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Bayesian Causal Phenotype Network Incorporating Genetic Variation and Biological Knowledge

Jee Young Moon, Elias Chaibub Neto, Xinwei Deng and Brian S. Yandell.

in Probabilistic Graphical Models for Genetics, Genomics, and Postgenomics

September 2014; p ublished online December 2014 .

Chapter. Subjects: Probability and Statistics; Bioinformatics and Computational Biology. 15975 words.

In a segregating population, quantitative trait loci (QTL) mapping can identify QTLs with a causal effect on a phenotype. A common feature of these methods is that QTL mapping and phenotype...

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Bayesian Networks in the Study of Genome-wide DNA Methylation

Meromit Singer and Lior Pachter.

in Probabilistic Graphical Models for Genetics, Genomics, and Postgenomics

September 2014; p ublished online December 2014 .

Chapter. Subjects: Probability and Statistics; Bioinformatics and Computational Biology. 12821 words.

This chapter explores the use of Bayesian networks in the study of genome-scale deoxyribonucleic acid (DNA) methylation. It begins by describing different experimental methods for the...

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Bayesian, Systems-based, Multilevel Analysis of Associations for Complex Phenotypes: from Interpretation to Decision

Péter Antal, András Millinghoffer, Gábor Hullám, Gergely Hajós, Péter Sárközy, András Gézsi, Csaba Szalai and András Falus.

in Probabilistic Graphical Models for Genetics, Genomics, and Postgenomics

September 2014; p ublished online December 2014 .

Chapter. Subjects: Probability and Statistics; Bioinformatics and Computational Biology. 20271 words.

The relative scarcity of the results reported by genetic association studies (GAS) prompted many research directions. Despite the centrality of the concept of association in GASs, refined...

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Comparison of Mixture Bayesian and Mixture Regression Approaches to Infer Gene Networks

Sandra L. Rodriguez–Zas and Bruce R. Southey.

in Probabilistic Graphical Models for Genetics, Genomics, and Postgenomics

September 2014; p ublished online December 2014 .

Chapter. Subjects: Probability and Statistics; Bioinformatics and Computational Biology. 7260 words.

Most Bayesian network applications to gene network reconstruction assume a single distributional model across all the samples and treatments analyzed. This assumption is likely to be...

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Detection of Copy Number Variations from Array Comparative Genomic Hybridization Data Using Linear-chain Conditional Random Field Models

Xiaolin Yin and Jing Li.

in Probabilistic Graphical Models for Genetics, Genomics, and Postgenomics

September 2014; p ublished online December 2014 .

Chapter. Subjects: Probability and Statistics; Bioinformatics and Computational Biology. 12063 words.

Copy number variation (CNV) accounts for roughly 12% of the human genome. Beside their inherent role in cancer development, CNVs have been reported to underlie susceptibility to complex...

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Essentials to Understand Probabilistic Graphical Models: A Tutorial about Inference and Learning

Christine Sinoquet.

in Probabilistic Graphical Models for Genetics, Genomics, and Postgenomics

September 2014; p ublished online December 2014 .

Chapter. Subjects: Probability and Statistics; Bioinformatics and Computational Biology. 28163 words.

The aim of this chapter is to offer an advanced tutorial to scientists with no background or no deep background on probabilistic graphical models. To readers more familiar with these...

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Graphical Modeling of Biological Pathways in Genome-wide Association Studies

Min Chen, Judy Cho and Hongyu Zhao.

in Probabilistic Graphical Models for Genetics, Genomics, and Postgenomics

September 2014; p ublished online December 2014 .

Chapter. Subjects: Probability and Statistics; Bioinformatics and Computational Biology. 11975 words.

Genome-wide association studies (GWASs) are widely used to identify good candidates of disease-associated genes that are of interest for further follow-up studies. However, knowledge of...

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Graphical Models and Multivariate Analysis of Microarray Data

Harri Kiiveri.

in Probabilistic Graphical Models for Genetics, Genomics, and Postgenomics

September 2014; p ublished online December 2014 .

Chapter. Subjects: Probability and Statistics; Bioinformatics and Computational Biology. 9375 words.

The usual analysis of gene expression data ignores the correlation between gene expression values. Biologically, this assumption is unreasonable. The approach presented in this chapter...

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Latent Variable Models for Analyzing DNA Methylation

E. Andrés Houseman.

in Probabilistic Graphical Models for Genetics, Genomics, and Postgenomics

September 2014; p ublished online December 2014 .

Chapter. Subjects: Probability and Statistics; Bioinformatics and Computational Biology. 10324 words.

Deoxyribonucleic acid (DNA) methylation is tightly linked with cellular differentiation. For instance, it has been observed that DNA methylation in tumor cells encodes phenotypic...

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Mahalanobis D2

Overview page. Subjects: Probability and Statistics — Ecology and Conservation.

A measure of generalized distance between samples based on the means, variances (see mean square), and covariances of various properties of replicate samples in multivariate analysis. The...

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