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Author :
Publisher :
ISBN 13 :
Total Pages : 896 pages
Book Rating : 4.3/5 (91 download)
Download or read book Journal of the American Statistical Association written by and published by . This book was released on 2009 with total page 896 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Ewart Carson
Publisher : Elsevier
ISBN 13 : 0080511902
Total Pages : 437 pages
Book Rating : 4.0/5 (85 download)
Download or read book Modelling Methodology for Physiology and Medicine written by Ewart Carson and published by Elsevier. This book was released on 2000-12-31 with total page 437 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modelling Methodology for Physiology and Medicine offers a unique approach and an unprecedented range of coverage of the state-of-the-art, advanced modelling methodology that is widely applicable to physiology and medicine. The book opens with a clear and integrated treatment of advanced methodology for developing mathematical models of physiology and medical systems. Readers are then shown how to apply this methodology beneficially to real-world problems in physiology and medicine, such as circulation and respiration. - Builds upon and enhances the readers existing knowledge of modelling methodology and practice - Editors are internationally renowned leaders in their respective fields
Author : Robert O'Neill
Publisher :
ISBN 13 : 9788301111502
Total Pages : 233 pages
Book Rating : 4.1/5 (115 download)
Download or read book Kernel three written by Robert O'Neill and published by . This book was released on 1993 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Alain Goriely
Publisher : Springer
ISBN 13 : 038787710X
Total Pages : 651 pages
Book Rating : 4.3/5 (878 download)
Download or read book The Mathematics and Mechanics of Biological Growth written by Alain Goriely and published by Springer. This book was released on 2017-05-29 with total page 651 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph presents a general mathematical theory for biological growth. It provides both a conceptual and a technical foundation for the understanding and analysis of problems arising in biology and physiology. The theory and methods are illustrated on a wide range of examples and applications. A process of extreme complexity, growth plays a fundamental role in many biological processes and is considered to be the hallmark of life itself. Its description has been one of the fundamental problems of life sciences, but until recently, it has not attracted much attention from mathematicians, physicists, and engineers. The author herein presents the first major technical monograph on the problem of growth since D’Arcy Wentworth Thompson’s 1917 book On Growth and Form. The emphasis of the book is on the proper mathematical formulation of growth kinematics and mechanics. Accordingly, the discussion proceeds in order of complexity and the book is divided into five parts. First, a general introduction on the problem of growth from a historical perspective is given. Then, basic concepts are introduced within the context of growth in filamentary structures. These ideas are then generalized to surfaces and membranes and eventually to the general case of volumetric growth. The book concludes with a discussion of open problems and outstanding challenges. Thoughtfully written and richly illustrated to be accessible to readers of varying interests and background, the text will appeal to life scientists, biophysicists, biomedical engineers, and applied mathematicians alike.
Author : Judea Pearl
Publisher : Basic Books
ISBN 13 : 0465097618
Total Pages : 432 pages
Book Rating : 4.4/5 (65 download)
Download or read book The Book of Why written by Judea Pearl and published by Basic Books. This book was released on 2018-05-15 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Turing Award-winning computer scientist and statistician shows how understanding causality has revolutionized science and will revolutionize artificial intelligence "Correlation is not causation." This mantra, chanted by scientists for more than a century, has led to a virtual prohibition on causal talk. Today, that taboo is dead. The causal revolution, instigated by Judea Pearl and his colleagues, has cut through a century of confusion and established causality -- the study of cause and effect -- on a firm scientific basis. His work explains how we can know easy things, like whether it was rain or a sprinkler that made a sidewalk wet; and how to answer hard questions, like whether a drug cured an illness. Pearl's work enables us to know not just whether one thing causes another: it lets us explore the world that is and the worlds that could have been. It shows us the essence of human thought and key to artificial intelligence. Anyone who wants to understand either needs The Book of Why.
Author : Benjamin M. Bolker
Publisher : Princeton University Press
ISBN 13 : 0691125228
Total Pages : 408 pages
Book Rating : 4.6/5 (911 download)
Download or read book Ecological Models and Data in R written by Benjamin M. Bolker and published by Princeton University Press. This book was released on 2008-07-21 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction and background; Exploratory data analysis and graphics; Deterministic functions for ecological modeling; Probability and stochastic distributions for ecological modeling; Stochatsic simulation and power analysis; Likelihood and all that; Optimization and all that; Likelihood examples; Standar statistics revisited; Modeling variance; Dynamic models.
Author : Mauricio A. Álvarez
Publisher : Foundations & Trends
ISBN 13 : 9781601985583
Total Pages : 86 pages
Book Rating : 4.9/5 (855 download)
Download or read book Kernels for Vector-Valued Functions written by Mauricio A. Álvarez and published by Foundations & Trends. This book was released on 2012 with total page 86 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph reviews different methods to design or learn valid kernel functions for multiple outputs, paying particular attention to the connection between probabilistic and regularization methods.
