Автор: Malley Название: Statistical Learning for Biomedical Data ISBN: 0521699096 ISBN-13(EAN): 9780521699099 Издательство: Cambridge Academ Рейтинг: Цена: 3642 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book is for anyone who has biomedical data and needs to identify variables that predict an outcome, for two-group outcomes such as tumor/not-tumor, survival/death, or response from treatment. Statistical learning machines are ideally suited to these types of prediction problems, especially if the variables being studied may not meet the assumptions of traditional techniques. Learning machines come from the world of probability and computer science but are not yet widely used in biomedical research. This introduction brings learning machine techniques to the biomedical world in an accessible way, explaining the underlying principles in nontechnical language and using extensive examples and figures. The authors connect these new methods to familiar techniques by showing how to use the learning machine models to generate smaller, more easily interpretable traditional models. Coverage includes single decision trees, multiple-tree techniques such as Random Forests™, neural nets, support vector machines, nearest neighbors and boosting.
Автор: Sung Название: Algorithms in Bioinformatics ISBN: 1420070339 ISBN-13(EAN): 9781420070330 Издательство: Taylor&Francis Рейтинг: Цена: 5537 р. Наличие на складе: Есть (1 шт.) Описание: This classroom-tested text provides an in-depth introduction to the algorithmic techniques applied in bioinformatics. For each topic, the author clearly details the biological motivation, precisely defines the corresponding computational problems, and includes detailed examples to illustrate each algorithm. The text covers basic molecular biology concepts, sequence similarity, the suffix tree, sequence databases, sequence and genome alignment, the phylogenetic tree, genome rearrangement, motif finding, the secondary structure of RNA, peptide sequencing, and population genetics. Supplementary material is provided on the author’s website and a solutions manual is available for qualifying instructors.
Описание: Uses the method of maximum likelihood to a large extent to ensure reasonable, and in some cases optimal procedures. This work treats the basic and important topics in multivariate statistics.
Автор: Nachtsheim;Neter;Kutner Название: Applied Linear Statistical Models with Student CD ISBN: 0071122214 ISBN-13(EAN): 9780071122214 Издательство: McGraw-Hill Рейтинг: Цена: 5642 р. Наличие на складе: Поставка под заказ.
Описание: "Applied Linear Statistical Models", 5e, is the long established leading authoritative text and reference on statistical modeling. For students in most any discipline where statistical analysis or interpretation is used, ALSM serves as the standard work. The text includes brief introductory and review material, and then proceeds through regression and modeling for the first half, and through ANOVA and Experimental Design in the second half. All topics are presented in a precise and clear style supported with solved examples, numbered formulae, graphic illustrations, and "Notes" to provide depth and statistical accuracy and precision. Applications used within the text and the hallmark problems, exercises, and projects are drawn from virtually all disciplines and fields providing motivation for students in virtually any college. The Fifth edition provides an increased use of computing and graphical analysis throughout, without sacrificing concepts or rigor. In general, the 5e uses larger data sets in examples and exercises, and where methods can be automated within software without loss of understanding, it is so done.
Автор: Tramontano Название: Introduction to Bioinformatics ISBN: 1584885696 ISBN-13(EAN): 9781584885696 Издательство: Taylor&Francis Рейтинг: Цена: 6164 р. Наличие на складе: Невозможна поставка.
Описание: From the elucidation and analysis of a genomic sequence to the prediction of a protein structure and the identification of the molecular function, Introduction to Bioinformatics describes the rationale and limitations of the bioinformatics methods and tools that can help solve biological problems. The author addresses the ways to store and retrieve biological data, decrypt information encoded by genomes, and detect and exploit the evolutionary and functional relationships among biological elements. The book also includes material on proteomics that is not found in any other basic bioinformatics textbook. It concludes with a discussion of the future of bioinformatics.
