Abstract. We describe and empirically evaluate machine learning methods for the prediction of zinc binding sites from protein sequences. We start by observing that a data set consi...
Sauro Menchetti, Andrea Passerini, Paolo Frasconi,...
Background: Statistical methods for ranking differentially expressed genes (DEGs) from gene expression data should be evaluated with regard to high sensitivity, specificity, and r...
Background: Large biological data sets, such as expression profiles, benefit from reduction of random noise. Principal component (PC) analysis has been used for this purpose, but ...
Motivation: The issue of high dimensionality in microarray data has been, and remains, a hot topic in statistical and computational analysis. Efficient gene filtering and differen...
Background: High-throughput genotyping technology has enabled cost effective typing of thousands of individuals in hundred of thousands of markers for use in genome wide studies. ...