• The Journal of the Korea Contents Association
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• v.10 no.4
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• pp.19-27
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• 2010

In recent years, high-throughput genome-wide RNA interference screening is emerging as an essential tool to biologists in understanding complex cellular processes. The manual analysis of the large number of images produced in each study spends much time and the labor. Hence, automatic cellular image analysis becomes an urgent need, where segmentation is the first and one of the most important steps. However, those factors such as the region overlapping, a variety of shapes, and non-uniform local characteristics of cellular images become obstacles to efficient cell segmentation. To avoid the problem, a new watershed-based cell segmentation algorithm using a localized segmentation method and a feature vector is proposed in this paper. Localized approach in segmentation resolves the problems caused by a variety of shapes and non-uniform characteristics. In addition, the poor performance of segmentation in overlapped regions can be improved by taking advantage of a feature vector whose component features complement each other. Simulation results show that the proposed method improves the segmentation performance compared to the method in Cellprofiler.

• KSBB Journal
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• v.22 no.6
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• pp.393-400
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• 2007

Analysis of protein interactions/functions in a microarray format has been of great potential in drug discovery, diagnostics, and cell biology, because it is amenable to large-scale and high-throughput biological assays in a rapid and economical way. In recent years, the protein microarray have broaden their utility towards the global analysis of protein interactions on a proteome scale, the functional activity analysis based on protein interactions and post-translational modifications (PTMs), and the discovery of biomarkers through profiling of protein expression between sample and reference pool. As a promising tool for proteomics, the protein microarray technology has advanced outstandingly over the past decade in terms of surface chemistry, acquisition of relevant proteins on a proteomic level, and detection methods. In this article, we briefly describe various techniques for development of protein microarray, and introduce developmental state of protein microarray and its applications.

• Molecules and Cells
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• v.23 no.2
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• pp.170-174
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• 2007

High-throughput subcellular imaging is a powerful tool for investigating the function of genes. In order to identify novel regulators of apoptosis we transiently transfected HeLa cells with 938 hypothetical genes of unknown function, and captured their nuclear images with an automated fluorescence microscope. We selected genes that induced greater than 3-fold increase in the percentage of apoptotic nuclei compared with vector-transfected cells. The full-length genes C10orf61, MGC 26717, and FLJ13855 were identified as candidate proapoptotic genes, and their apoptotic effects were confirmed by DNA fragmentation ELISAs and Western blotting for caspase-7 and PARP. We conclude that a subcellular image-based apoptotic screen is useful for identifying genes with proapoptotic activity.

• Molecules and Cells
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• v.44 no.3
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• pp.127-135
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• 2021

Since the introduction of RNA sequencing (RNA-seq) as a high-throughput mRNA expression analysis tool, this procedure has been increasingly implemented to identify cell-level transcriptome changes in a myriad of model systems. However, early methods processed cell samples in bulk, and therefore the unique transcriptomic patterns of individual cells would be lost due to data averaging. Nonetheless, the recent and continuous development of new single-cell RNA sequencing (scRNA-seq) toolkits has enabled researchers to compare transcriptomes at a single-cell resolution, thus facilitating the analysis of individual cellular features and a deeper understanding of cellular functions. Nonetheless, the rapid evolution of high throughput single-cell "omics" tools has created the need for effective hypothesis verification strategies. Particularly, this issue could be addressed by coupling cell engineering techniques with single-cell sequencing. This approach has been successfully employed to gain further insights into disease pathogenesis and the dynamics of differentiation trajectories. Therefore, this review will discuss the current status of cell engineering toolkits and their contributions to single-cell and genome-wide data collection and analyses.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.2
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• pp.167-172
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• 2012

In biology the advent of the high-throughput technology for sequencing, probing, or screening has produced huge volume of data which could not be manually handled. Biologists have resorted to software tools in order to effectively handle them. This paper introduces a bioinformatics tool to help biologists find potentially interesting pathway maps from a transcriptome data set in which the expression levels of genes are described for both case and control samples. The tool accepts a transcriptome data set, and then selects and categorizes some of genes into four classes using a fuzzy filtering technique where classes are defined by membership functions. It collects and edits the pathway maps related to those selected genes without analyst' intervention. It invokes a sequence of web service functions from KEGG, which an online pathway database system, in order to retrieve related information, locate pathway maps, and manipulate them. It maintains all retrieved pathway maps in a local database and presents them to the analysts with graphical user interface. The tool has been successfully used in identifying target genes for further analysis in transcriptome study of human cytomegalovirous. The tool is very helpful in that it can considerably save analysts' time and efforts by collecting and presenting the pathway maps that contain some interesting genes, once a transcriptome data set is just given.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.1
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• pp.146-170
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• 2017

