• Natural Product Sciences
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• v.26 no.3
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• pp.183-190
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• 2020

Genome mining has recently emerged as a powerful strategy to discover novel microbial secondary metabolites. However, more than 50% of biosynthetic gene clusters are not transcribed under standardized laboratory culture condition. Several methods have been applied to activate silent biosynthetic gene clusters in the microbes so far. Among the regulatory systems for production of secondary metabolites, global regulators, which affect transcription of genes through regulatory cascades, typically govern the production of small molecules. In this review, global regulators to affect production of microbial secondary metabolites were discussed.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.89.5-89
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• 2002

The technology to predict new chemical compounds by using properties of already known compounds is a kind of data mining and an important technology in chemical industrial fields. Many knowledge have been accumulated in the fields, and especially nowadays in the field of medicine development industry, the technology is connected with the post genome technology, and generates a new conception, physiome. The word is defined as followings. It is the quantitative and integrated description of the functional behavior of the physiological state of an individual or species. The physiome describes the physiological of the normal intact organism and is built on information and structure, that is geno...

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.7
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• pp.1236-1241
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• 2016

Cancer has been the most frequent in Korea, and pathogenesis and progression of cancer have been known to be occurred through various causes and stages. Recently, the research of chromosomal and genetic disorder and the research about prognostic factor to predict occurrence, recurrence and progress of chromosomal and genetic disorder have been performed actively. In this paper, we analyzed DNA methylation data downloaded from TCGA (The Cancer Genome Atlas), open database, to research bladder cancer which is the most frequent among urinary system cancers. Using three level of methylation data which had the most preprocessing, 59 candidate CpG island were extracted from 480,000 CpG island, and then we analyzed extracted CpG island applying data mining technique. As a result, cg12840719 CpG island were analyzed significant, and in Cox's regression we can find the CpG island with high relative risk in comparison with other CpG island. Shown in the result of classification analysis, the CpG island which have high correlation with bladder cancer are cg03146993, cg07323648, cg12840719, cg14676825 and classification accuracy is about 76%. Also we found out that positive predictive value, the probability which predicts cancer in case of cancer was 72.4%. Through the verification of candidate CpG island from the result, we can utilize this method for diagnosing and treating cancer.

• Genomics & Informatics
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• v.14 no.4
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• pp.255-264
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• 2016

The plethora of genome sequence information of bacteria in recent times has ushered in many novel strategies for antibacterial drug discovery and facilitated medical science to take up the challenge of the increasing resistance of pathogenic bacteria to current antibiotics. In this study, we adopted subtractive genomics approach to analyze the whole genome sequence of the Fusobacterium nucleatum, a human oral pathogen having association with colorectal cancer. Our study divulged 1,499 proteins of F. nucleatum, which have no homolog's in human genome. These proteins were subjected to screening further by using the Database of Essential Genes (DEG) that resulted in the identification of 32 vitally important proteins for the bacterium. Subsequent analysis of the identified pivotal proteins, using the Kyoto Encyclopedia of Genes and Genomes (KEGG) Automated Annotation Server (KAAS) resulted in sorting 3 key enzymes of F. nucleatum that may be good candidates as potential drug targets, since they are unique for the bacterium and absent in humans. In addition, we have demonstrated the three dimensional structure of these three proteins. Finally, determination of ligand binding sites of the 2 key proteins as well as screening for functional inhibitors that best fitted with the ligands sites were conducted to discover effective novel therapeutic compounds against F. nucleatum.

• Genomics & Informatics
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• v.20 no.3
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• pp.26.1-26.19
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• 2022

Diabetes and its related complications are associated with long term damage and failure of various organ systems. The microvascular complications of diabetes considered in this study are diabetic retinopathy, diabetic neuropathy, and diabetic nephropathy. The aim is to identify the weighted co-expressed and differentially expressed genes (DEGs), major pathways, and their miRNA, transcription factors (TFs) and drugs interacting in all the three conditions. The primary goal is to identify vital DEGs in all the three conditions. The overlapped five genes (AKT1, NFKB1, MAPK3, PDPK1, and TNF) from the DEGs and the co-expressed genes were defined as key genes, which differentially expressed in all the three cases. Then the protein-protein interaction network and gene set linkage analysis (GSLA) of key genes was performed. GSLA, gene ontology, and pathway enrichment analysis of the key genes elucidates nine major pathways in diabetes. Subsequently, we constructed the miRNA-gene and transcription factor-gene regulatory network of the five gene of interest in the nine major pathways were studied. hsa-mir-34a-5p, a major miRNA that interacted with all the five genes. RELA, FOXO3, PDX1, and SREBF1 were the TFs interacting with the major five gene of interest. Finally, drug-gene interaction network elucidates five potential drugs to treat the genes of interest. This research reveals biomarker genes, miRNA, TFs, and therapeutic drugs in the key signaling pathways, which may help us, understand the processes of all three secondary microvascular problems and aid in disease detection and management.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.30-30
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• 2022

