Gene selection in microarray data analysis for brain cancer classification

Cancer classification has been one of the most challenging tasks in clinical diagnosis. At present cancer classification is done mainly by looking through the cells' morphological differences, which do not always give a clear distinction of cancer subtypes. Unfortunately, this may have a significant impact on the final outcome of whether a patient could be cured effectively. Microarray technology can play an important role on diagnosing which type of disease one is carrying. The gene selection process is critical for developing gene markers for faster and more accurate diagnosis. In this paper, we develop a method using pairwise data comparisons instead of the one-over-the-rest approach used nowadays. Results are evaluated using available clustering techniques including hierarchical clustering and k-means clustering. Using pairwise comparison, the best accuracy achieved is 95% while it is only 83% when using one-over-the-rest approach. ©2006 IEEE.published_or_final_versio

Nitrite/nitrate levels in patients after stem cell transplant

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Second order statistics based blind source separation for artifact correction of short ERP epochs

ERP is commonly obtained by averaging over segmented EEC epochs. In case artifacts are present in the raw EEC measurement, pre-processing is required to prevent the averaged ERP waveform being interfered by artifacts. The simplest pre-processing approach is by rejecting trials in which presence of artifact is detected. Alternatively artifact correction instead of rejection can be performed by blind source separation, so that waste of ERP trials is avoided. In this paper, we propose a second order statistics based blind source separation approach to ERP artifact correction. Comparing with blind separation using independent component analysis, second order statistics based method does not rely on higher order statistics or signal entropy, and therefore leads to more robust separation even if only short epochs are available.published_or_final_versio

Downregulation of endothelin (ET)-1 and interleukin (IL)-8 expression in human respiratory mucosa by Pseudomonas aeruginosa pyocyanin (pyo) and 1-hydroxy-phenazine (HP)

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Down-expression of inducible nitric oxide synthase (iNOS) and endothelial (Enos) proteins and mRNA iNOS in bronchiectasis in vivo

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Nitric oxide (NO) levels in exhaled air, sputum, serum, saliva, and urine of bronchiectasis subjects: a comparision study

Session - Respiratory & Critical Care Medicine: no. S-RC-1published_or_final_versio

Exhaled nitric oxide (NO) levels in steady state bronchiectasis: a prospective systematic study

Session - Respiratory & Critical Care Medicine: no. S-RC-2published_or_final_versio

Aquaporin 3 expression in respiratory mucosa is down-regulated in bronchiectasis in vivo

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The effects of gender on exhaled Nitric Oxide (NO) production among volunteers

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Anti-inflammatory treatment increased exhaled nitric oxide production on patients with active bronchiectasis

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