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EBookClubs

Read Books & Download eBooks Full Online

Book Advanced Studies in Behaviormetrics and Data Science

Download or read book Advanced Studies in Behaviormetrics and Data Science written by Tadashi Imaizumi and published by Springer Nature. This book was released on 2020-04-17 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the latest developments in behaviormetrics and data science, covering a wide range of topics in data analysis and related areas of data science, including analysis of complex data, analysis of qualitative data, methods for high-dimensional data, dimensionality reduction, visualization of such data, multivariate statistical methods, analysis of asymmetric relational data, and various applications to real data. In addition to theoretical and methodological results, it also shows how to apply the proposed methods to a variety of problems, for example in consumer behavior, decision making, marketing data, and social network structures. Moreover, it discuses methodological aspects and applications in a wide range of areas, such as behaviormetrics; behavioral science; psychology; and marketing, management and social sciences. Combining methodological advances with real-world applications collected from a variety of research fields, the book is a valuable resource for researchers and practitioners, as well as for applied statisticians and data analysts.

Book Knowledge Exploration in Life Science Informatics

Download or read book Knowledge Exploration in Life Science Informatics written by Jesús A. López and published by Springer. This book was released on 2005-01-27 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume of the Springer Lecture Notes in Computer Science series contains the contributions presented at the International Symposium on Knowledge Exploration in Life Science Informatics (KELSI 2004) held in Milan, Italy, 25-26 November 2004. The two main objectives of the symposium were: • To explore the symbiosis between information and knowledge technologies and v- ious life science disciplines, such as biochemistry, biology, neuroscience, medical research, social sciences, and so on. • To investigate the synergy among different life science informatics areas, including cheminformatics,bioinformatics,neuroinformatics,medical informatics,systems - ology, socionics, and others. Modern life sciences investigate phenomena and systems at the level of molecules, cells, tissues, organisms, and populations. Typical areas of interest include natural e- lution, development,disease, behavior,cognition,and consciousness.This quest is g- eratinganoverwhelmingandfast-growingamountofdata,information,andknowledge, re?ecting living systems at different levels of organization. Future progress of the life sciences will depend on effective and ef?cient management, sharing, and exploitation of these resources by computational means.

Book Statistics and Informatics in Molecular Cancer Research

Download or read book Statistics and Informatics in Molecular Cancer Research written by Carsten Wiuf and published by OUP Oxford. This book was released on 2009-06-18 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: Molecular understanding of cancer and cancer progression is at the forefront of many research programs today. High-throughput array technologies and other modern molecular techniques produce a wealth of molecular data about the structure, and function of cells, tissues, and organisms. Correctly analyzed and interpreted these data hold the promise of bringing new markers for prognostic and diagnostic use, for new treatment schemes, and of gaining new biological insight into the evolution of cancer and its molecular, pathological, and clinical consequences. Aimed at graduates and researchers, this book discusses novel advances in informatics and statistics in molecular cancer research. Through eight chapters from carefully chosen experts it brings the reader up to date with specific topics in cancer research, how the topics give rise to development of new informatics and statistics tools, and how the tools can be applied. The focus of the book is to give the reader an understanding of key concepts and tools, rather than focusing on technical issues. A main theme is the extensive use of array technologies in modern cancer research - gene expression and exon arrays, SNP and copy number arrays, and methylation arrays - to derive quantitative and qualitative statements about cancer, its progression and aetiology, and to understand how these technologies on one hand allow us learn about cancer tissue as a complex system and on the other hand allow us to pinpoint key genes and events as crucial for the development of the disease.

Book Exploratory Data Analysis with MATLAB

Download or read book Exploratory Data Analysis with MATLAB written by Wendy L. Martinez and published by CRC Press. This book was released on 2017-08-07 with total page 589 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the Second Edition: "The authors present an intuitive and easy-to-read book. ... accompanied by many examples, proposed exercises, good references, and comprehensive appendices that initiate the reader unfamiliar with MATLAB." —Adolfo Alvarez Pinto, International Statistical Review "Practitioners of EDA who use MATLAB will want a copy of this book. ... The authors have done a great service by bringing together so many EDA routines, but their main accomplishment in this dynamic text is providing the understanding and tools to do EDA. —David A Huckaby, MAA Reviews Exploratory Data Analysis (EDA) is an important part of the data analysis process. The methods presented in this text are ones that should be in the toolkit of every data scientist. As computational sophistication has increased and data sets have grown in size and complexity, EDA has become an even more important process for visualizing and summarizing data before making assumptions to generate hypotheses and models. Exploratory Data Analysis with MATLAB, Third Edition presents EDA methods from a computational perspective and uses numerous examples and applications to show how the methods are used in practice. The authors use MATLAB code, pseudo-code, and algorithm descriptions to illustrate the concepts. The MATLAB code for examples, data sets, and the EDA Toolbox are available for download on the book’s website. New to the Third Edition Random projections and estimating local intrinsic dimensionality Deep learning autoencoders and stochastic neighbor embedding Minimum spanning tree and additional cluster validity indices Kernel density estimation Plots for visualizing data distributions, such as beanplots and violin plots A chapter on visualizing categorical data

