• Genomics & Informatics
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• v.5 no.1
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• pp.10-18
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• 2007

Numerous studies have reported that genes with similar expression patterns are co-regulated. From gene expression data, we have assumed that genes having similar expression pattern would share similar transcription factor binding sites (TFBSs). These function as the binding regions for transcription factors (TFs) and thereby regulate gene expression. In this context, various analysis tools have been developed. However, they have shortcomings in the combined analysis of expression patterns and significant TFBSs and in the functional analysis of target genes of significantly overrepresented putative regulators. In this study, we present a web-based A Functional Clustering Analysis Tool for Predicted Transcription Regulatory Elements and Gene Ontology Terms (FCAnalyzer). This system integrates microarray clustering data with similar expression patterns, and TFBS data in each cluster. FCAnalyzer is designed to perform two independent clustering procedures. The first process clusters gene expression profiles using the K-means clustering method, and the second process clusters predicted TFBSs in the upstream region of previously clustered genes using the hierarchical biclustering method for simultaneous grouping of genes and samples. This system offers retrieved information for predicted TFBSs in each cluster using $Match^{TM}$ in the TRANSFAC database. We used gene ontology term analysis for functional annotation of genes in the same cluster. We also provide the user with a combinatorial TFBS analysis of TFBS pairs. The enrichment of TFBS analysis and GO term analysis is statistically by the calculation of P values based on Fisher’s exact test, hypergeometric distribution and Bonferroni correction. FCAnalyzer is a web-based, user-friendly functional clustering analysis system that facilitates the transcriptional regulatory analysis of co-expressed genes. This system presents the analyses of clustered genes, significant TFBSs, significantly enriched TFBS combinations, their target genes and TFBS-TF pairs.

• Journal of Information Processing Systems
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• v.12 no.1
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• pp.1-34
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• 2016

Gene identification is at the center of genomic studies. Although the first phase of the Encyclopedia of DNA Elements (ENCODE) project has been claimed to be complete, the annotation of the functional elements is far from being so. Computational methods in gene identification continue to play important roles in this area and other relevant issues. So far, a lot of work has been performed on this area, and a plethora of computational methods and avenues have been developed. Many review papers have summarized these methods and other related work. However, most of them focus on the methodologies from a particular aspect or perspective. Different from these existing bodies of research, this paper aims to comprehensively summarize the mainstream computational methods in gene identification and tries to provide a short but concise technical reference for future studies. Moreover, this review sheds light on the emerging trends and cutting-edge techniques that are believed to be capable of leading the research on this field in the future.

• Proceedings of the Korean Society of Developmental Biology Conference
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• 2001.10a
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• pp.18-24
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• 2001

To identify genes implicated in the control of pluripotency as well as characteristics of stem cells, we analyzed expression profiles of genes derived from mouse morulas, blastocysts, embryonic stem cells, mesenchymal stem cells, and uterus tissue cDNA microarray. Comparative analyses of their expression profiles identified putative clones that expressed specifically in specific samples or not in a specific sample. The expression pattern of these candidate clones was analyzed using RT-PCR and non-radioactive in situ hybridization. Functional annotation of these clones on pluripotency and stem cells and molecular mechanisms underlying many facets of mammalian development and differentiation.

• Proceedings of the Korean Society of Embryo Transfer Conference
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• 2001.05a
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• pp.12-21
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• 2001

To identify genes implicated in the control of pluripotency as well as characteristics of stem cells, we analyzed expression profiles of genes derived from mouse morulas, blastocysts, embryonic stem cells, mesenchymal stem cells, and uterus tissue using cDNA microarray. Comparative analyses of their expression profiles identified putative clones that expressed specifically in specific samples or not in a specific sample. The expression pattern of these condidate clones was analyzed using RT-PCR and non-radioactive in situ hybridization. Functional annotation of these clones on pluripotency and stem cell plasticity is in ongoing. These studies may further our understanding on the nature of the stem cells and molecular mechanisms underlying many facets of mammalian development and differentiation.

• The Plant Pathology Journal
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• v.30 no.4
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• pp.425-431
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• 2014

Leaf scald caused by the infection of Rhynchosporium secalis, is a worldwide crop disease resulting in significant loss of barley yield. In this study, a systematic sequencing of expressed sequence tags (ESTs) was chosen to obtain a global picture of the assembly of genes involved in pathogenesis. To identify a large number of plant ESTs, which are induced at different time points, an amplified fragment length polymorphism (AFLP) display of complementary DNA (cDNA) was utilized. Transcriptional changes of 140 ESTs were observed, of which 19 have no previously described function. Functional annotation of the transcripts revealed a variety of infection-induced host genes encoding classical pathogenesis-related (PR) or genes that play a role in the signal transduction pathway. The expression analyses by a semi-quantitative reverse transcription polymerase chain reaction (RT-PCR) revealed that Rar1 and Rpg4 are defense inducible genes, and were consistent with the cDNA-AFLP data in their expression patterns. Hence, the here presented transcriptomic approach provides novel global catalogue of genes not currently represented in the EST databases.

