Background: One important application of microarray experiments is to identify differentially expressed genes. Often, small and negative expression levels were clipped-off to be e...
Background: A critical step in processing oligonucleotide microarray data is combining the information in multiple probes to produce a single number that best captures the express...
Analyzing gene expression patterns is becoming a highly relevant task in the Bioinformatics area. This analysis makes it possible to determine the behavior patterns of genes under...
Background: Microarray experiments examine the change in transcript levels of tens of thousands of genes simultaneously. To derive meaningful data, biologists investigate the resp...
Mayer Alvo, Zhongzhu Liu, Andrew Williams, Carole ...
Existing 3D clustering algorithms on gene ? sample ? time expression data do not consider the time lags between correlated gene expression patterns. Besides, they either ignore the...