Book Molecular Data Analysis Using R

Download or read book Molecular Data Analysis Using R written by Csaba Ortutay and published by John Wiley & Sons. This book was released on 2017-02-06 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses the difficulties experienced by wet lab researchers with the statistical analysis of molecular biology related data. The authors explain how to use R and Bioconductor for the analysis of experimental data in the field of molecular biology. The content is based upon two university courses for bioinformatics and experimental biology students (Biological Data Analysis with R and High-throughput Data Analysis with R). The material is divided into chapters based upon the experimental methods used in the laboratories. Key features include: • Broad appeal--the authors target their material to researchers in several levels, ensuring that the basics are always covered. • First book to explain how to use R and Bioconductor for the analysis of several types of experimental data in the field of molecular biology. • Focuses on R and Bioconductor, which are widely used for data analysis. One great benefit of R and Bioconductor is that there is a vast user community and very active discussion in place, in addition to the practice of sharing codes. Further, R is the platform for implementing new analysis approaches, therefore novel methods are available early for R users.

Book Modern Multivariate Statistical Techniques

Download or read book Modern Multivariate Statistical Techniques written by Alan J. Izenman and published by Springer Science & Business Media. This book was released on 2009-03-02 with total page 757 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first book on multivariate analysis to look at large data sets which describes the state of the art in analyzing such data. Material such as database management systems is included that has never appeared in statistics books before.

Book Introduction to Statistical Data Analysis for the Life Sciences

Download or read book Introduction to Statistical Data Analysis for the Life Sciences written by Claus Thorn Ekstrom and published by CRC Press. This book was released on 2014-11-06 with total page 521 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Hands-On Approach to Teaching Introductory StatisticsExpanded with over 100 more pages, Introduction to Statistical Data Analysis for the Life Sciences, Second Edition presents the right balance of data examples, statistical theory, and computing to teach introductory statistics to students in the life sciences. This popular textbook covers the m

Book Statistics at the Bench

Download or read book Statistics at the Bench written by Martina Bremer and published by . This book was released on 2010 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: This handbook is a convenient bench companion for biologists, designed as a handy reference guide for elementary and intermediate statistical analyses. Statistical methods most frequently used in publications and reports, as well as guidelines for the interpretation of results, are explained using simple examples with complete instructions for Excel.

Book Bio Medical Informatics  One Discipline

Download or read book Bio Medical Informatics One Discipline written by Isaac S. Kohane and published by . This book was released on 2002 with total page 1312 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Modern Data Science with R

Download or read book Modern Data Science with R written by Benjamin S. Baumer and published by CRC Press. This book was released on 2021-03-31 with total page 830 pages. Available in PDF, EPUB and Kindle. Book excerpt: From a review of the first edition: "Modern Data Science with R... is rich with examples and is guided by a strong narrative voice. What’s more, it presents an organizing framework that makes a convincing argument that data science is a course distinct from applied statistics" (The American Statistician). Modern Data Science with R is a comprehensive data science textbook for undergraduates that incorporates statistical and computational thinking to solve real-world data problems. Rather than focus exclusively on case studies or programming syntax, this book illustrates how statistical programming in the state-of-the-art R/RStudio computing environment can be leveraged to extract meaningful information from a variety of data in the service of addressing compelling questions. The second edition is updated to reflect the growing influence of the tidyverse set of packages. All code in the book has been revised and styled to be more readable and easier to understand. New functionality from packages like sf, purrr, tidymodels, and tidytext is now integrated into the text. All chapters have been revised, and several have been split, re-organized, or re-imagined to meet the shifting landscape of best practice.

Book A First Course in Stochastic Models

Download or read book A First Course in Stochastic Models written by Henk C. Tijms and published by John Wiley and Sons. This book was released on 2003-07-22 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field of applied probability has changed profoundly in the past twenty years. The development of computational methods has greatly contributed to a better understanding of the theory. A First Course in Stochastic Models provides a self-contained introduction to the theory and applications of stochastic models. Emphasis is placed on establishing the theoretical foundations of the subject, thereby providing a framework in which the applications can be understood. Without this solid basis in theory no applications can be solved. Provides an introduction to the use of stochastic models through an integrated presentation of theory, algorithms and applications. Incorporates recent developments in computational probability. Includes a wide range of examples that illustrate the models and make the methods of solution clear. Features an abundance of motivating exercises that help the student learn how to apply the theory. Accessible to anyone with a basic knowledge of probability. A First Course in Stochastic Models is suitable for senior undergraduate and graduate students from computer science, engineering, statistics, operations resear ch, and any other discipline where stochastic modelling takes place. It stands out amongst other textbooks on the subject because of its integrated presentation of theory, algorithms and applications.

