عنوان

Probabilistic graphical models for genetics, genomics, and postgenomics

شماره استاندارد

87580

عنوان اصلي

Probabilistic graphical models for genetics, genomics, and postgenomics

محل نشرو پخش و غیره

Oxford

نام ناشر، پخش کننده و غيره

Oxford University Press

تاریخ نشرو بخش و غیره

2014

نام خاص و کميت اثر

xxvii, 449 p.: ill. ; 25 cm

متن يادداشت

Includes bibliographical references and index

متن يادداشت

edited by Christine Sinoquet, editor-in-chief, and Raphael Mourad, Editor

متن يادداشت

pt. I. Introduction -- Probabilistic graphical models for next-generation genomics and genetics -- Essentials to understand probabilistic graphical models : a tutorial about inference and learning -- pt. II. Gene expression -- Graphical models and multivariate analysis of microarray data -- Comparison of mixture Bayesian and mixture regression approaches to infer gene networks -- Network inference in breast cancer with Gaussian graphical models and extensions -- pt. III. Causality discovery -- Utilizing genotypic information as a prior for learning gene networks -- Bayesian causal phenotype network incorporating genetic variation and biological knowledge -- Structural equation models for studying causal phenotype networks in quantitative genetics -- pt. IV. Genetic association studies -- Modeling linkage disequilibrium and performing association studies through probabilistic graphical models : a visiting tour of recent advances -- Modeling linkage disequilibrium with decomposable graphical models -- Scoring, searching and evaluating Bayesian network models of gene-phenotype association -- Graphical modeling of biological pathways in genome-wide association studies -- Bayesian systems-based, multilevel analysis of associations for complex phenotypes : from interpretation to decision -- pt. V. Epigenetics -- Bayesian networks in the study of genome-wide DNA methylation -- Latent variable models for analyzing DNA methylation -- pt. VI. Detection of copy number variations -- Detection of copy number variations from array comparative genomic hybridization data using linear-chain conditional random field models -- pt. VII. Prediction of outcomes from high-dimensional genomic data -- Prediction of clinical outcomes from genome-wide data

عنصر شناسه ای

Statistical methods ، Genomics

عنصر شناسه ای

Statistical methods ، Genetics

عنصر شناسه ای

، Graphical modeling )Statistics(

شماره رده

کد نقش

TI

عنصر شناسه اي

AU enitsirhC ,teuqoniS editor

عنصر شناسه اي

AU leahpaR ,daruoM editor

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