It is a consensus in microarray analysis that identifying potential local patterns, characterized by coherent groups of genes and conditions, may shed light on the discovery of pre...
Background: Microarray data normalization is an important step for obtaining data that are reliable and usable for subsequent analysis. One of the most commonly utilized normaliza...
John A. Berger, Sampsa Hautaniemi, Anna-Kaarina J&...
Background: Probability based statistical learning methods such as mutual information and Bayesian networks have emerged as a major category of tools for reverse engineering mecha...
The problem of simultaneously clustering columns and rows (coclustering) arises in important applications, such as text data mining, microarray analysis, and recommendation system...
Background: Obtaining physiological insights from microarray experiments requires computational techniques that relate gene expression data to functional information. Traditionall...
Anne M. Denton, Jianfei Wu, Megan K. Townsend, Pre...