Book Analysis of Multivariate and High Dimensional Data

Download or read book Analysis of Multivariate and High Dimensional Data written by Inge Koch and published by Cambridge University Press. This book was released on 2014 with total page 531 pages. Available in PDF, EPUB and Kindle. Book excerpt: This modern approach integrates classical and contemporary methods, fusing theory and practice and bridging the gap to statistical learning.

Book Genomic Signal Processing

    Book Details:
  • Author : Ilya Shmulevich
  • Publisher : Princeton University Press
  • Release : 2014-09-08
  • ISBN : 1400865263
  • Pages : 314 pages

Download or read book Genomic Signal Processing written by Ilya Shmulevich and published by Princeton University Press. This book was released on 2014-09-08 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: Genomic signal processing (GSP) can be defined as the analysis, processing, and use of genomic signals to gain biological knowledge, and the translation of that knowledge into systems-based applications that can be used to diagnose and treat genetic diseases. Situated at the crossroads of engineering, biology, mathematics, statistics, and computer science, GSP requires the development of both nonlinear dynamical models that adequately represent genomic regulation, and diagnostic and therapeutic tools based on these models. This book facilitates these developments by providing rigorous mathematical definitions and propositions for the main elements of GSP and by paying attention to the validity of models relative to the data. Ilya Shmulevich and Edward Dougherty cover real-world situations and explain their mathematical modeling in relation to systems biology and systems medicine. Genomic Signal Processing makes a major contribution to computational biology, systems biology, and translational genomics by providing a self-contained explanation of the fundamental mathematical issues facing researchers in four areas: classification, clustering, network modeling, and network intervention.

Book Computational Science and Its Applications   ICCSA 2007

Download or read book Computational Science and Its Applications ICCSA 2007 written by Osvaldo Gervasi and published by Springer. This book was released on 2007-08-29 with total page 1229 pages. Available in PDF, EPUB and Kindle. Book excerpt: This three-volume set constitutes the refereed proceedings of the International Conference on Computational Science and its Applications. These volumes feature outstanding papers that present a wealth of original research results in the field of computational science, from foundational issues in computer science and mathematics to advanced applications in almost all sciences that use computational techniques.

Book Genetic Variation

    Book Details:
  • Author : Michael P. Weiner
  • Publisher :
  • Release : 2007
  • ISBN :
  • Pages : 504 pages

Download or read book Genetic Variation written by Michael P. Weiner and published by . This book was released on 2007 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt: Genetic Variation: A Laboratory Manualis the first compendium of protocols specifically geared towards genetic variation studies, and includes thorough discussions on their applications for human and model organism studies. Intended for graduate students and professional scientists in clinical and research settings, it covers the complete spectrum of genetic variation—from SNPs and microsatellites to more complex DNA alterations, including copy number variation. Written and edited by leading scientists in the field, the early sections of the manual are devoted to study design and generating genotype data, the use of resources such as HapMap and dbSNP, as well as experimental, statistical, and bioinformatic approaches for analyzing the data. The final sections include descriptions of genetic variation in model organisms and discussions of recent insights into human genetic ancestry, forensics, and human variation.

Book Handbook of Surface Plasmon Resonance

Download or read book Handbook of Surface Plasmon Resonance written by Richard B. M. Schasfoort and published by Royal Society of Chemistry. This book was released on 2017-05-30 with total page 555 pages. Available in PDF, EPUB and Kindle. Book excerpt: Surface plasmon resonance (SPR) plays a dominant role in real-time interaction sensing of biomolecular binding events, this book provides a total system description including optics, fluidics and sensor surfaces for a wide researcher audience.

Book Semiparametric Theory and Missing Data

Download or read book Semiparametric Theory and Missing Data written by Anastasios Tsiatis and published by Springer Science & Business Media. This book was released on 2007-01-15 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book summarizes current knowledge regarding the theory of estimation for semiparametric models with missing data, in an organized and comprehensive manner. It starts with the study of semiparametric methods when there are no missing data. The description of the theory of estimation for semiparametric models is both rigorous and intuitive, relying on geometric ideas to reinforce the intuition and understanding of the theory. These methods are then applied to problems with missing, censored, and coarsened data with the goal of deriving estimators that are as robust and efficient as possible.