Download or read book Inference and Visualization of Periodic Sequences written by Ying Sun and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation is composed of four articles describing inference and visualization of periodic sequences. In the first article, a nonparametric method is proposed for estimating the period and values of a periodic sequence when the data are evenly spaced in time. The period is estimated by a "leave-out-one-cycle" version of cross-validation (CV) and complements the periodogram, a widely used tool for period estimation. The CV method is computationally simple and implicitly penalizes multiples of the smallest period, leading to a "virtually" consistent estimator. The second article is the multivariate extension, where we present a CV method of estimating the periods of multiple periodic sequences when data are observed at evenly spaced time points. The basic idea is to borrow information from other correlated sequences to improve estimation of the period of interest. We show that the asymptotic behavior of the bivariate CV is the same as the CV for one sequence, however, for finite samples, the better the periods of the other correlated sequences are estimated, the more substantial improvements can be obtained. The third article proposes an informative exploratory tool, the functional boxplot, for visualizing functional data, as well as its generalization, the enhanced functional boxplot. Based on the center outwards ordering induced by band depth for functional data, the descriptive statistics of a functional boxplot are: the envelope of the 50% central region, the median curve and the maximum non-outlying envelope. In addition, outliers can be detected by the 1.5 times the 50% central region empirical rule. The last article proposes a simulation-based method to adjust functional boxplots for correlations when visualizing functional and spatio-temporal data, as well as detecting outliers. We start by investigating the relationship between the spatiotemporal dependence and the 1.5 times the 50% central region empirical outlier detection rule. Then, we propose to simulate observations without outliers based on a robust estimator of the covariance function of the data. We select the constant factor in the functional boxplot to control the probability of correctly detecting no outliers. Finally, we apply the selected factor to the functional boxplot of the original data.

Download or read book Introduction to Bioinformatics in Microbiology written by Henrik Christensen and published by Springer Nature. This book was released on 2023-11-27 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: This updated and extended second edition of the textbook introduces the basic concepts of bioinformatics and enhances students' skills in the use of software and tools relevant to microbiology research. It discusses the most relevant methods for analysing data and teaches readers how to draw valid conclusions from the observations obtained. Free software and servers available on the Internet are presented in an updated version of 2023 and more advanced stand-alone software is proposed as a second option. In addition, new tools for microbial genome analysis and new flowcharts that complement the didactic elements have been added. Exercises and training questionnaires are included at the end of each chapter to facilitate learning. The book is aimed at Ph.D. students and advanced undergraduate students in microbiology, biotechnology, and (veterinary) medicine with little or basic knowledge of bioinformatics.

Download or read book Visualizing with Text written by Richard Brath and published by CRC Press. This book was released on 2020-11-01 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: Visualizing with Text uncovers the rich palette of text elements usable in visualizations from simple labels through to documents. Using a multidisciplinary research effort spanning across fields including visualization, typography, and cartography, it builds a solid foundation for the design space of text in visualization. The book illustrates many new kinds of visualizations, including microtext lines, skim formatting, and typographic sets that solve some of the shortcomings of well-known visualization techniques. Key features: More than 240 illustrations to aid inspiration of new visualizations Eight new approaches to data visualization leveraging text Quick reference guide for visualization with text Builds a solid foundation extending current visualization theory Bridges between visualization, typography, text analytics, and natural language processing The author website, including teaching exercises and interactive demos and code, can be found here. Designers, developers, and academics can use this book as a reference and inspiration for new approaches to visualization in any application that uses text.

Download or read book Diagrammatic Representation and Inference written by Philip T. Cox and published by Springer. This book was released on 2012-06-19 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 7th International Conference on Theory and Application of Diagrams, Diagrams 2012, held in Canaterbury, UK, in July 2012. The 16 long papers, 6 short papers and 21 poster abstracts presented were carefully reviewed and selected from 83 submissions. The papers are organized in keynotes, tutorial, workshops, graduate student symposium and topical sections on psychological and cognitive issues, diagram layout, diagrams and data analysis, Venn and Euler diagrams, reasoning with diagrams, investigating aesthetics, applications of diagrams.

Download or read book Elements of Causal Inference written by Jonas Peters and published by MIT Press. This book was released on 2017-11-29 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: A concise and self-contained introduction to causal inference, increasingly important in data science and machine learning. The mathematization of causality is a relatively recent development, and has become increasingly important in data science and machine learning. This book offers a self-contained and concise introduction to causal models and how to learn them from data. After explaining the need for causal models and discussing some of the principles underlying causal inference, the book teaches readers how to use causal models: how to compute intervention distributions, how to infer causal models from observational and interventional data, and how causal ideas could be exploited for classical machine learning problems. All of these topics are discussed first in terms of two variables and then in the more general multivariate case. The bivariate case turns out to be a particularly hard problem for causal learning because there are no conditional independences as used by classical methods for solving multivariate cases. The authors consider analyzing statistical asymmetries between cause and effect to be highly instructive, and they report on their decade of intensive research into this problem. The book is accessible to readers with a background in machine learning or statistics, and can be used in graduate courses or as a reference for researchers. The text includes code snippets that can be copied and pasted, exercises, and an appendix with a summary of the most important technical concepts.

