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Data Analysis for Omic Sciences: Methods and Applications

Data Analysis for Omic Sciences: Methods and Applications, Volume 82, shows how these types of challenging datasets can be analyzed;

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Exploratory Data Analysis in Empirical Research

ideas and examples for cross disciplinary applications of classification and data analysis methods in fields such as data and web mining;

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Omic Association Studies with R and Bioconductor

After the great expansion of genome-wide association studies, their scientific methodology and, notably, their data analysis has matured;

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Omic Association Studies with R and Bioconductor

After the great expansion of genome-wide association studies, their scientific methodology and, notably, their data analysis has matured;

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Big Data in Omics and Imaging, Two Volume Set

analysis and the modern advanced statistical methods for big data Provides tools for high dimensional data reduction Discusses searching;

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Statistical Analysis of Proteomics, Metabolomics, and Lipidomics Data Using Mass Spectrometry

spectrometry data for the new omic sciences. The text discusses common aspects of design and analysis between and across all (or most) forms of mass;

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Advanced Studies in Classification and Data Science

of data analysis and related areas, e.g. the analysis of complex data, analysis of qualitative data, methods for high-dimensional data;

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Modern Statistical Methods for Health Research

interactions of scholars across health research related disciplines. Topics covered include: Health data analysis and applications to EHR data;

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Advanced Studies in Behaviormetrics and Data Science

This book focuses on the latest developments in behaviormetrics and data science, covering a wide range of topics in data analysis and;

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Advanced Studies in Behaviormetrics and Data Science

This book focuses on the latest developments in behaviormetrics and data science, covering a wide range of topics in data analysis and;

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Applied Longitudinal Analysis

Longitudinal Analysis, Second Edition presents modern methods for analyzing data from longitudinal studies and now features the latest state-of-the-art;

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Computational Intelligence Methods for Bioinformatics and Biostatistics

medicine, and data integration and analysis in omic-science.;

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Methods and Applications of Longitudinal Data Analysis

Methods and Applications of Longitudinal Data Analysis describes methods for the analysis of longitudinal data in the medical;

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Statistical Analysis of Spherical Data

This is the first comprehensive, yet clearly presented, account of statistical methods for analysing spherical data. The analysis of data;

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BIOS Instant Notes in Bioinformatics

, supramolecular organization, systems biology and the integration of-omic data, physiology, image analysis, and text analysis.;

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An Introduction to Categorical Data Analysis

, particularly for applications in the biomedical and social sciences. An Introduction to Categorical Data Analysis, Third Edition summarizes these;

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Categorical Data Analysis

Praise for the Second Edition A must-have book for anyone expecting to do research and/or applications in categorical data analysis;

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Spatial Data Analysis in the Social and Environmental Sciences

Within both the social and environmental sciences, much of the data collected is within a spatial context and requires statistical analysis;

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Surrogate Tissue Analysis

applications and considerations for omic technologies in the field of surrogate tissue analysis. Highlighting important issues to consider when;

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Statistical Methods for Agricultural and Biological Sciences

STATISTICAL METHODS for Agricultural and Biological Sciences introduces basic statistical concepts as are required for understanding;

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Machine Learning Methods in the Environmental Sciences

circulation models(GCM), weather and climate prediction, air quality forecasting, analysis and modelling of environmental data, oceanographic and;

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Machine Learning Methods in the Environmental Sciences

circulation models(GCM), weather and climate prediction, air quality forecasting, analysis and modelling of environmental data, oceanographic and;

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Structural Analysis in the Social Sciences

, exponential families of random graphs, the analysis of longitudinal network data, graphical techniques for exploring network data, and software for;

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Structural Analysis in the Social Sciences

, exponential families of random graphs, the analysis of longitudinal network data, graphical techniques for exploring network data, and software for;

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Classification and Data Analysis

composite measures, and numerous applications of data analysis methods in economics, finance and other social sciences. The book is intended for a;

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Multivariate Analysis for the Biobehavioral and Social Sciences

the Biobehavioral and Social Sciences: A Graphical Approach outlines the essential multivariate methods for understanding data in the social;

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Statistical Analysis of Longitudinal Categorical Data in the Social and Behavioral Sciences

social sciences, computer tutorials, and exercises. Written for social scientists and students, no advanced mathematical training is required;

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