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The Pacific Symposium on Biocomputing (PSB) 2011 is an international, multidisciplinary conference for the presentation and discussion of current research in the theory and application of computational methods in problems of biological significance. Presentations are rigorously peer reviewed and are published in an archival proceedings volume. ""PSB 2011"" will be held on January 3 - 7, 2011 in Kohala Coast, Hawaii. Tutorials and workshops will be offered prior to the start of the conference. PSB 2011 will bring together top researchers from the US, Asia Pacific, and around the world to exchan

Biology -- Computer simulation -- Congresses. --- Biology -- Mathematical models -- Congresses. --- Molecular biology -- Computer simulation -- Congresses. --- Molecular biology -- Mathematical models -- Congresses. --- Protein Interactions --- Metabolomics --- Biocomputing --- Computational Genetics --- Ontology --- Computational Proteomics --- Bioinformatics

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The Pacific Symposium on Biocomputing (PSB) 2013 is an international, multidisciplinary conference for the presentation and discussion of current research in the theory and application of computational methods in problems of biological significance. Presentations are rigorously peer reviewed and are published in an archival proceedings volume. PSB 2013 will be held on January 3 - 7, 2013 in Kohala Coast, Hawaii. Tutorials and workshops will be offered prior to the start of the conference.PSB 2013 will bring together top researchers from the US, the Asian Pacific nations, and around the world t

Biology -- Computer simulation -- Congresses. --- Biology -- Mathematical models -- Congresses. --- Biology -- Mathematical models. --- Biology --- Health & Biological Sciences --- Biology - General --- Protein Interactions --- Metabolomics --- Biocomputing --- Computational Genetics --- Ontology --- Computational Proteomics --- Bioinformatics

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Molecular biology --- Biología molecular --- Computer simulation --- Simulación por computadoras --- Information Technology --- Computer Science (Hardware & Networks) --- Molecular biology - Computer simulation - Congresses --- Biología molecular - Simulación por computadoras - Congresos

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Chemistry --- Materials science --- Biology --- Mathematical models --- Computer simulation --- Chemistry - Mathematical models - Congresses --- Materials science - Mathematical models - Congresses --- Biology - Mathematical models - Congresses --- Chemistry - Computer simulation - Congresses --- Materials science - Computer simulation - Congresses --- Biology - Computer simulation - Congresses

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An unprecedented wealth of data is being generated by genome sequencing projects and other experimental efforts to determine the structure and function of biological molecules. The demands and opportunities for interpreting these data are expanding rapidly. Bioinformatics is the development and application of computer methods for management, analysis, interpretation, and prediction, as well as for the design of experiments. Machine learning approaches (e.g., neural networks, hidden Markov models, and belief networks) are ideally suited for areas where there is a lot of data but little theory, which is the situation in molecular biology. The goal in machine learning is to extract useful information from a body of data by building good probabilistic models--and to automate the process as much as possible.In this book Pierre Baldi and Soren Brunak present the key machine learning approaches and apply them to the computational problems encountered in the analysis of biological data. The book is aimed both at biologists and biochemists who need to understand new data-driven algorithms and at those with a primary background in physics, mathematics, statistics, or computer science who need to know more about applications in molecular biology.This new second edition contains expanded coverage of probabilistic graphical models and of the applications of neural networks, as well as a new chapter on microarrays and gene expression. The entire text has been extensively revised.

Stochastic processes --- Molecular biology --- Artificial intelligence. Robotics. Simulation. Graphics --- Bioinformatics --- Neural networks (Computer science) --- Machine learning --- Markov processes --- Bio-informatique --- Biologie moléculaire --- Réseaux neuronaux (Informatique) --- Apprentissage automatique --- Markov, Processus de --- Computer simulation --- Mathematical models --- Modèles mathématiques --- Bioinformatics. --- Machine learning. --- Markov processes. --- Computer simulation. --- Mathematical models. --- Neural networks (Computer science). --- Biologie moléculaire --- Réseaux neuronaux (Informatique) --- Modèles mathématiques --- Molecular biology - Computer simulation. --- Molecular biology - Mathematical models.