Background: Spatially mapped large scale gene expression databases enable quantitative comparison of data measurements across genes, anatomy, and phenotype. In most ongoing effort...
Christopher Lau, Lydia Ng, Carol Thompson, Sayan D...
Background: Non-negative matrix factorisation (NMF), a machine learning algorithm, has been applied to the analysis of microarray data. A key feature of NMF is the ability to iden...
Abstract. This paper presents a method that uses gene ontologies, together with the paradigm of relational subgroup discovery, to help find description of groups of genes different...
Background: Tissue Microarrays (TMAs) have emerged as a powerful tool for examining the distribution of marker molecules in hundreds of different tissues displayed on a single sli...
Jules J. Berman, Milton Datta, Andre Kajdacsy-Ball...
Clustering or co-clustering techniques have been proved useful in many application domains. A weakness of these techniques remains the poor support for grouping characterization. ...