Kunsoo Park
Seoul National University · Computer Science
About the Lab
Professor Kunsoo Park's research lab specializes in high-performance computing and computational biology, focusing on the development of advanced algorithms and mathematical models for interpreting complex mass spectrometry data. The lab explores efficient parallel computing techniques, particularly leveraging GPU-accelerated architectures, to solve computationally intensive problems in bioinformatics and cryptography. Key research directions include isotopic peak detection in high-resolution mass spectra and the optimization of time-memory trade-off methods such as the rainbow table for cryptographic applications. The lab bridges theoretical modeling with practical implementation on heterogeneous computing systems to enable faster and more accurate data analysis in life sciences and cybersecurity.
Research Overview
Research Output Trend
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Selected Papers
15Determining isotopic clusters and their monoisotopic masses is a first step in interpreting complex mass spectra generated by high-resolution mass spectrometers. We propose a mathematical model for isotopic distributions of polypeptides and an effective interpretation algorithm. Our model uses two types of ratios: intensity ratio of two adjacent peaks and intensity ratio product of three adjacent peaks in an isotopic distribution. These ratios can be approximated as simple functions of a polypep
BACKGROUND: Protein quantification is an essential step in many proteomics experiments. A number of labeling approaches have been proposed and adopted in mass spectrometry (MS) based relative quantification. The mTRAQ, one of the stable isotope labeling methods, is amine-specific and available in triplex format, so that the sample throughput could be doubled when compared with duplex reagents. METHODS AND RESULTS: Here we propose a novel data analysis algorithm for peptide quantification in trip
Research Areas
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