• The Korean Journal of Applied Statistics
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• v.21 no.1
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• pp.65-80
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• 2008

Small scale time-course microarray experiments are those which have a small number of time points. They comprise about 80 percent of all time-course microarray experiments conducted up to 2005. Several statistical methods for the small scale time-course microarray experiments have been proposed. In this paper we applied three methods, namely, QR method, maSigPro method and STEM, to a real time-course microarray experiment which had six time points. We compared the performance of these three methods based on a simulation study and concluded that STEM outperformed, in general, in terms of power when the FDR was set to be 5%.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.5
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• pp.17-24
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• 2010

Recently the study of identifying bio-markers for disease diagnosis and prognosis has been actively performed. In particular, lots of attentions have been paid to the finding of pathway gene-sets differentially expressed in disease patients rather than the finding of individual gene markers. In this paper we propose a novel method to identify disease-related pathway gene-sets based on time-series microarray data. For this purpose, we firstly compute individual gene scores by the using maSigPro (microarray Significant Profiles) and then arrange all the genes in the decreasing order of the corresponding gene scores. The rank of each gene in the entire list is used to evaluate the statistical significance of candidate gene-sets with Wilcoxson rank sum test. For the generation of candidate gene-sets, MSigDB (Molecular Signatures Database) pathway information has been employed. The experiment was conducted with prostate cancer time-series microarray data and the results showed the usefulness of the proposed method by correctly identifying 6 out of 7 biological pathways already known as being actually related to prostate cancer.

• Progress in Medical Physics
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• v.25 no.4
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• pp.242-247
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• 2014

To see the discrepancies between the calculated and the delivered dose distribution of IMRT fields for respiratory-induced moving target according to the motion ranges. Four IMRT plans in which there are five fields, for lung and liver patients were selected. The gantry angles were set to $0^{\circ}$ for every field and recalculated using TPS (Eclipse Ver 8.1, Varian Medical Systems, Inc., USA). The ion-chamber array detector (MatriXX, IBA Dosimetry, Germany) was placed on the respiratory simulating platform and made it to move with ranges of 1, 2, and 3 cm, respectively. The IMRT fields were delivered to the detector with 30~70% gating windows. The comparison was performed by gamma index with tolerance of 3 mm and 3%. The average pass rate was 98.63% when there's no motion. When 1.0, 2.0, 3.0 cm motion ranges were simulated, the average pass rate were 98.59%, 97.82%, and 95.84%, respectively. Therefore, ITV margin should be increased or gating windows should be decreased for targets with large motion ranges.