this volume illustrates the use of the wide and diverse range of algorithmic techniques. The application of algorithms from computer sciences, including artificial intelligence, machine learning, genetic programming, evolutionary algorithms and neural nets to molecular biologyespecially DNA and RNA sequence analysis and protein engineering is broadly examined. Both algorithmic and biological background problems are explained for the benefit of an interdisciplinary audience.

An introductory text that emphasizes the underlying algorithmic ideas that are driving advances in bioinformatics. This introductory text offers a clear exposition of the algorithmic principles driving advances in bioinformatics. Accessible to students in both biology and computer science, it strikes a unique balance between rigorous mathematics and practical techniques, emphasizing the ideas underlying algorithms rather than offering a collection of apparently unrelated problems. The book introduces biological and algorithmic ideas together, linking issues in computer science to biology and thus capturing the interest of students in both subjects. It demonstrates that relatively few design techniques can be used to solve a large number of practical problems in biology, and presents this material intuitively. An Introduction to Bioinformatics Algorithms is one of the first books on bioinformatics that can be used by students at an undergraduate level. It includes a dual table of contents, organized by algorithmic idea and biological idea; discussions of biologically relevant problems, including a detailed problem formulation and one or more solutions for each; and brief biographical sketches of leading figures in the field. These interesting vignettes offer students a glimpse of the inspirations and motivations for real work in bioinformatics, making the concepts presented in the text more concrete and the techniques more approachable.PowerPoint presentations, practical bioinformatics problems, sample code, diagrams, demonstrations, and other materials can be found at the Author's website.

Computers have become an essential component of modern biology. They help to manage the vast and increasing amount of biological data and continue to play an integral role in the discovery of new biological relationships. This in silico approach to biology has helped to reshape the modern biological sciences. With the biological revolution now among us, it is imperative that each scientist develop and hone today’s bioinformatics skills, if only at a rudimentary level. Bioinformatics Methods and Protocols was conceived as part of the Methods in Molecular Biology series to meet this challenge and to provide the experienced user with useful tips and an up-to-date overview of current developments. It builds upon the foundation that was provided in the two-volume set published in 1994 entitled Computer Analysis of Sequence Data. We divided Bioinformatics Methods and Protocols into five parts, including a thorough survey of the basic sequence analysis software packages that are available at most institutions, as well as the design and implemen- tion of an essential introductory Bioinformatics course. In addition, we included sections describing specialized noncommercial software, databases, and other resources available as part of the World Wide Web and a stimul- ing discussion of some of the computational challenges biologists now face and likely future solutions.

With the rapid development of proteomic technologies in the life sciences and in clinical applications, many bioinformatics methodologies, databases, and software tools have been developed to support comparative proteomics study. In Bioinformatics for Comparative Proteomics, experts in the field highlight the current status, challenges, open problems, and future trends for developing bioinformatics tools and resources for comparative proteomics research in order to deliver a definitive reference providing both the breadth and depth needed on the subject. Structured in three major sections, this detailed volume covers basic bioinformatics frameworks relating to comparative proteomics, bioinformatics databases and tools for proteomics data analysis, and integrated bioinformatics systems and approaches for studying comparative proteomics in the systems biology context. Written for the highly successful Methods in Molecular BiologyTM series, the contributions in this book provide the meticulous, step-by-step description and implementation advice that is crucial for getting optimal results in the lab. Comprehensive and easy-to-use, Bioinformatics for Comparative Proteomics serves all readers who wish to learn about state-of-the-art bioinformatics databases and tools, novel computational methods and future trends in proteomics data analysis, and comparative proteomics in systems biology.

This textbook presents mathematical models in bioinformatics and describes biological problems that inspire the computer science tools used to manage the enormous data sets involved. The first part of the book covers mathematical and computational methods, with practical applications presented in the second part. The mathematical presentation avoids unnecessary formalism, while remaining clear and precise. The book closes with a thorough bibliography, reaching from classic research results to very recent findings. This volume is suited for a senior undergraduate or graduate course on bioinformatics, with a strong focus on mathematical and computer science background.