Author : Stephen P. Ellner
Publisher : Princeton University Press
ISBN 13 : 1400840961
Total Pages : 352 pages
Book Rating : 4.4/5 (8 download)
Download or read book Dynamic Models in Biology written by Stephen P. Ellner and published by Princeton University Press. This book was released on 2011-09-19 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: From controlling disease outbreaks to predicting heart attacks, dynamic models are increasingly crucial for understanding biological processes. Many universities are starting undergraduate programs in computational biology to introduce students to this rapidly growing field. In Dynamic Models in Biology, the first text on dynamic models specifically written for undergraduate students in the biological sciences, ecologist Stephen Ellner and mathematician John Guckenheimer teach students how to understand, build, and use dynamic models in biology. Developed from a course taught by Ellner and Guckenheimer at Cornell University, the book is organized around biological applications, with mathematics and computing developed through case studies at the molecular, cellular, and population levels. The authors cover both simple analytic models--the sort usually found in mathematical biology texts--and the complex computational models now used by both biologists and mathematicians. Linked to a Web site with computer-lab materials and exercises, Dynamic Models in Biology is a major new introduction to dynamic models for students in the biological sciences, mathematics, and engineering.
Author : Kim-Anh Do
Publisher : Cambridge University Press
ISBN 13 : 052186092X
Total Pages : 437 pages
Book Rating : 4.5/5 (218 download)
Download or read book Bayesian Inference for Gene Expression and Proteomics written by Kim-Anh Do and published by Cambridge University Press. This book was released on 2006-07-24 with total page 437 pages. Available in PDF, EPUB and Kindle. Book excerpt: Expert overviews of Bayesian methodology, tools and software for multi-platform high-throughput experimentation.
Author : Robert E. Kass
Publisher : Springer
ISBN 13 : 1461496020
Total Pages : 663 pages
Book Rating : 4.4/5 (614 download)
Download or read book Analysis of Neural Data written by Robert E. Kass and published by Springer. This book was released on 2014-07-08 with total page 663 pages. Available in PDF, EPUB and Kindle. Book excerpt: Continual improvements in data collection and processing have had a huge impact on brain research, producing data sets that are often large and complicated. By emphasizing a few fundamental principles, and a handful of ubiquitous techniques, Analysis of Neural Data provides a unified treatment of analytical methods that have become essential for contemporary researchers. Throughout the book ideas are illustrated with more than 100 examples drawn from the literature, ranging from electrophysiology, to neuroimaging, to behavior. By demonstrating the commonality among various statistical approaches the authors provide the crucial tools for gaining knowledge from diverse types of data. Aimed at experimentalists with only high-school level mathematics, as well as computationally-oriented neuroscientists who have limited familiarity with statistics, Analysis of Neural Data serves as both a self-contained introduction and a reference work.
Author : Keith J. Holyoak, Ph.D.
Publisher : Oxford University Press
ISBN 13 : 0199734682
Total Pages : 865 pages
Book Rating : 4.1/5 (997 download)
Download or read book The Oxford Handbook of Thinking and Reasoning written by Keith J. Holyoak, Ph.D. and published by Oxford University Press. This book was released on 2012-04-19 with total page 865 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Oxford Handbook of Thinking and Reasoning brings together the contributions of many of the leading researchers in thinking and reasoning to create the most comprehensive overview of research on thinking and reasoning that has ever been available. Each chapter includes a bit of historical perspective on the topic, and concludes with some thoughts about where the field seems to be heading.
Author : Grant Humphries
Publisher : Springer
ISBN 13 : 3319969781
Total Pages : 442 pages
Book Rating : 4.3/5 (199 download)
Download or read book Machine Learning for Ecology and Sustainable Natural Resource Management written by Grant Humphries and published by Springer. This book was released on 2018-11-05 with total page 442 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ecologists and natural resource managers are charged with making complex management decisions in the face of a rapidly changing environment resulting from climate change, energy development, urban sprawl, invasive species and globalization. Advances in Geographic Information System (GIS) technology, digitization, online data availability, historic legacy datasets, remote sensors and the ability to collect data on animal movements via satellite and GPS have given rise to large, highly complex datasets. These datasets could be utilized for making critical management decisions, but are often “messy” and difficult to interpret. Basic artificial intelligence algorithms (i.e., machine learning) are powerful tools that are shaping the world and must be taken advantage of in the life sciences. In ecology, machine learning algorithms are critical to helping resource managers synthesize information to better understand complex ecological systems. Machine Learning has a wide variety of powerful applications, with three general uses that are of particular interest to ecologists: (1) data exploration to gain system knowledge and generate new hypotheses, (2) predicting ecological patterns in space and time, and (3) pattern recognition for ecological sampling. Machine learning can be used to make predictive assessments even when relationships between variables are poorly understood. When traditional techniques fail to capture the relationship between variables, effective use of machine learning can unearth and capture previously unattainable insights into an ecosystem's complexity. Currently, many ecologists do not utilize machine learning as a part of the scientific process. This volume highlights how machine learning techniques can complement the traditional methodologies currently applied in this field.