• BMB Reports
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• v.44 no.9
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• pp.578-583
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• 2011

Aspartate aminotransferase (AST) and alanine aminotransferase (ALT) are biochemical markers used to test for liver diseases. Copy number variation (CNV) plays an important role in determining complex traits and is an emerging area in the study various diseases. We performed a genome-wide association study with liver function biomarkers AST and ALT in 407 unrelated Koreans. We assayed the genome-wide variations on an Affymetrix Genome-Wide 6.0 array, and CNVs were analyzed using HelixTree. Using single linear regression, 32 and 42 CNVs showed significance for AST and ALT, respectively (P value < 0.05). We compared CNV-based genes between the current study (KARE2; AST-140, ALT-172) and KARE1 (AST-1885, ALT-773) using NetBox. Results showed 9 genes (CIDEB, DFFA, PSMA3, PSMC5, PSMC6, PSMD12, PSMF1, SDC4, and SIAH1) were overlapped for AST, but no overlapped genes were found for ALT. Functional gene annotation analysis shown the proteasome pathway, Wnt signaling pathway, programmed cell death, and protein binding.

• Korean Journal of Microbiology
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• v.39 no.2
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• pp.67-75
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• 2003

One large topic in comparative genomics is to predict functional annotation by classifying protein sequences. Computational approaches for function prediction include protein structure prediction, sequence alignment and domain prediction or binding site prediction. This paper is on another computational approach searching for sets of homologous sequences from sequence similarity graph. Methods based on similarity graph do not need previous knowledges about sequences, but largely depend on the researcher's subjective threshold settings. In this paper, we propose a genome sequence clustering method of iterative testing and graph decomposition, and a simple method to calculate a strict threshold having biochemical meaning. Proposed method was applied to known bacterial genome sequences and the result was shown with the BAG algorithm's. Result clusters are lacking some completeness, but the confidence level is very high and the method does not need user-defined thresholds.

• Proceedings of the KSAR Conference
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• 2001.10a
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• pp.18-24
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• 2001

To identify genes implicated in the control of pluripotency as well as characteristics of stem cells, we analyzed expression profiles of genes derived from mouse morulas, blastocysts, embryonic stem cells, mesenchymal stem cells, and uterus tissue using cDNA microarray. Comparative analyses of their expression profiles identified putative clones that expressed specifically in specific samples or not in a specific sample. The expression pattern of these candidate clones was analyzed using RT-PCR and non-radioactive in situ hybridization. Functional annotation of these clones on pluripotency and stem cell plasticity is in ongoing. These studies may further our understanding on the nature of the stem cells and molecular mechanisms underlying many facets of mammalian development and differentiation.

• Genomics & Informatics
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• v.9 no.4
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• pp.197-199
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• 2011

The biological interpretation of two-dimensional (2D) gel electrophoresis experiments is a key step toward understanding the functions of biological systems. We here present a web-based integrated database, called 2DSpotDB, for the management of proteome data derived from several pathogens. The 2DSpotDB was established as a part of the management of a pathogen proteome project at the Korea National Institute of Health. The goals of the 2DSpotDB implementation are to store and define important pathogen genes, retrieve information obtained by 2D polyacrylamide gel electrophoresis and mass spectrometry, and create an integrated system to provide pathogen proteome information for biological scientists. This database currently contains 14 gels and information on 387 protein spots, among which 329 proteins were identified and annotated.

• Genomics & Informatics
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• v.9 no.4
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• pp.161-172
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• 2011

Angiogenesis is regulated by a large number of molecules and complex signaling mechanisms. The G protein $G{\alpha}_{13}$ is a part of this signaling mechanism as an endothelial cell movement regulator. Gene expression analysis of $G{\alpha}_{13}$ knockout mouse embryos was carried out to identify the role of $G{\alpha}_{13}$ in angiogenesis signaling during embryonic development. Hypoxia-inducible response factors including those acting as regulators of angiogenesis were over expressed, while genes related to the cell cycle, DNA replication, protein modification and cell-cell dissociation were under expressed. Functional annotation and network analysis indicate that $G{\alpha}_{13}{^{-/-}}$ embryonic mice were exposed to hypoxic conditions. The present analysis of the time course highlighted the significantly high levels of disorder in the development of the cardiovascular system. The data suggested that hypoxia-inducible factors including those associated with angiogenesis and abnormalities related to endothelial cell division contributed to the developmental failure of $G{\alpha}_{13}$ knockout mouse embryos.