Gene expression

Application of MUTIC to the exploration of gene expression data in prostate cancer

L. S. Coelho, Mudado, M. A., Goertzel, B., and Pennachin, C., “Application of MUTIC to the exploration of gene expression data in prostate cancer”, vol. 6, pp. 890-900, 2007.

We show here an example of the application of a novel method, MUTIC (model utilization-based clustering), used for identifying complex interactions between genes or gene categories based on gene expression data. The method deals with binary categorical data which consist of a set of gene expression profiles divided into two biologically meaningful categories. It does not require data from multiple time points.

Control of gene expression and genetic manipulation in the Trypanosomatidae

S. M. R. Teixeira and da Rocha, W. D., “Control of gene expression and genetic manipulation in the Trypanosomatidae”, vol. 2. pp. 148-158, 2003.

Mechanisms controlling gene expression in trypanosomatids depend on several layers of regulation, with most regulatory pathways acting at a post-transcriptional level. Consequently, these parasites can follow the rapid changes associated with transitions between the insect vector and the mammalian host, with instant reprogramming of genetic expression.

Gene expression in Chromobacterium violaceum

R. Silva, Araripe, J. R., Rondinelli, E., and Ürményi, T. P., “Gene expression in Chromobacterium violaceum”, vol. 3, pp. 64-75, 2004.

The repertoire of 4,431 open reading frames (ORFs), eight rRNA operons and 98 tRNA genes of Chromobacterium violaceum must be expressed in a regulated manner for successful adaptation to a wide variety of environmental conditions. To accomplish this feat, the organism relies on protein machineries involved in transcription, RNA processing and translation. Analysis of the C.

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