Computational exome and genome analysis, Robinson, Peter N. Piro, Rosario Michael Jager, Marten
Автор: Okabe Название: Spatial Analysis Along Networks - Statistical and Computational Methods ISBN: 0470770813 ISBN-13(EAN): 9780470770818 Издательство: Wiley Рейтинг: Цена: 88650.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: * Presents a much-needed practical guide to statistical spatial analysis on a network, in a logical, user-friendly order. * Introduces the preliminary methods involved, before detailing the advanced, computational methods, enabling the readers a complete understanding of the advanced topics.
Автор: Richard C. Deonier; Simon Tavar?; Michael S. Water Название: Computational Genome Analysis ISBN: 1441931627 ISBN-13(EAN): 9781441931627 Издательство: Springer Рейтинг: Цена: 69830.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Computational Genome Analysis An Introduction presents the foundations of key problems in computational molecular biology and bioinformatics. It focuses on computational and statistical principles applied to genomes, and introduces the mathematics and statistics that are crucial for understanding these applications. The book is appropriate for a one-semester course for advanced undergraduate or beginning graduate students, and it can also introduce computational biology to computer scientists, mathematicians, or biologists who are extending their interests into this exciting field.
This book features:
Topics organized around biological problems, such as sequence alignment and assembly, DNA signals, analysis of gene expression, and human genetic variation
Presentation of fundamentals of probability, statistics, and algorithms
Implementation of computational methods with numerous examples based upon the R statistics package
Extensive descriptions and explanations to complement the analytical development
More than 100 illustrations and diagrams (some in color) to reinforce concepts and present key results from the primary literature
Exercises at the end of chapters
Michael S. Waterman is a University Professor, a USC Associates Chair in Natural Sciences, and Professor of Biological Sciences, Computer Science, and Mathematics at the University of Southern California. A member of the National Academy of Sciences and the American Academy of Arts and Sciences, Professor Waterman is Founding Editor and Co-Editor in Chief of the Journal of Computational Biology. His research has focused on computational analysis of molecular sequence data. His best-known work is the co-development of the local alignment Smith-Waterman algorithm, which has become the foundational tool for database search methods. His interests have also encompassed physical mapping, as exemplified by the Lander-Waterman formulas, and genome sequence assembly using an Eulerian path method.
Simon Tavare holds the George and Louise Kawamoto Chair in Biological Sciences and is a Professor of Biological Sciences, Mathematics, and Preventive Medicine at the University of Southern California. Professor Tavare's research lies at the interface between statistics and biology, specifically focusing on problems arising in molecular biology, human genetics, population genetics, molecular evolution, and bioinformatics. His statistical interests focus on stochastic computation. Among the applications are linkage disequilibrium mapping, stem cell evolution, and inference in the fossil record. Dr. Tavare is also a professor in the Department of Oncology at the University of Cambridge, England, where his group concentrates on cancer genomics.
Richard C. Deonier is Professor Emeritus in the Molecular and Computational Biology Section of the Department of Biological Sciences at the University of Southern California. Originally trained as a physical biochemist, His major research has been in areas of molecular genetics, with particular interests in physical methods for gene mapping, bacterial transposable elements, and conjugative plasmids. During 30 years of active teaching, he has taught chemistry, biology, and computational biology at both the undergraduate and graduate levels.
Название: Computational modeling and data analysis in covid-19 research ISBN: 036768036X ISBN-13(EAN): 9780367680367 Издательство: Taylor&Francis Рейтинг: Цена: 112290.00 T Наличие на складе: Невозможна поставка. Описание: This book covers recent research on the COVID-19 pandemic. It includes the analysis, implementation, usage, and proposed ideas and models with architecture to handle the COVID-19 outbreak. Using advanced technologies such as artificial intelligence (AI) and machine learning (ML), techniques for data analysis, this book will be helpful to mitigate exposure and ensure public health. We know prevention is better than cure, so by using several ML techniques, researchers can try to predict the disease in its early stage and develop more effective medications and treatments. Computational technologies in areas like AI, ML, Internet of Things (IoT), and drone technologies underlie a range of applications that can be developed and utilized for this purpose. Because in most cases there is no one solution to stop the spreading of pandemic diseases, and the integration of several tools and tactics are needed. Many successful applications of AI, ML, IoT, and drone technologies already exist, including systems that analyze past data to predict and conclude some useful information for controlling the spread of COVID-19 infections using minimum resources. The AI and ML approach can be helpful to design different models to give a predictive solution for mitigating infection and preventing larger outbreaks. This book:Examines the use of artificial intelligence (AI), machine learning (ML), Internet of Things (IoT), and drone technologies as a helpful predictive solution for controlling infection of COVID-19 Covers recent research related to the COVID-19 pandemic and includes the analysis, implementation, usage, and proposed ideas and models with architecture to handle a pandemic outbreak Examines the performance, implementation, architecture, and techniques of different analytical and statistical models related to COVID-19 Includes different case studies on COVID-19
Computational Analysis and Understanding of Natural Languages: Principles, Methods and Applications, Volume 38, the latest release in this monograph that provides a cohesive and integrated exposition of these advances and associated applications, includes new chapters on Linguistics: Core Concepts and Principles, Grammars, Open-Source Libraries, Application Frameworks, Workflow Systems, Mathematical Essentials, Probability, Inference and Prediction Methods, Random Processes, Bayesian Methods, Machine Learning, Artificial Neural Networks for Natural Language Processing, Information Retrieval, Language Core Tasks, Language Understanding Applications, and more.
