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This work pulls together all of the vital information about the most commonly used databases, analytical tools, and tables used in sequence analysis.
A hands-on introduction to Unix, Perl and other bioinformatics tools using relevant and interesting molecular biology problems.
This is the only book completely devoted to the popular BLAST (Basic Local Alignment Search Tool), and one that every biologist with an interest in sequence analysis should learn from.
Introductio to bioinformatics. Overview of structural bioinformatics. Database warehousing in bioinformatics. Modeling for bioinformatics. Pattern matching for motifs. Visualization and fractal analysis of biological sequences. Microarray data analysis.
Data mining provides a set of new techniques to integrate, synthesize, and analyze tdata, uncovering the hidden patterns that exist within. Traditionally, techniques such as kernel learning methods, pattern recognition, and data mining, have been the domain of researchers in areas such as artificial intelligence, but leveraging these tools, techniques, and concepts against your data asset to identify problems early, understand interactions that exist and highlight previously unrealized relationships through the combination of these different disciplines can provide significant value for the investigator and her organization.
Sequence analysis (SA) was developed to study social processes that unfold over time as sequences of events. It has gained increasing attention as the availability of longitudinal data made it possible to address sequence-oriented questions. This volume introduces the basics of SA to guide practitioners and support instructors through the basic workflow of sequence analysis. In addition to the basics, this book outlines recent advances and innovations in SA. The presentation of statistical, substantive, and theoretical foundations is enriched by examples to help the reader understand the repercussions of specific analytical choices. The extensive ancillary material supports self-learning based on real-world survey data and research questions from the field of life course research. Data and code and a variety of additional resources to enrich the use of this book are available on an accompanying website.
′This book provides an excellent reference guide to basic theoretical arguments, practical quantitative techniques and the methodologies that the majority of social science researchers are likely to require for postgraduate study and beyond′ - Environment and Planning ′The book provides researchers with guidance in, and examples of, both quantitative and qualitative modes of analysis, written by leading practitioners in the field. The editors give a persuasive account of the commonalities of purpose that exist across both modes, as well as demonstrating a keen awareness of the different things that each offers the practising researcher′ - Clive Seale, Brunel University ′With the appearance of this handbook, data analysts no longer have to consult dozens of disparate publications to carry out their work. The essential tools for an intelligent telling of the data story are offered here, in thirty chapters written by recognized experts. ′ - Michael Lewis-Beck, F Wendell Miller Distinguished Professor of Political Science, University of Iowa ′This is an excellent guide to current issues in the analysis of social science data. I recommend it to anyone who is looking for authoritative introductions to the state of the art. Each chapter offers a comprehensive review and an extensive bibliography and will be invaluable to researchers wanting to update themselves about modern developments′ - Professor Nigel Gilbert, Pro Vice-Chancellor and Professor of Sociology, University of Surrey This is a book that will rapidly be recognized as the bible for social researchers. It provides a first-class, reliable guide to the basic issues in data analysis, such as the construction of variables, the characterization of distributions and the notions of inference. Scholars and students can turn to it for teaching and applied needs with confidence. The book also seeks to enhance debate in the field by tackling more advanced topics such as models of change, causality, panel models and network analysis. Specialists will find much food for thought in these chapters. A distinctive feature of the book is the breadth of coverage. No other book provides a better one-stop survey of the field of data analysis. In 30 specially commissioned chapters the editors aim to encourage readers to develop an appreciation of the range of analytic options available, so they can choose a research problem and then develop a suitable approach to data analysis.
Probabilistic models are becoming increasingly important in analysing the huge amount of data being produced by large-scale DNA-sequencing efforts such as the Human Genome Project. For example, hidden Markov models are used for analysing biological sequences, linguistic-grammar-based probabilistic models for identifying RNA secondary structure, and probabilistic evolutionary models for inferring phylogenies of sequences from different organisms. This book gives a unified, up-to-date and self-contained account, with a Bayesian slant, of such methods, and more generally to probabilistic methods of sequence analysis. Written by an interdisciplinary team of authors, it aims to be accessible to molecular biologists, computer scientists, and mathematicians with no formal knowledge of the other fields, and at the same time present the state-of-the-art in this new and highly important field.
The pharmaceutical industry relies on numerous well-designed experiments involving high-throughput techniques and in silico approaches to analyze potential drug targets. These in silico methods are often predictive, yielding faster and less expensive analyses than traditional in vivo or in vitro procedures. In Silico Technologies in Drug Target Ide
This new third edition updates a best-selling encyclopedia. It includes about 56% more words than the 1,392-page second edition of 2003. The number of illustrations increased to almost 2,000 and their quality has improved by design and four colors. It includes approximately 1,800 current databases and web servers. This encyclopedia covers the basics and the latest in genomics, proteomics, genetic engineering, small RNAs, transcription factories, chromosome territories, stem cells, genetic networks, epigenetics, prions, hereditary diseases, and patents. Similar integrated information is not available in textbooks or on the Internet.