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""Computational biology drives discovery through its use of high-throughput informatics approaches. This book provides a road map of the current drug development process and how computational biology approaches play a critical role across the entire drug discovery pipeline. Through the use of previously unpublished, real-life case studies the impact of a range of computational approaches are discussed at various phases of the pipeline. Additionally, a focus section provides innovative visualisation approaches, from both the drug discovery process as well as from other fields that utilise large datasets, recognising the increasing use of such technology. Serving the needs of early career and more experienced scientists, this up-to-date reference provides an essential introduction to the process and background of drug discovery, highlighting how computational researchers can contribute to that pipeline"--Provided by publisher."

"The growth in the bioinformatics and computational biology fields over the last few years has been remarkable. The analysis of the datasets of next generation sequencing needs new algorithms and approaches from fields such as databases, statistics, Data mining, machine learning, optimization, computer science and artificial intelligence. Also systems biology has also been emerging as an alternative to the reductionist view that dominated biological research in the last decades. This book presents the results of the 6th International Conference on Practical Applications of Computational Biology & Bioinformatics held at University of Salamanca, Spain, 28-30th March, 2012 which brought together interdisciplinary scientists that have a strong background in the biological and computational sciences."

"Brazilian Symposium on Bioinformatics covers all aspects of bioinformatics and computational biology, including sequence analysis, motifs, and pattern matching, biological databases, data management, data integration, and data mining, biomedical text mining, structural, comparative, and functional genomics, personal genomics, protein structure, modeling, and simulation, gene identification, regulation and expression analysis, gene and protein interaction and networks, molecular docking, molecular evolution and phylogenetics, computational systems biology, computational proteomics, statistical analysis of molecular sequences, algorithms for problems in computational biology, applications in molecular biology, biochemistry, genetics, medicine, microbiology and associated subjects."

"This book constitutes the refereed proceedings of the 7th International Conference on Pattern Recognition in Bioinformatics, PRIB 2012, held in Tokyo, Japan, in November 2012. The 24 revised full papers presented were carefully reviewed and selected from 33 submissions. Their topics are widely ranging from fundamental techniques, sequence analysis to biological network analysis. The papers are organized in topical sections on generic methods, visualization, image analysis, and platforms, applications of pattern recognition techniques, protein structure and docking, complex data analysis, and sequence analysis."

"Do you have a biological question that could be readily answered by computational techniques, but little experience in programming? Do you want to learn more about the core techniques used in computational biology and bioinformatics? Written in an accessible style, this guide provides a foundation for both newcomers to computer programming and those interested in learning more about computational biology. The chapters guide the reader through: a complete beginners' course to programming in Python, with an introduction to computing jargon; descriptions of core bioinformatics methods with working Python examples; scientific computing techniques, including image analysis, statistics and machine learning. This book also functions as a language reference written in straightforward English, covering the most common Python language elements and a glossary of computing and biological terms. This title will teach undergraduates, postgraduates and professionals working in the life sciences how to program with Python, a powerful, flexible and easy-to-use language."