The synergistic confluence of linguistics, statistics, big data, and high-performance computing is the underlying force for the recent and dramatic advances in analyzing and understanding natural languages, hence making this series all the more important.
Provides a thorough treatment of open-source libraries, application frameworks and workflow systems for natural language analysis and understanding
Presents new chapters on Linguistics: Core Concepts and Principles, Grammars, Open-Source Libraries, Application Frameworks, Workflow Systems, Mathematical Essentials, Probability, and more
Автор: Givens Название: Computational Statistics 2e ISBN: 0470533315 ISBN-13(EAN): 9780470533314 Издательство: Wiley Рейтинг: Цена: 117160.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Retaining the general organization and style of its predecessor, this new edition continues to serve as a comprehensive guide to modern and classical methods of statistical computing and computational statistics.
Автор: Reich Название: Probabilistic Forecasting and Bayesian Data Assimilation ISBN: 1107069394 ISBN-13(EAN): 9781107069398 Издательство: Cambridge Academ Рейтинг: Цена: 128830.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book focuses on the Bayesian approach to data assimilation, outlining the subject`s key ideas and concepts, and explaining how to implement specific data assimilation algorithms. It is an ideal introduction for graduate students in applied mathematics, computer science, engineering, geoscience and other emerging application areas.
Автор: Reich Название: Probabilistic Forecasting and Bayesian Data Assimilation ISBN: 1107663911 ISBN-13(EAN): 9781107663916 Издательство: Cambridge Academ Рейтинг: Цена: 49630.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book focuses on the Bayesian approach to data assimilation, outlining the subject`s key ideas and concepts, and explaining how to implement specific data assimilation algorithms. It is an ideal introduction for graduate students in applied mathematics, computer science, engineering, geoscience and other emerging application areas.
Автор: Cairns Paul Название: Doing Better Statistics in Human-Computer Interaction ISBN: 110848252X ISBN-13(EAN): 9781108482523 Издательство: Cambridge Academ Рейтинг: Цена: 102430.00 T Наличие на складе: Невозможна поставка. Описание: Written for human-computer interaction (HCI) researchers - whether undergraduates, professors, or UX professionals who need to analyse quantitative data - this book helps to improve readers` knowledge of the modern best practice in statistics and their understanding of how to do statistical analysis on their own data.
Автор: Nat?lia Bebiano Название: Applied and Computational Matrix Analysis ISBN: 3319499823 ISBN-13(EAN): 9783319499826 Издательство: Springer Рейтинг: Цена: 149060.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
This volume presents recent advances in the field of matrix analysis based on contributions at the MAT-TRIAD 2015 conference. Topics covered include interval linear algebra and computational complexity, Birkhoff polynomial basis, tensors, graphs, linear pencils, K-theory and statistic inference, showing the ubiquity of matrices in different mathematical areas.
With a particular focus on matrix and operator theory, statistical models and computation, the International Conference on Matrix Analysis and its Applications 2015, held in Coimbra, Portugal, was the sixth in a series of conferences.
Applied and Computational Matrix Analysis will appeal to graduate students and researchers in theoretical and applied mathematics, physics and engineering who are seeking an overview of recent problems and methods in matrix analysis.
Автор: Rebenko Alexei L Название: Theory of Interacting Quantum Fields ISBN: 3110250624 ISBN-13(EAN): 9783110250626 Издательство: Walter de Gruyter Рейтинг: Цена: 210690.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
This monograph is devoted to the systematic presentation of foundations of the quantum field theory. Unlike numerous monographs devoted to this topic, a wide range of problems covered in this book are accompanied by their sufficiently clear interpretations and applications. An important significant feature of this monograph is the desire of the author to present mathematical problems of the quantum field theory with regard to new methods of the constructive and Euclidean field theory that appeared in the last thirty years of the 20th century and are based on the rigorous mathematical apparatus of functional analysis, the theory of operators, and the theory of generalized functions.
The monograph is useful for students, post-graduate students, and young scientists who desire to understand not only the formality of construction of the quantum field theory but also its essence and connection with the classical mechanics, relativistic classical field theory, quantum mechanics, group theory, and the theory of path integral formalism.
Автор: M. Antonia Amaral Turkman, Carlos Daniel Paulino, Peter Muller Название: Computational Bayesian Statistics: An Introduction ISBN: 1108481035 ISBN-13(EAN): 9781108481038 Издательство: Cambridge Academ Рейтинг: Цена: 116160.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book explains the fundamental ideas of Bayesian analysis, with a focus on computational methods such as MCMC and available software such as R/R-INLA, OpenBUGS, JAGS, Stan, and BayesX. It is suitable as a textbook for a first graduate-level course and as a user`s guide for researchers and graduate students from beyond statistics.
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