maigesPack: A Computational Environment for Microarray Data Analysis

Microarray technology is still an important way to assess gene expression in molecular biology, mainly because it measures expression profiles for thousands of genes simultaneously, what makes this technology a good option for some studies focused on systems biology. One of its main problem is complexity of experimental procedure, presenting several sources of variability, hindering statistical modeling. So far, there is no standard protocol for generation and evaluation of microarray data. To mitigate the analysis process this paper presents an R package, named maigesPack, that helps with data organization. Besides that, it makes data analysis process more robust, reliable and reproducible. Also, maigesPack aggregates several data analysis procedures reported in literature, for instance: cluster analysis, differential expression, supervised classifiers, relevance networks and functional classification of gene groups or gene networks

Constructing and Visualizing High-Quality Classifier Decision Boundary Maps dagger

Visualizing decision boundaries of machine learning classifiers can help in classifier design, testing and fine-tuning. Decision maps are visualization techniques that overcome the key sparsity-related limitation of scatterplots for this task. To increase the trustworthiness of decision map use, we perform an extensive evaluation considering the dimensionality-reduction (DR) projection techniques underlying decision map construction. We extend the visual accuracy of decision maps by proposing additional techniques to suppress errors caused by projection distortions. Additionally, we propose ways to estimate and visually encode the distance-to-decision-boundary in decision maps, thereby enriching the conveyed information. We demonstrate our improvements and the insights that decision maps convey on several real-world datasets

Trypanosoma cruzi Gene Expression in Response to Gamma Radiation

Trypanosoma cruzi is an organism highly resistant to ionizing radiation. Following a dose of 500 Gy of gamma radiation, the fragmented genomic DNA is gradually reconstructed and the pattern of chromosomal bands is restored in less than 48 hours. Cell growth arrests after irradiation but, while DNA is completely fragmented, RNA maintains its integrity. In this work we compared the transcriptional profiles of irradiated and non-irradiated epimastigotes at different time points after irradiation using microarray. In total, 273 genes were differentially expressed; from these, 160 were up-regulated and 113 down-regulated. We found that genes with predicted functions are the most prevalent in the down-regulated gene category. Translation and protein metabolic processes, as well as generation of precursor of metabolites and energy pathways were affected. In contrast, the up-regulated category was mainly composed of obsolete sequences (which included some genes of the kinetoplast DNA), genes coding for hypothetical proteins, and Retrotransposon Hot Spot genes. Finally, the tyrosyl-DNA phosphodiesterase 1, a gene involved in double-strand DNA break repair process, was up-regulated. Our study demonstrated the peculiar response to ionizing radiation, raising questions about how this organism changes its gene expression to manage such a harmful stress

Characterization of global transcription profile of normal and HPV-immortalized keratinocytes and their response to TNF treatment

<p>Abstract</p> <p>Background</p> <p>Persistent infection by high risk HPV types (e.g. HPV-16, -18, -31, and -45) is the main risk factor for development of cervical intraepithelial neoplasia and cervical cancer. Tumor necrosis factor (TNF) is a key mediator of epithelial cell inflammatory response and exerts a potent cytostatic effect on normal or HPV16, but not on HPV18 immortalized keratinocytes. Moreover, several cervical carcinoma-derived cell lines are resistant to TNF anti-proliferative effect suggesting that the acquisition of TNF-resistance may constitute an important step in HPV-mediated carcinogenesis. In the present study, we compared the gene expression profiles of normal and HPV16 or 18 immortalized human keratinocytes before and after treatment with TNF for 3 or 60 hours.</p> <p>Methods</p> <p>In this study, we determined the transcriptional changes 3 and 60 hours after TNF treatment of normal, HPV16 and HPV18 immortalized keratinocytes by microarray analysis. The expression pattern of two genes observed by microarray was confirmed by Northern Blot. NF-κB activation was also determined by electrophoretic mobility shift assay (EMSA) using specific oligonucleotides and nuclear protein extracts.</p> <p>Results</p> <p>We observed the differential expression of a common set of genes in two TNF-sensitive cell lines that differs from those modulated in TNF-resistant ones. This information was used to define genes whose differential expression could be associated with the differential response to TNF, such as: <it>KLK7 </it>(<it>kallikrein 7</it>), <it>SOD2 </it>(<it>superoxide dismutase 2</it>), <it>100P </it>(<it>S100 calcium binding protein P</it>), <it>PI3 </it>(<it>protease inhibitor 3, skin-derived</it>), <it>CSTA </it>(<it>cystatin A</it>), <it>RARRES1 </it>(<it>retinoic acid receptor responder 1</it>), and <it>LXN </it>(<it>latexin</it>). The differential expression of the <it>KLK7 </it>and <it>SOD2 </it>transcripts was confirmed by Northern blot. Moreover, we observed that <it>SOD2 </it>expression correlates with the differential NF-κB activation exhibited by TNF-sensitive and TNF-resistant cells.</p> <p>Conclusion</p> <p>This is the first in depth analysis of the differential effect of TNF on normal and HPV16 or HPV18 immortalized keratinocytes. Our findings may be useful for the identification of genes involved in TNF resistance acquisition and candidate genes which deregulated expression may be associated with cervical disease establishment and/or progression.</p

2: Restoration of variable area soundtracks: watershed against region growing segmentation

Review of a work submitted to the International Symposium on Mathematical Morphology, 8 (ISMM)

2: Watershed from Propagated Markers Improved by the Binding of Markers Heuristic

Review of a work submitted to the International Symposium on Mathematical Morphology, 8 (ISMM)

Basis computation algorithms

Algorithms for the computation of the basis (maximal intervals of the kernel) of binary and gray-scale translation-invariant and locally defined morphological operators are presented. Some examples that illustrate the dynamics of the algorithms as well as their use as learning algorithms are also presented