Download or read book Sequence Evolution Function written by Eugene V. Koonin and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 482 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sequence - Evolution - Function is an introduction to the computational approaches that play a critical role in the emerging new branch of biology known as functional genomics. The book provides the reader with an understanding of the principles and approaches of functional genomics and of the potential and limitations of computational and experimental approaches to genome analysis. Sequence - Evolution - Function should help bridge the "digital divide" between biologists and computer scientists, allowing biologists to better grasp the peculiarities of the emerging field of Genome Biology and to learn how to benefit from the enormous amount of sequence data available in the public databases. The book is non-technical with respect to the computer methods for genome analysis and discusses these methods from the user's viewpoint, without addressing mathematical and algorithmic details. Prior practical familiarity with the basic methods for sequence analysis is a major advantage, but a reader without such experience will be able to use the book as an introduction to these methods. This book is perfect for introductory level courses in computational methods for comparative and functional genomics.

Download or read book Number Theory and Symmetry written by Michel Planat and published by MDPI. This book was released on 2021-01-20 with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt: According to Carl Friedrich Gauss (1777–1855), mathematics is the queen of the sciences—and number theory is the queen of mathematics. Numbers (integers, algebraic integers, transcendental numbers, p-adic numbers) and symmetries are investigated in the nine refereed papers of this MDPI issue. This book shows how symmetry pervades number theory. In particular, it highlights connections between symmetry and number theory, quantum computing and elementary particles (thanks to 3-manifolds), and other branches of mathematics (such as probability spaces) and revisits standard subjects (such as the Sieve procedure, primality tests, and Pascal’s triangle). The book should be of interest to all mathematicians, and physicists.

Download or read book Mastering Data Analysis with R written by Gergely Daroczi and published by Packt Publishing Ltd. This book was released on 2015-09-30 with total page 397 pages. Available in PDF, EPUB and Kindle. Book excerpt: Gain sharp insights into your data and solve real-world data science problems with R—from data munging to modeling and visualization About This Book Handle your data with precision and care for optimal business intelligence Restructure and transform your data to inform decision-making Packed with practical advice and tips to help you get to grips with data mining Who This Book Is For If you are a data scientist or R developer who wants to explore and optimize your use of R's advanced features and tools, this is the book for you. A basic knowledge of R is required, along with an understanding of database logic. What You Will Learn Connect to and load data from R's range of powerful databases Successfully fetch and parse structured and unstructured data Transform and restructure your data with efficient R packages Define and build complex statistical models with glm Develop and train machine learning algorithms Visualize social networks and graph data Deploy supervised and unsupervised classification algorithms Discover how to visualize spatial data with R In Detail R is an essential language for sharp and successful data analysis. Its numerous features and ease of use make it a powerful way of mining, managing, and interpreting large sets of data. In a world where understanding big data has become key, by mastering R you will be able to deal with your data effectively and efficiently. This book will give you the guidance you need to build and develop your knowledge and expertise. Bridging the gap between theory and practice, this book will help you to understand and use data for a competitive advantage. Beginning with taking you through essential data mining and management tasks such as munging, fetching, cleaning, and restructuring, the book then explores different model designs and the core components of effective analysis. You will then discover how to optimize your use of machine learning algorithms for classification and recommendation systems beside the traditional and more recent statistical methods. Style and approach Covering the essential tasks and skills within data science, Mastering Data Analysis provides you with solutions to the challenges of data science. Each section gives you a theoretical overview before demonstrating how to put the theory to work with real-world use cases and hands-on examples.

Download or read book Modeling Image Sequences with Particular Application to Fmri Data written by Neil J. Crellin and published by . This book was released on 1996 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Prediction of Protein Structures Functions and Interactions written by Janusz M. Bujnicki and published by John Wiley & Sons. This book was released on 2008-12-23 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: The growing flood of new experimental data generated by genome sequencing has provided an impetus for the development of automated methods for predicting the functions of proteins that have been deduced by sequence analysis and lack experimental characterization. Prediction of Protein Structures, Functions and Interactions presents a comprehensive overview of methods for prediction of protein structure or function, with the emphasis on their availability and possibilities for their combined use. Methods of modeling of individual proteins, prediction of their interactions, and docking of complexes are put in the context of predicting gene ontology (biological process, molecular function, and cellular component) and discussed in the light of their contribution to the emerging field of systems biology. Topics covered include: first steps of protein sequence analysis and structure prediction automated prediction of protein function from sequence template-based prediction of three-dimensional protein structures: fold-recognition and comparative modelling template-free prediction of three-dimensional protein structures quality assessment of protein models prediction of molecular interactions: from small ligands to large protein complexes macromolecular docking integrating prediction of structure, function, and interactions Prediction of Protein Structures, Functions and Interactions focuses on the methods that have performed well in CASPs, and which are constantly developed and maintained, and are freely available to academic researchers either as web servers or programs for local installation. It is an essential guide to the newest, best methods for prediction of protein structure and functions, for researchers and advanced students working in structural bioinformatics, protein chemistry, structural biology and drug discovery.