Joint channel assignment and routing is a well-known problem in multi-radio wireless mesh networks for which optimal configurations is required to optimize the overall throughput and fairness. However, other objectives need to be considered in order to provide a high quality service to network users when it deployed with high traffic dynamic. In this paper, we propose a re-configuration optimization model that optimizes the network throughput in addition to reducing the disruption to the mesh clients' traffic due to the re-configuration process. In this multi-objective optimization model, four objective functions are proposed to be minimized namely maximum link-channel utilization, network average contention, channel re-assignment cost, and re-routing cost. The latter two objectives focus on reducing the re-configuration overhead. This is to reduce the amount of disrupted traffic due to the channel switching and path re-routing resulted from applying the new configuration. In order to adapt to traffic dynamics in the network which might be caused by many factors i.e. users' mobility, a centralized heuristic re-configuration algorithm called State-Aware Joint Routing and Channel Assignment (SA-JRCA) is proposed in this research based on our re-configuration model. The proposed algorithm re-assigns channels to radios and re-configures flows' routes with aim of achieving a tradeoff between maximizing the network throughput and minimizing the re-configuration overhead. The ns-2 simulator is used as simulation tool and various metrics are evaluated. These metrics include channel-link utilization, channel re-assignment cost, re-routing cost, throughput, and delay. Simulation results show the good performance of SA-JRCA in term of packet delivery ratio, aggregated throughput and re-configuration overhead. It also shows higher stability to the traffic variation in comparison with other compared algorithms which suffer from performance degradation when high traffic dynamics is applied.

• Genomics & Informatics
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• v.15 no.3
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• pp.82-86
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• 2017

Chromosomal microarray (CMA) is a high-resolution, high-throughput method of identifying submicroscopic genomic copy number variations (CNVs). CMA has been established as the first-line diagnostic test for individuals with developmental delay (DD), intellectual disability (ID), autism spectrum disorders (ASDs), and multiple congenital anomalies (MCAs). CMA analysis was performed in 42 Korean patients who had been diagnosed with unexplained DD, ID, ASDs, and MCAs. Clinically relevant CNVs were discovered in 28 patients. Variants of unknown significance were detected in 13 patients. The diagnostic yield was high (66.7%). CMA is a superior diagnostic tool compared with conventional karyotyping and fluorescent in situ hybridization.

• Proceedings of the KIEE Conference
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• 2004.07c
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• pp.2128-2130
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• 2004

High throughput analysis using a DNA chip microarray is powerful tool in the post genome era. Less labor-intensive and lower cost-performance is required. Thus, this paper aims to develop the multi-channel type label-free DNA chip and detect SNP (Single nucleotide polymorphisms). At first, we fabricated a high integrated type DNA chip array by lithography technology. Various probe DNAs were immobilized on the microelectrode array. We succeeded to discriminate of DNA hybridization between target DNA and mismatched DNA on microarray after immobilization of a various probe DNA and hybridization of label-free target DNA on the electrodes simultaneously. This method is based on redox of an electrochemical ligand.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.17 no.4
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• pp.410-414
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• 2004

High throughput analysis using a DNA chip microarray is powerful tool in the post genome era. Less labor-intensive and lower cost-performance is required. Thus, this paper aims to develop the multi-channel type label-free DNA chip and detect SNP (Single nucleotide polymorphisms). At first, we fabricated a high integrated type DNA chip array by lithography technology. Various probe DNAs were immobilized on the microelectrode array. We succeeded to discriminate of DNA hybridization between target DNA and mismatched DNA on microarray after immobilization of a various probe DNA and hybridization of label-free target DNA on the electrodes simultaneously. This method is based on redox of an electrochemical ligand.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2006.06a
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• pp.410-411
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• 2006

High throughput analysis using a DNA chip microarray is powerful tool in the post genome era. Less labor-intensive and lower cost-performance is required. Thus, this paper aims to develop the multi-channel type label-free DNA chip and detect SNP (Single nucleotide polymorphisms). At first, we fabricated a high integrated type DNA chip array by lithography technology. Various probe DNAs were immobilized on the microelectrode array. We succeeded to discriminate of DNA hybridization between target DNA and mismatched DNA on microarray after immobilization of a various probe DNA and hybridization of label-free target DNA on. the electrodes simultaneously. This method is based on redox of an electrochemical ligand.