Bayesian Modeling of MPSS Data: Gene Expression Analysis of Bovine Salmonella Infection
نویسندگان
چکیده
منابع مشابه
Bayesian Modeling of MPSS Data: Gene Expression Analysis of Bovine Salmonella Infection.
Massively Parallel Signature Sequencing (MPSS) is a high-throughput counting-based technology available for gene expression profiling. It produces output that is similar to Serial Analysis of Gene Expression (SAGE) and is ideal for building complex relational databases for gene expression. Our goal is to compare the in vivo global gene expression profiles of tissues infected with different stra...
متن کاملBayesian Differential Analysis of Gene Expression Data
This paper describes a novel Bayesian method for the differential analysis of large scale gene expression data. The novelty of the method is the use of a contamination model that integrates the different sources of variability that affect gene expression data measured with microarray technology, thus removing the need for arbitrary normalization.
متن کاملBayesian Modeling Based on Data from the Internet of Things
The Internet of Things is suggested as the upcoming revolution in the Information and communication technology due to its very high capability of making various businesses and industries more productive and efficient. This productivity comes from the emergence of innovation and the introduction of new capabilities for businesses. Different industries have shown varying reactions to IOT, but wha...
متن کاملBayesian Analysis of Cell-Cycle Gene Expression Data
The study of the cell-cycle is important in order to aid in our understanding of the basic mechanisms of life, yet progress has been slow due to the complexity of the process and our lack of ability to study it at high resolution. Recent advances in microarray technology have enabled scientists to study the gene expression at the genome-scale with a manageable cost, and there has been an increa...
متن کاملBayesian hierarchical error model for analysis of gene expression data
MOTIVATION Analysis of genome-wide microarray data requires the estimation of a large number of genetic parameters for individual genes and their interaction expression patterns under multiple biological conditions. The sources of microarray error variability comprises various biological and experimental factors, such as biological and individual replication, sample preparation, hybridization a...
متن کاملذخیره 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: Journal of the American Statistical Association
سال: 2010
ISSN: 0162-1459,1537-274X
DOI: 10.1198/jasa.2010.ap08327