Exploiting sample variability to enhance multivariate analysis of microarray data

Exploiting sample variability to enhance multivariate analysis of microarray data

MOTIVATION Biological and technical variability is intrinsic in any microarray experiment. While most approaches aim to account for this variability, they do not actively exploit it. Here, we consider a novel approach that uses the variability between arrays to provide an extra source of information that can enhance gene expression analyses. RESULTS We develop a method that uses sample simila...

Multivariate exploratory tools for microarray data analysis.

The ultimate success of microarray technology in basic and applied biological sciences depends critically on the development of statistical methods for gene expression data analysis. The most widely used tests for differential expression of genes are essentially univariate. Such tests disregard the multidimensional structure of microarray data. Multivariate methods are needed to utilize the inf...

An Application of Multivariate Analysis to Complex Sample Survey Data

Exploiting Evidence from Unstructured Data to Enhance Master Data Management

Master data management (MDM) integrates data from multiple structured data sources and builds a consolidated 360degree view of business entities such as customers and products. Today’s MDM systems are not prepared to integrate information from unstructured data sources, such as news reports, emails, call-center transcripts, and chat logs. However, those unstructured data sources may contain val...

cDNA Microarray Data Normalization