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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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Bayesian Modeling in Bioinformatics

phylogenic analysis, sparsity priors for protein-protein interaction predictions, and Bayesian networks for gene expression data. The text also;

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Bayesian Modeling in Bioinformatics

phylogenic analysis, sparsity priors for protein-protein interaction predictions, and Bayesian networks for gene expression data. The text also;

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Bayesian Inference for Gene Expression and Proteomics

of Bayesian methods in the analysis of high-throughput bioinformatics data that arise from medical, in particular, cancer research, as well as;

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Bayesian Inference For Gene Expression And Proteomics

of Bayesian methods in the analysis of high-throughput bioinformatics data that arise from medical, in particular, cancer research, as well as;

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Advanced Analysis of Gene Expression Microarray Data

patterns in gene expression microarray data sets* Sample-based analysis: supervised and unsupervised methods for the reduction of the gene;

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Genomics Data Analysis

expression and on genetic association data and briefly covering metabolomics data and proteomics data * gradual introduction to the mathematical;

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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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Gene Expression Data Analysis

for generating gene expression data. Background knowledge on statistical modeling and machine learning techniques. Detailed methodology;

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Weighted Network Analysis

High-throughput measurements of gene expression and genetic marker data facilitate systems biologic and systems genetic data analysis;

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Statistical Analysis of Gene Expression Microarray Data

authors of this book. Statistical Analysis of Gene Expression Microarray Data promises to become the definitive basic reference in the field;

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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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Nonlinear Mixture Models

literature.In this book the authors present Bayesian methods of analysis for nonlinear, hierarchical mixture models, with a finite, but possibly unknown;

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Microarray Gene Expression Data Analysis

that are available from non--commercial sources. Concepts and principles underpinning gene expression analysis are emphasised and wherever;

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Principles and Methods for Data Science

, Analysis of microarray gene expression data using information theory and stochastic algorithm, Hybrid Models, Markov Chain Monte Carlo Methods;

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Sage

In the post-genomic era SAGE (Serial Analysis of Gene Expression) is one of the most powerful tools available for global expression;

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Bioconductor Case Studies

apply Bioconductor tools in the analysis of microarray gene expression data. Topics covered include: (1) import and preprocessing of data from;

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Analyzing Microarray Gene Expression Data

A multi-discipline, hands-on guide to microarray analysis of biological processes Analyzing Microarray Gene Expression Data provides a;

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Statistics in Human Genetics and Molecular Biology

. It also covers differential gene expression detection as well as classification and cluster analysis using gene expression data sets;

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Analysis of Microarray Data: A Network-Based Approach

for Gene Regulation* Estimating Transcriptional Regulatory Networks by a Bayesian Network* Analysis of Therapeutic Compound Effects;

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A Practical Approach to Microarray Data Analysis

, and simulation of regulatory gene networks, and the mapping of expression data to metabolic pathways and chromosome locations have been added;

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Gene Expression Analysis

This volume provides experimental and bioinformatics approaches related to different aspects of gene expression analysis. Divided in three;

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Analyzing High-Dimensional Gene Expression and DNA Methylation Data with R

Analyzing high-dimensional gene expression and DNA methylation data with R is the first practical book that shows a ``pipeline;

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Analyzing High-Dimensional Gene Expression and DNA Methylation Data with R

Analyzing high-dimensional gene expression and DNA methylation data with R is the first practical book that shows a ``pipeline;

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Gene Expression Studies Using Affymetrix Microarrays

a molecular biologist and a biostatistician with a combined decade of experience in practical expression profiling experiments and data;

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Gene Expression Studies Using Affymetrix Microarrays

a molecular biologist and a biostatistician with a combined decade of experience in practical expression profiling experiments and data;

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Advanced Computational Methods for Biocomputing & Bioimaging

Computational models have been playing a significant role for the computer-based analysis of biological and biomedical data. Given the;

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