Author : Nicholas T. Carnevale
Publisher : Cambridge University Press
ISBN 13 : 1139447831
Total Pages : 399 pages
Book Rating : 4.1/5 (394 download)
Download or read book The NEURON Book written by Nicholas T. Carnevale and published by Cambridge University Press. This book was released on 2006-01-12 with total page 399 pages. Available in PDF, EPUB and Kindle. Book excerpt: The authoritative reference on NEURON, the simulation environment for modeling biological neurons and neural networks that enjoys wide use in the experimental and computational neuroscience communities. This book shows how to use NEURON to construct and apply empirically based models. Written primarily for neuroscience investigators, teachers, and students, it assumes no previous knowledge of computer programming or numerical methods. Readers with a background in the physical sciences or mathematics, who have some knowledge about brain cells and circuits and are interested in computational modeling, will also find it helpful. The NEURON Book covers material that ranges from the inner workings of this program, to practical considerations involved in specifying the anatomical and biophysical properties that are to be represented in models. It uses a problem-solving approach, with many working examples that readers can try for themselves.
Author : Ming-Hui Chen
Publisher : CRC Press
ISBN 13 : 1466500794
Total Pages : 398 pages
Book Rating : 4.4/5 (665 download)
Download or read book Bayesian Phylogenetics written by Ming-Hui Chen and published by CRC Press. This book was released on 2014-05-27 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: Offering a rich diversity of models, Bayesian phylogenetics allows evolutionary biologists, systematists, ecologists, and epidemiologists to obtain answers to very detailed phylogenetic questions. Suitable for graduate-level researchers in statistics and biology, Bayesian Phylogenetics: Methods, Algorithms, and Applications presents a snapshot of current trends in Bayesian phylogenetic research. Encouraging interdisciplinary research, this book introduces state-of-the-art phylogenetics to the Bayesian statistical community and, likewise, presents state-of-the-art Bayesian statistics to the phylogenetics community. The book emphasizes model selection, reflecting recent interest in accurately estimating marginal likelihoods. It also discusses new approaches to improve mixing in Bayesian phylogenetic analyses in which the tree topology varies. In addition, the book covers divergence time estimation, biologically realistic models, and the burgeoning interface between phylogenetics and population genetics.
Author : Gina M. Cannarozzi
Publisher : Oxford University Press
ISBN 13 : 019960116X
Total Pages : 297 pages
Book Rating : 4.1/5 (996 download)
Download or read book Codon Evolution written by Gina M. Cannarozzi and published by Oxford University Press. This book was released on 2012-02-23 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: The second part of the book focuses on codon usage bias.
Author : Suvranu De
Publisher : Springer
ISBN 13 : 1447165993
Total Pages : 287 pages
Book Rating : 4.4/5 (471 download)
Download or read book Multiscale Modeling in Biomechanics and Mechanobiology written by Suvranu De and published by Springer. This book was released on 2014-10-10 with total page 287 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presenting a state-of-the-art overview of theoretical and computational models that link characteristic biomechanical phenomena, this book provides guidelines and examples for creating multiscale models in representative systems and organisms. It develops the reader's understanding of and intuition for multiscale phenomena in biomechanics and mechanobiology, and introduces a mathematical framework and computational techniques paramount to creating predictive multiscale models. Biomechanics involves the study of the interactions of physical forces with biological systems at all scales – including molecular, cellular, tissue and organ scales. The emerging field of mechanobiology focuses on the way that cells produce and respond to mechanical forces – bridging the science of mechanics with the disciplines of genetics and molecular biology. Linking disparate spatial and temporal scales using computational techniques is emerging as a key concept in investigating some of the complex problems underlying these disciplines. Providing an invaluable field manual for graduate students and researchers of theoretical and computational modelling in biology, this book is also intended for readers interested in biomedical engineering, applied mechanics and mathematical biology.
Author : Kenneth P. Burnham
Publisher : Springer Science & Business Media
ISBN 13 : 0387224564
Total Pages : 512 pages
Book Rating : 4.3/5 (872 download)
Download or read book Model Selection and Multimodel Inference written by Kenneth P. Burnham and published by Springer Science & Business Media. This book was released on 2007-05-28 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: A unique and comprehensive text on the philosophy of model-based data analysis and strategy for the analysis of empirical data. The book introduces information theoretic approaches and focuses critical attention on a priori modeling and the selection of a good approximating model that best represents the inference supported by the data. It contains several new approaches to estimating model selection uncertainty and incorporating selection uncertainty into estimates of precision. An array of examples is given to illustrate various technical issues. The text has been written for biologists and statisticians using models for making inferences from empirical data.
