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Bayesian Inference for Gene Expression and Proteomics

reviews of Bayesian methodology, tools and software for single group inference, group comparisons, classification and clustering, motif discovery;

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Bayesian Inference For Gene Expression And Proteomics

reviews of Bayesian methodology, tools and software for single group inference, group comparisons, classification and clustering, motif discovery;

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Bayesian Modeling in Bioinformatics

expression and phylogenic analysis. The book explores Bayesian techniques and models for detecting differentially expressed genes, classifying;

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Bayesian Modeling in Bioinformatics

expression and phylogenic analysis. The book explores Bayesian techniques and models for detecting differentially expressed genes, classifying;

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Bayesian Analysis of Gene Expression Data

exclusively to Bayesian methods of analysis for applications to high-throughput gene expression data, exploring the relevant methods that are changing;

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Genomics Data Analysis

combine advantages of traditional Bayesian and frequentist statistics. Techniques for estimating the local false discovery rate assign;

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Genomics Data Analysis

combine advantages of traditional Bayesian and frequentist statistics. Techniques for estimating the local false discovery rate assign;

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Measuring Gene Expression

In the post-genomic age, much biomedical research looks at when, where, and at what level genes are expressed. Measuring Gene Expression;

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Genomics and Proteomics in Nutrition

expression on protein production, establishing links between gene expression and nutrition, the influence of micro- and macronutrients on cellular;

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Genomics and Proteomics in Nutrition

expression on protein production, establishing links between gene expression and nutrition, the influence of micro- and macronutrients on cellular;

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Functional Genomics and Proteomics in the Clinical Neurosciences

The purpose of this work is to familiarize neuroscientists with the available tools for proteome research and their relative abilities and;

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An Introduction to Bayesian Inference in Econometrics

volume is an early introduction to Bayesian inference and methodology which still has lasting value for today's statistician and student. The;

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Statistical Inference

inference and Bayesian model comparison, this book develops a unique methodology for solving challenging inference problems. It also includes a;

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Statistical Inference

inference and Bayesian model comparison, this book develops a unique methodology for solving challenging inference problems. It also includes a;

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Examining the Causal Relationship Between Genes, Epigenetics, and Human Health

For as much as we know about DNA and gene expression, many more mysteries remain to be solved. Epigenetics and epigenomics seek to study;

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Bayesian Inference for Probabilistic Risk Assessment

Bayesian Inference for Probabilistic Risk Assessment provides a Bayesian foundation for framing probabilistic problems and performing;

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Principles of Proteomics

amounts of data. Databases are critical for recording and carefully storing this data, allowing the researcher to make connections between their;

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Genomics and Proteomics

and genomic approaches for abiotic stress tolerance in crop plants The book will be valuable for biotechnology researchers and;

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Genomics and Proteomics

. * Biotechnological and genomic approaches for abiotic stress tolerance in crop plants The book will be valuable for biotechnology researchers and;

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Introduction to Bayesian Statistics

statistical topics, such as scientific data gathering, discrete random variables, robust Bayesian methods, and Bayesian approaches to inference for;

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Statistics for Astrophysics

Computation (ABC) and Bayesian nonparametric inference and clustering.;

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Likelihood and Bayesian Inference

methods. It includes a separate chapter on modern numerical techniques for Bayesian inference, and also addresses advanced topics, such as model;

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Likelihood & Bayesian Inference

methods. It includes a separate chapter on modern numerical techniques for Bayesian inference, and also addresses advanced topics, such as model;

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Probability and Bayesian Modeling

Probability and Bayesian Modeling is an introduction to probability and Bayesian thinking for undergraduate students with a calculus;

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An Introduction to Bayesian Inference and Decision

An Introduction to Bayesian Inference and Decision is een boek van Robert L Winkler;

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Bayesian Programming

methodology for building subjective probabilistic models. The authors introduce the principles of Bayesian programming and discuss good practices for;

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Bayesian Programming

methodology for building subjective probabilistic models. The authors introduce the principles of Bayesian programming and discuss good practices for;

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