Background: Modern high throughput experimental techniques such as DNA microarrays often result in large lists of genes. Computational biology tools such as clustering are then us...
Alain B. Tchagang, Alexander Gawronski, Hugo B&eac...
Background: In gene networks, the timing of significant changes in the expression level of each gene may be the most critical information in time course expression profiles. With ...
Hao Li, Constance L. Wood, Yushu Liu, Thomas V. Ge...
Background: Microarrays have become extremely useful for analysing genetic phenomena, but establishing a relation between microarray analysis results (typically a list of genes) a...
Franck Rapaport, Andrei Zinovyev, Marie Dutreix, E...
Background: Microarray data analysis is notorious for involving a huge number of genes compared to a relatively small number of samples. Gene selection is to detect the most signi...
Clustering has been one of the most popular methods to discover useful biological insights from DNA microarray. An interesting paradigm is simultaneous clustering of both genes an...