Gene selection: a Bayesian variable selection approach

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

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

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Gene selection: a Bayesian variable selection approach

UNLABELLED Selection of significant genes via expression patterns is an important problem in microarray experiments. Owing to small sample size and the large number of variables (genes), the selection process can be unstable. This paper proposes a hierarchical Bayesian model for gene (variable) selection. We employ latent variables to specialize the model to a regression setting and uses a Baye...

متن کامل

Bayesian recursive variable selection

In this work we introduce a new model space prior for Bayesian variable selection in linear regression. This prior is designed based on a recursive constructive procedure that randomly generates models by including variables in a stagewise fashion. We provide a recipe for carrying out Bayesian variable selection and model averaging using this prior, and show that it possesses several desirable ...

متن کامل

Bayesian Shrinkage Variable Selection

We introduce a new Bayesian approach to the variable selection problem which we term Bayesian Shrinkage Variable Selection (BSVS ). This approach is inspired by the Relevance Vector Machine (RVM ), which uses a Bayesian hierarchical linear setup to do variable selection and model estimation. RVM is typically applied in the context of kernel regression although it is also suitable in the standar...

متن کامل

Bayesian Grouped Variable Selection

Traditionally, variable selection in the context of linear regression has been approached using optimization based approaches like the classical Lasso. Such methods provide a sparse point estimate with respect to regression coefficients but are unable to provide more information regarding the distribution of regression coefficients like expectation, variance estimates etc. In the recent years, ...

متن کامل

Objective Bayesian Variable Selection

A novel fully automatic Bayesian procedure for variable selection in normal regression models is proposed, along with computational strategies for model posterior evaluation. A stochastic search algorithm is given, based on the Metropolis-Hastings Algorithm, that has a stationary distribution proportional to the model posterior probabilities. The procedure is illustrated on both simulated and r...

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

ژورنال

عنوان ژورنال: Bioinformatics

سال: 2003

ISSN: 1367-4803,1460-2059

DOI: 10.1093/bioinformatics/19.1.90