• Journal of the Korea Society for Simulation
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• v.22 no.4
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• pp.139-147
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• 2013

This paper proposes a novel method for feature selection for mass spectrometric proteomic data based on Random Forest. The method includes an effective preprocessing step to filter a large amount of redundant features with high correlation and applies a tournament strategy to get an optimal feature subset. Experiments on three public datasets, Ovarian 4-3-02, Ovarian 7-8-02 and Prostate shows that the new method achieves high performance comparing with widely used methods and balanced rate of specificity and sensitivity.

• The Korea Genome Conference
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• 2006.09a
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• pp.41-41
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• 2006

• Journal of the Korean Chemical Society
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• v.7 no.2
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• pp.165-169
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• 1963

12 samples from an assay process chain were submitted to qualitative and quantitative neutron activation analysis for the determination of gold. Gold was detected and quantitatively determined in three samples after a chemical separation consisting of solvent extraction and precipitation steps. Recoveries ranged between 81.0 and 93.6% and results of duplicated determinations were reproducible. Quantitative data were obtained from gamma-spectrometric photopeak-area counting. Interference from fast neutron reactions was negligible.

• Geophysics and Geophysical Exploration
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• v.19 no.4
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• pp.179-186
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• 2016

Data leveling utilizing baseline survey makes existing old data be smoothly compiled, and also keep characteristics of data, such as small high frequency anomaly information. The previously proposed leveling method may easily loose or damage the original characteristics of the data. This paper suggests a new leveling method. New method determines the leveling coefficients using regional field of the original data, which is composed by data on the grids point coincided with baseline survey grid, while existing method uses all grid data without any considerations. Results of new leveling method on test area shows that new method make two data sets compiled more smoothly and trends of data distribution expressed more clearly. And then, it also preserves high frequency information well.

• Journal of Biosystems Engineering
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• v.33 no.1
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• pp.63-68
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• 2008

This study was carried out to find a useful method to predict hardness of tomato using optical spectrum data. Optical spectrum of reflectance and transmittance data were collected processed by 9 kind of preprocessing methods-normalizations of mean, maximum and range, SNV (standard normal variate), MSC (multiplicative scatter correction), the first derivative and second derivative of Savitzky-Golay and Norris-Gap. With the preprocessed and non-processed original spectrum data, prediction models of hardness of tomato were developed using analytical tools of PLS (partial least squares) and MLR (multiple linear regression) and tested for their validation. The test of validation resulted that the analytical tools of PLS and MLR output similar performances while the transmittance spectra showed much better result than the reflectance spectra.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.313-318
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• 2005

Estimating the reliability of protein-protein interaction data sets obtained by high-throughput technologies such as yeast two-hybrid assays and mass spectrometry is of great importance. We develop a maximum likelihood estimation method that uses both protein localization and gene expression data to estimate the reliability of protein interaction data sets. By integrating protein localization data and gene expression data, we can obtain more accurate estimates of the reliability of various interaction data sets. We apply the method to protein physical interaction data sets and protein complex data sets. The reliability of the yeast two-hybrid interactions by Ito et al. (2001) is 27%, and that by Uetz et at.(2000) is 68%. The reliability of the protein complex data sets using tandem affinity purification-mass spec-trometry (TAP) by Gavin et at. (2002) is 45%, and that using high-throughput mass spectrometric protein complex identification (HMS-PCI) by Ho et al. (2002) is 20%. The method is general and can be applied to analyze any protein interaction data sets.

• Geophysics and Geophysical Exploration
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• v.14 no.1
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• pp.116-120
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• 2011

Radioelement ratios are useful for mapping subtle variations in radiometric signatures in map data. But the conventional method for calculating radioelement ratios has the significant limitation that if just one of the radioelements comprising the ratio has a small spread of concentration estimates relative to its mean, then it will not contribute significantly to the ratio map. However, if both the numerator and denominator are first normalised to approximately the same mean and spread prior to ratioing, then they will contribute equally to the enhancement of the differences between them across the map area.

• Journal of the Korean Chemical Society
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• v.22 no.3
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• pp.138-148
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• 1978

A discussion of the various theories of natural diamond formation is given. Experimental data from mass spectrometric analysis of included gases is related to theoretical data on the carbon-hydrogen-oxygen gas phase under geologic conditions.Possible temperature-pressure conditions for natural diamond formation are proposed.

• Mass Spectrometry Letters
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• v.12 no.3
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• pp.81-84
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• 2021

Collagen, which accounts for one-third of human protein, is reduced due to human aging, and much attention is focused on making collagen into food to prevent such aging. Gel permeation chromatography with Reflective Index (RI) detection (GPC/RI) was chosen as the most suitable instrument to confirm molecular weight distribution, and we explored the use of this technique for analysis of collagen peptide molecular sizes and distributions. Data reliability was verified by matrix-assisted laser desorption/ionization coupled to time-of-flight (MALDI-TOF) mass spectrometric analysis. The data were considered meaningful for comparative analysis of molecular weight distribution patterns.

• Bulletin of the Korean Chemical Society
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• v.35 no.3
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• pp.845-850
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• 2014

The rapid development of shotgun proteomics is paving the way for extensive proteome profiling, while providing extensive information on various post translational modifications (PTMs) that occur to a proteome of interest. For example, the current phosphoproteomic methods can yield more than 10,000 phosphopeptides identified from a proteome sample. Despite these developments, it remains a challenging issue to pinpoint the true phosphorylation sites, especially when multiple sites are possible for phosphorylation in the peptides. We developed the Phospho-UMC filter, which is a simple method of localizing the site of phosphorylation using unique mass classes (UMCs) information to differentiate phosphopeptides with different phosphorylation sites and increase the confidence in phosphorylation site localization. The method was applied to large scale phosphopeptide profiling data and was demonstrated to be effective in the reducing ambiguity associated with the tandem mass spectrometric data analysis of phosphopeptides.