Download or read book Index Medicus written by and published by . This book was released on 2004 with total page 2324 pages. Available in PDF, EPUB and Kindle. Book excerpt: Vols. for 1963- include as pt. 2 of the Jan. issue: Medical subject headings.

Download or read book The American Mathematical Monthly written by and published by . This book was released on 1991 with total page 626 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Introduction to Applied Linear Algebra written by Stephen Boyd and published by Cambridge University Press. This book was released on 2018-06-07 with total page 477 pages. Available in PDF, EPUB and Kindle. Book excerpt: A groundbreaking introduction to vectors, matrices, and least squares for engineering applications, offering a wealth of practical examples.

Download or read book Probability Models for DNA Sequence Evolution written by Rick Durrett and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: "What underlying forces are responsible for the observed patterns of variability, given a collection of DNA sequences?" In approaching this question a number of probability models are introduced and anyalyzed.Throughout the book, the theory is developed in close connection with data from more than 60 experimental studies that illustrate the use of these results.

Download or read book Statistical Parametric Mapping The Analysis of Functional Brain Images written by William D. Penny and published by Elsevier. This book was released on 2011-04-28 with total page 689 pages. Available in PDF, EPUB and Kindle. Book excerpt: In an age where the amount of data collected from brain imaging is increasing constantly, it is of critical importance to analyse those data within an accepted framework to ensure proper integration and comparison of the information collected. This book describes the ideas and procedures that underlie the analysis of signals produced by the brain. The aim is to understand how the brain works, in terms of its functional architecture and dynamics. This book provides the background and methodology for the analysis of all types of brain imaging data, from functional magnetic resonance imaging to magnetoencephalography. Critically, Statistical Parametric Mapping provides a widely accepted conceptual framework which allows treatment of all these different modalities. This rests on an understanding of the brain's functional anatomy and the way that measured signals are caused experimentally. The book takes the reader from the basic concepts underlying the analysis of neuroimaging data to cutting edge approaches that would be difficult to find in any other source. Critically, the material is presented in an incremental way so that the reader can understand the precedents for each new development. This book will be particularly useful to neuroscientists engaged in any form of brain mapping; who have to contend with the real-world problems of data analysis and understanding the techniques they are using. It is primarily a scientific treatment and a didactic introduction to the analysis of brain imaging data. It can be used as both a textbook for students and scientists starting to use the techniques, as well as a reference for practicing neuroscientists. The book also serves as a companion to the software packages that have been developed for brain imaging data analysis. An essential reference and companion for users of the SPM software Provides a complete description of the concepts and procedures entailed by the analysis of brain images Offers full didactic treatment of the basic mathematics behind the analysis of brain imaging data Stands as a compendium of all the advances in neuroimaging data analysis over the past decade Adopts an easy to understand and incremental approach that takes the reader from basic statistics to state of the art approaches such as Variational Bayes Structured treatment of data analysis issues that links different modalities and models Includes a series of appendices and tutorial-style chapters that makes even the most sophisticated approaches accessible

Download or read book Interactive Data Visualization for the Web written by Scott Murray and published by "O'Reilly Media, Inc.". This book was released on 2013-03-11 with total page 269 pages. Available in PDF, EPUB and Kindle. Book excerpt: Author Scott Murray teaches you the fundamental concepts and methods of D3, a JavaScript library that lets you express data visually in a web browser

Download or read book Documenting Domestication written by Melinda A. Zeder and published by Univ of California Press. This book was released on 2006-06-20 with total page 377 pages. Available in PDF, EPUB and Kindle. Book excerpt: Agriculture is the lever with which humans transformed the earth over the last 10,000 years and created new forms of plant and animal species that have forever altered the face of the planet. In the last decade, significant technological and methodological advances in both molecular biology and archaeology have revolutionized the study of plant and animal domestication and are reshaping our understanding of the transition from foraging to farming, one of the major turning points in human history. This groundbreaking volume for the first time brings together leading archaeologists and biologists working on the domestication of both plants and animals to consider a wide variety of archaeological and genetic approaches to tracing the origin and dispersal of domesticates. It provides a comprehensive overview of the state of the art in this quickly changing field as well as reviews of recent findings on specific crop and livestock species in the Americas, Eurasia, and Africa. Offering a unique global perspective, it explores common challenges and potential avenues for future progress in documenting domestication.