Philippines is the second world supplier of coconut by-products. As its first major genomics project, the Philippine Genome Center program for Agriculture (PGC-Agriculture) took the challenge to sequence and assemble the whole coconut genome. The project aims to provide advance genetics tools for our collaborating coconut researchers while taking the opportunity to initiate local capacity. Combination of different NGS platforms was explored and the Philippine 'Catigan Green Dwarf' (CATD) variety was selected with the breeders to be the crop's reference genome. A high quality genome assembly of CATD was generated and used to characterize important genes of coconut towards the development of resilient and outstanding varieties especially for added high-value traits. The talk will present the significant results of the project as published in various papers including the first report of whole genome sequence of a dwarf coconut variety. Updates will include the challenges hurdled and specific applications such as gene mining for host insect resistance and screening for least damaged coconuts (thus potentially insect resistant varieties). Genome-wide DNA markers as published and genes related to coconut oil qualitative/quantitative traits will also be presented, including initial molecular/biochemical studies that support nutritional and medicinal claims. A web-based genome database is currently built for ease access and wider utility of these genomics tools. Indeed, a major milestone accomplished by the coconut genomics research team, which was facilitated with the all-out government support and strong collaboration among multidisciplinary experts and partnership with advance research institutes.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.10a
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• pp.328-332
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• 2000

As DNA sequences have been known through the Genome project the techniques for dealing with molecule-level gene information are being made researches briskly. It is also urgent to develop new computer algorithms for making databases and analyzing it efficiently considering the vastness of the information for known sequences. In this respect, this paper studies the association rule search algorithms for finding out the characteristics shown by means of the association between promoter sequences and genes, which is one of the important research areas in molecular biology. This paper treat biological data, while previous search algorithms used transaction data. So, we design a transformed association nile algorithm that covers data types and biological properties. These research results will contribute to reducing the time and the cost for biological experiments by minimizing their candidates.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.114-114
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• 2017

The aim of this research is to improve Korean lettuce varieties in terms of Fusarium wilt, bolting under hot weather and nutritional function applying genomics approaches. To find related gene/molecular markers, we selected 96 lettuce varieties which are popular in domestic fresh vegetable markets. To construct frame works of the genomic approaches, we exploited GBS(Genotyping by Sequencing) and found total 61,407 SNPs from lettuce whole genomes (MAF>0.02). We observed that Three SNPs array per 100kb of lettuce genome. Average LD decay is expected to expand up to 3.9M(million)bp. Thus, we concluded that about 104 SNPs exist within a LD, which is sufficient to use GWAS(Genome-wide Association Study) to explore the useful gene/molecular markers. In addition, we optimized mass screening method to evaluate disease resistance levels against Fusarium wilt and are testing the bolting sensitivity during summer growing season for those lettuce allele mining set.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.4
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• pp.739-744
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• 2000

As DNA sequences have been known through the Genome project the techniques for dealing with molecule-level gene information are being made researches briskly. It is also urgent to develop new computer algorithms for making databases and analyzing it efficiently considering the vastness of the information for known sequences. In this respect, this paper studies the association rule search algorithms for finding out the characteristics shown by means of the association between promoter sequences and genes, which is one of the important research areas in molecular biology. This paper treat biological data, while previous search algorithms used transaction data. So, we design a transformed association rule algorithm that covers data types and biological properties. These research results will contribute to reducing the time and the cost for biological experiments by minimizing their candidates.

• Journal of Pharmaceutical Investigation
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• v.34 no.1
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• pp.73-79
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• 2004

The union of information-technology and biology presents great possibilities to both applications of bio-information and development of science and technology. Also, meaningful analysis of bio-information brings about a new innovation in the field of bio-market with the advent and growth of bioinformatics. Hence, bioinformatics is the most import aspect for establishing a science-technology-oriented society in the $21^{st}$ century. This article provides trends in current state of bioinformatics. Technological development of bioinformatics for the rapid growth of bio-industry means that using bioinformatics, a biologist can process and store enormous amount of data such as current Human Genome Project and future data in the field of biology. We have manly looked at the tends of bio-information, databases and mining tools that are generally used, and strategies and directions for the future.