Hyunsoo Kim
Sungkyunkwan University · Medicine
About the Lab
Professor Hyunsoo Kim's research lab specializes in computational biology, bioinformatics, and biomedical data science, focusing on developing advanced algorithms and statistical methods for high-dimensional 'omics' data analysis. The lab emphasizes sparse and non-negative matrix factorization for pattern recognition in gene expression and imaging data, as well as innovative imputation techniques for handling missing values in biological datasets. A key research direction involves biomarker discovery in hepatocellular carcinoma through integrative analysis of genomic and proteomic data, complemented by targeted mass spectrometry validation. The lab also explores medical imaging applications, particularly PET/CT and MRI, for improved cancer diagnosis and therapy monitoring.
Research Overview
Research Output Trend
Figures are computed from collected data and may differ slightly.
Selected Papers
15MOTIVATION: Many practical pattern recognition problems require non-negativity constraints. For example, pixels in digital images and chemical concentrations in bioinformatics are non-negative. Sparse non-negative matrix factorizations (NMFs) are useful when the degree of sparseness in the non-negative basis matrix or the non-negative coefficient matrix in an NMF needs to be controlled in approximating high-dimensional data in a lower dimensional space. RESULTS: In this article, we introduce a n
MOTIVATION: Gene expression data often contain missing expression values. Effective missing value estimation methods are needed since many algorithms for gene expression data analysis require a complete matrix of gene array values. In this paper, imputation methods based on the least squares formulation are proposed to estimate missing values in the gene expression data, which exploit local similarity structures in the data as well as least squares optimization process. RESULTS: The proposed loc
The use of covalent inhibitors in the field of drug discovery has attracted considerable attention in the 2000s. As a result, more than 50 covalent drugs are currently on the market, and numerous covalent drug candidates are now under development. Therefore, interest in covalent drugs is expected to continue in the future. The purpose of this focused review is to provide an understanding of the development of covalent inhibitors by describing their inherent characteristics, possibilities, and li
Screening can effectively reduce mortality and morbidity in some diseases. In Korea, a practical national screening program for chronic disease was launched in 1995 and several problems were discussed. The program focused primarily on disease detection without follow-up care. In addition, the test items were uniform regardless of subject's age, sex, or risk factors; and people with low socioeconomic status were excluded. To improve the quality of program, a new national screening program called
Hepatocellular carcinoma (HCC) is one of the most common and aggressive cancers and is associated with a poor survival rate. Clinically, the level of alpha-fetoprotein (AFP) has been used as a biomarker for the diagnosis of HCC. The discovery of useful biomarkers for HCC, focused solely on the proteome, has been difficult; thus, wide-ranging global data mining of genomic and proteomic databases from previous reports would be valuable in screening biomarker candidates. Further, multiple reaction
Positron emission tomography / computed tomography (PET/CT), with its metabolic data of (18) F-fluorodeoxyglucose (FDG) cellular uptake in addition to morphologic CT data, is an established technique for staging of lung cancer and has higher sensitivity and accuracy for lung nodule characterization than conventional approaches. Its strength extends outside the chest, with unknown metastases detected or suspected metastases excluded in a significant number of patients. Lastly, PET/CT is used in t
Common CT findings of M massiliense diseases overlap with those of M abscessus disease. However, responses to antibiotic treatment are much different; in M massiliense disease, negative sputum conversion is accomplished in all patients and serial CT scans show improvement in most patients.
Current construction hazard identification mostly relies on safety managers’ ability to identify hazards using their prior knowledge about them. Consequently, numerous latent hazards remain unidentified, which poses significant risks to construction workers. To advance current hazard identification capabilities, this study examines the feasibility of harnessing and analyzing collective patterns of workers’ bodily responses (balance, gait, etc.) to identify safety hazards on a jobsite. To test th
INTRODUCTION: The reported mortality rates range from 28% to 100% in burn patients who develop acute kidney injury (AKI) and from 50% to 100% among such patients treated with renal replacement therapy. Recently, the serum cystatin C and plasma and urine neutrophil gelatinase-associated lipocalin (NGAL) levels have been introduced as early biomarkers for AKI; the levels of these biomarkers are known to increase 24 to 48 hours before the serum creatinine levels increase. In this study, we aimed to
PURPOSE: To investigate the changes in apparent diffusion coefficients (ADCs) in cervical cancer patients receiving concurrent chemoradiotherapy (CCRT), and to assess the relationship between tumor ADCs or changes in tumor ADCs and final tumor responses to therapy. MATERIALS AND METHODS: Twenty-four patients with cervical cancer who received CCRT were examined with 3 Tesla (T) MRI including diffusion-weighted imaging (DWI). All patients had three serial MR examinations: before therapy (pre-Tx);
Mass spectrometry (MS) has revolutionized clinical chemistry, offering unparalleled capabilities for biomolecule analysis. This review explores the growing significance of mass spectrometry (MS), particularly when coupled with liquid chromatography (LC), in identifying disease biomarkers and quantifying biomolecules for diagnostic and prognostic purposes. The unique advantages of MS in accurately identifying and quantifying diverse molecules have positioned it as a cornerstone in personalized-me
Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related death, necessitating the discovery of serum markers for its early detection. In this study, a total of 180 serum samples from liver cirrhosis (LC), hepatocellular carcinoma (HCC) patients and paired samples of HCC patients who recovered (Recovery) were analyzed by multiple reaction monitoring-mass spectrometry (MRM-MS) to verify biomarkers. The three-fold crossvalidation was repeated 100 times in the training and test se
BACKGROUND: agglutinin-reactive fraction of α-fetoprotein (AFP-L3) is a serum biomarker for hepatocellular carcinoma (HCC). AFP-L3 is typically measured by liquid-phase binding assay (LiBA). However, LiBA does not always reflect AFP-L3 concentrations because of its low analytical sensitivity. Thus, we aimed to develop an analytically sensitive multiple reaction monitoring-mass spectrometry (MRM-MS) assay to quantify AFP-L3 in serum. METHODS: agglutinin lectin, deglycosylation, trypsin digestion,
Research Areas
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