• Genomics & Informatics
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• v.18 no.4
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• pp.46.1-46.4
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• 2020

We developed the BaSDAS (Barcode-Seq Data Analysis System), a GUI-based pooled knockout screening data analysis system, to facilitate the analysis of pooled knockout screen data easily and effectively by researchers with limited bioinformatics skills. The BaSDAS supports the analysis of various pooled screening libraries, including yeast, human, and mouse libraries, and provides many useful statistical and visualization functions with a user-friendly web interface for convenience. We expect that BaSDAS will be a useful tool for the analysis of genome-wide screening data and will support the development of novel drugs based on functional genomics information.

• BMB Reports
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• v.56 no.1
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• pp.43-48
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• 2023

Pre-clinical models are critical in gaining mechanistic and biological insights into disease progression. Recently, patient-derived organoid models have been developed to facilitate our understanding of disease development and to improve the discovery of therapeutic options by faithfully recapitulating in vivo tissues or organs. As technological developments of organoid models are rapidly growing, computational methods are gaining attention in organoid researchers to improve the ability to systematically analyze experimental results. In this review, we summarize the recent advances in organoid models to recapitulate human diseases and computational advancements to analyze experimental results from organoids.

• Communications for Statistical Applications and Methods
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• v.29 no.6
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• pp.655-664
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• 2022

On the motivation by an integrative study of multi-omics data, we are interested in estimating the structure of the sparse cross correlation matrix of two high-dimensional random vectors. We rewrite the problem as a multiple testing problem and propose a new method to estimate the sparse structure of the cross correlation matrix. To do so, we test the correlation coefficients simultaneously and threshold the correlation coefficients by controlling FRD at a predetermined level α. Further, we apply the proposed method and an alternative adaptive thresholding procedure by Cai and Liu (2016) to the integrative analysis of the protein expression data (X) and the mRNA expression data (Y) in TCGA breast cancer cohort. By varying the FDR level α, we show that the new procedure is consistently more efficient in estimating the sparse structure of cross correlation matrix than the alternative one.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.490-492
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• 2023

시퀀싱(sequencing) 기술의 발달로 다양한 오믹스(omics) 데이터의 축적과 인공 지능 기술의 발달로 인하여 다양한 드라이버 유전자 분류기법이 제안되어왔다. 최근에는 암 데이터가 대용량으로 축적되며 기계 학습 기반의 다양한 기법들이 활발히 제안되었다. 특히 다양한 오믹스 데이터를 결합한 고차원 데이터에서 높은 정확도를 확보하기 위한 시도가 활발히 이루어지고 있다. 본 논문에서는 멀티 오믹스와 네트워크 관련 특징을 기반으로 암의 증식 및 발생에 중요한 역할을 하는 드라이버 유전자를 분류하는 딥러닝 모델을 제시한다. 또한 The Cancer Genome Atlas(TCGA) 데이터를 통해서 모델 학습 후 기존 통계 및 머신러닝 기반 기법과 비교하여 성능이 개선되었음을 확인하였다.

• Mass Spectrometry Letters
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• v.14 no.4
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• pp.121-140
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• 2023

It is becoming more and more clear that each cell, even those of the same type, has a unique identity. This sophistication and the diversity of cell types in tissue are what are pushing the necessity for spatially distributed omics at the single-cell (SC) level. Single-cell chemical assessment, which also provides considerable insight into biological, clinical, pharmacodynamic, pathological, and toxicity studies, is crucial to the investigation of cellular omics (genomics, metabolomics, etc.). Mass spectrometry (MS) as a tool to image and profile single cells and subcellular organelles facilitates novel technical expertise for biochemical and biomedical research, such as assessing the intracellular distribution of drugs and the biochemical diversity of cellular populations. It has been illustrated that ambient mass spectrometry (AMS) is a valuable tool for the rapid, straightforward, and simple analysis of cellular and sub-cellular constituents and metabolites in their native state. This short review examines the advances in ambient mass spectrometry (AMS) and ambient mass spectrometry imaging (AMSI) on single-cell analysis that have been authored in recent years. The discussion also touches on typical single-cell AMS assessments and implementations.

• Bioindustry News
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• v.21 no.2
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• pp.4-11
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• 2008

• Proceedings of the Microbiological Society of Korea Conference
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• 2009.05a
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• pp.133-134
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• 2009

• Proceedings of the Korean Society of Toxicology Conference
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• 2005.11a
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• pp.27-38
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• 2005

• The Korea Genome Conference
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• 2003.09a
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• pp.43.2-43.2
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• 2003

• Molecules and Cells
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• v.44 no.11
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• pp.781-783
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• 2021