Автор: R K Pathria Название: Statistical Mechanics, ISBN: 0123821886 ISBN-13(EAN): 9780123821881 Издательство: Elsevier Science Рейтинг: Цена: 5549 р. 6166.00-10% Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Statistical Mechanics explores the physical properties of matter based on the dynamic behavior of its microscopic constituents. After a historical introduction, this book presents chapters about thermodynamics, ensemble theory, simple gases theory, Ideal Bose and Fermi systems, statistical mechanics of interacting systems, phase transitions, and computer simulations. This edition includes new topics such as BoseEinstein condensation and degenerate Fermi gas behavior in ultracold atomic gases and chemical equilibrium. It also explains the correlation functions and scattering; fluctuationdissipation theorem and the dynamical structure factor; phase equilibrium and the Clausius-Clapeyron equation; and exact solutions of one-dimensional fluid models and two-dimensional Ising model on a finite lattice. New topics can be found in the appendices, including finite-size scaling behavior of Bose-Einstein condensates, a summary of thermodynamic assemblies and associated statistical ensembles, and pseudorandom number generators. Other chapters are dedicated to two new topics, the thermodynamics of the early universe and the Monte Carlo and molecular dynamics simulations. This book is invaluable to students and practitioners interested in statistical mechanics and physics.
Автор: Huang, Kerson, Название: Introduction to statistical physics ISBN: 1420079026 ISBN-13(EAN): 9781420079029 Издательство: Taylor&Francis Рейтинг: Цена: 5955 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Written by a world-renowned theoretical physicist, this textbook familiarizes advanced undergraduate students with the different aspects of statistical physics. Along with many exercises, it includes a discussion of phase transition in thermodynamics. It also covers stochastic processes.
Автор: Ben Hui Liu and Leming M Shi Название: Statistical Genomics and Bioinformatics, Second Edition ISBN: 1584883286 ISBN-13(EAN): 9781584883289 Издательство: Taylor&Francis Рейтинг: Цена: 5224 р. Наличие на складе: Поставка под заказ.
Описание: Presents coverage of topics in statistical genomics. This work features several sections and chapters discussing areas such as sequence-based analysis, biochip data analysis, and generalized bioinformatics. It provides lists of statistical and linkage analysis software and their Web links, as well as SAS codes to help with difficult problems.
Автор: Mitra Название: Introduction to Machine Learning and Bioinformatics ISBN: 158488682X ISBN-13(EAN): 9781584886822 Издательство: Taylor&Francis Рейтинг: Цена: 7836 р. Наличие на складе: Невозможна поставка.
Описание: Examining the connections between these two increasingly intertwined areas, this text presents a unifying, thorough, and accessible introduction to the basic ideas and latest developments in machine learning and bioinformatics. It describes the major problems in bioinformatics and the concepts and algorithms of machine learning. The authors demonstrate the capabilities of key machine learning techniques, such as hidden Markov models and artificial neural networks, and apply state-of-the-art techniques to bioinformatics problems in structural biology, cancer treatment, and proteomics. They also include exercises at the end of some chapters and offer instructional materials on their website.
Автор: Ewens Название: Statistical Methods in Bioinformatics ISBN: 0387400826 ISBN-13(EAN): 9780387400822 Издательство: Springer Рейтинг: Цена: 10485 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Advances in computers and biotechnology have had a profound impact on biomedical research, and as a result complex data sets can be generated to address extremely complex biological questions. This book covers biological topics including sequence analysis, BLAST, microarray analysis, gene finding, and the analysis of evolutionary processes.
Описание: Statistical physics addresses the study and understanding of systems with many degrees of freedom. As such it has a rich and varied history, with applications to thermodynamics, magnetic phase transitions, and order/disorder transformations, to name just a few. However, the tools of statistical physics can be profitably used to investigate any system with a large number of components. Thus, recent years have seen these methods applied in many unexpected directions, three of which are the main focus of this volume. These applications have been remarkably successful and have enriched the financial, biological, and engineering literature. Although reported in the physics literature, the results tend to be scattered and the underlying unity of the field overlooked. This book provides a unique insight into the latest breakthroughs in a consistent manner, at a level accessible to undergraduates, yet with enough attention to the theory and computation to satisfy the professional researcher.
Автор: Dey Название: Bayesian Modeling in Bioinformatics ISBN: 1420070177 ISBN-13(EAN): 9781420070170 Издательство: Taylor&Francis Рейтинг: Цена: 8672 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume discusses the development and application of Bayesian statistical methods for the analysis of high-throughput bioinformatics data arising from problems in molecular and structural biology and disease-related medical research. It presents a broad overview of statistical inference, clustering, and classification problems in two main high-throughput platforms: microarray gene expression and phylogenic analysis. Illustrating concepts using real-world data, the book covers a variety of recently developed Bayesian techniques, along with applications in genome-wide studies, phylogenetics, breast cancer, expression genomics, and more.
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