Bayesian Networks for Genomic Analysis

نویسندگان

  • Paola Sebastiani
  • Maria M. Abad
  • Marco F. Ramoni
چکیده

Bayesian networks are emerging into the genomic arena as a general modeling tool able to unravel the cellular mechanism, to identify genotypes that confer susceptibility to disease, and to lead to diagnostic models. This chapter reviews the foundations of Bayesian networks and shows their application to the analysis of various types of genomic data, from genomic markers to gene expression data. The examples will highlight the potential of this methodology but also the current limitations and we will describe new research directions that hold the promise to make Bayesian networks a fundamental tool for genome data analysis. ∗Department of Biostatistics, Boston University School of Public Health, 715 Albany Street, Boston MA 02118. Email: [email protected] †Software Engineering Department, University of Granada, Daniel Saucedo Aranda, Granada, 18071 Spain. Email: [email protected] ‡Children’s Hospital Informatics Program and Harvard Partners Center for Genetics and Genomics, Harvard Medical School, HMS New Research Building, 77 Pasteur Avenue, Suite 255, Boston, MA 02115. Email: marco [email protected]

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A Bayesian Networks Approach to Reliability Analysis of a Launch Vehicle Liquid Propellant Engine

This paper presents an extension of Bayesian networks (BN) applied to reliability analysis of an open gas generator cycle Liquid propellant engine (OGLE) of launch vehicles. There are several methods for system reliability analysis such as RBD, FTA, FMEA, Markov Chains, and etc. But for complex systems such as LV, they are not all efficiently applicable due to failure dependencies between compo...

متن کامل

Estimation of Products Final Price Using Bayesian Analysis Generalized Poisson Model and Artificial Neural Networks

Estimating the final price of products is of great importance. For manufacturing companies proposing a final price is only possible after the design process over. These companies propose an approximate initial price of the required products to the customers for which some of time and money is required. Here using the existing data of already designed transformers and utilizing the bayesian anal...

متن کامل

Effect of Markers Effect Estimation Methods, Population Structure and Trait Architercture on the Accuracy of Genomic Breeding Values

This study aimed to investigate the  effect  of  the method of estimating the effects of markers , QTLs distribution, number of QTLs, effective population size and trait heritability on the accuracy of genomic predictions. Two effective population sizes, 100 and 500 individuals, were simulated by QMSim software. A 100 cM genome including one chromosome was simulated where 500 SNPs and two diffe...

متن کامل

مقایسه روش های مختلف آماری در انتخاب ژنومی گاوهای هلشتاین

Genomic selection combines statistical methods with genomic data to predict genetic values for complex traits.  The accuracy of prediction of genetic values ​​in selected population has a great effect on the success of this selection method. Accuracy of genomic prediction is highly dependent on the statistical model used to estimate marker effects in reference population. Various factors such a...

متن کامل

The modeling of body's immune system using Bayesian Networks

In this paper, the urinary infection, that is a common symptom of the decline of the immune system, is discussed based on the well-known algorithms in machine learning, such as Bayesian networks in both Markov and tree structures. A large scale sampling has been executed to evaluate the performance of Bayesian network algorithm. A number of 4052 samples wereobtained from the database of the Tak...

متن کامل

Accuracy of Genomic Prediction under Different Genetic Architectures and Estimation Methods

The accuracy of genomic breeding value prediction was investigated in various levels of reference population size, trait heritability and the number of quantitative trait locus (QTL). Five Bayesian methods, including Bayesian Ridge regression, BayesA, BayesB, BayesC and Bayesian LASSO, were used to estimate the marker effects for each of 27 scenarios resulted from combining three levels for her...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2004