• Biomolecules & Therapeutics
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• 제29권6호
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• pp.582-595
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• 2021

Researchers have endeavored to identify the etiology of inflammatory bowel diseases, including Crohn's disease and ulcerative colitis. Though the pathogenesis of inflammatory bowel diseases remains unknown, dysregulation of the immune system in the host gastrointestinal tract is believed to be the major causative factor. Omics is a powerful methodological tool that can reveal biochemical information stored in clinical samples. Lipidomics is a subset of omics that explores the lipid classes associated with inflammation. One objective of the present systematic review was to facilitate the identification of biochemical targets for use in future lipidomic studies on inflammatory bowel diseases. The use of high-resolution mass spectrometry to observe alterations in global lipidomics might help elucidate the immunoregulatory mechanisms involved in inflammatory bowel diseases and discover novel biomarkers for them. Assessment of the characteristics of previous clinical trials on inflammatory bowel diseases could help researchers design and establish patient selection and analytical method criteria for future studies on these conditions. In this study, we curated literature exclusively from four databases and extracted lipidomics-related data from literature, considering criteria. This paper suggests that the lipidomics approach toward research in inflammatory bowel diseases can clarify their pathogenesis and identify clinically valuable biomarkers to predict and monitor their progression.

• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2018년도 춘계 종합학술대회 논문집
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• pp.541-542
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• 2018

We performed improvement of the system function and maintenance task for the link and expand information registration system services in The National Agricultural Biotechnology information Center.

• Genomics & Informatics
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• 제10권4호
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• pp.263-265
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• 2012

We developed a user-friendly, interactive program to simultaneously cluster and visualize omics data, such as DNA and protein array profiles. This program provides diverse algorithms for the hierarchical clustering of two-dimensional data. The clustering results can be interactively visualized and optimized on a heatmap. The present tool does not require any prior knowledge of scripting languages to carry out the data clustering and visualization. Furthermore, the heatmaps allow the selective display of data points satisfying user-defined criteria. For example, a clustered heatmap of experimental values can be differentially visualized based on statistical values, such as p-values. Including diverse menu-based display options, QCanvas provides a convenient graphical user interface for pattern analysis and visualization with high-quality graphics.

• 한국작물학회:학술대회논문집
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• 한국작물학회 2022년도 추계학술대회
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• pp.242-242
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• 2022

As the aging population increases and interest in well-being increases, the importance of developing special crops increases. Natural medicine based on the special crops has been mainly used as an adjunct therapy for many diseases and symptoms based on culture, traditional medicine, and experience. In particular, it is attracting attention as a new resource to develop new drugs such as Artemisinin, a treatment for malaria. In order to efficiently use crops, it is essential to establish omics data such as genomes, transcriptomes, and metabolites of special-purpose crops. However, many special-purpose crops have large, heterogeneous and polyploid genomes that require high cost and long time to reference genome sequencing. Therefore, we built an inexpensive, fast, but very usefill reference transcriptome as the first step. We constructed high-quality reference transcriptom sets of Codonopsis lanceolata and Ixeridium dentatum with PacBio data. Our team will continue to construct reference transcriptoms of more special-purpose crops, and the data will be released by the National Agricultural Biotechnology Information Center (NABIC) in order to be widely used in agricultural as well as medical R&D.

• Genomics & Informatics
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• 제4권1호
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• pp.40-44
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• 2006

Toxicogenomics combines transcriptome, proteome and metabolome profiling with conventional toxicology to investigate the interaction between biological molecules and toxicant or environmental stress in disease caution. Toxicogenomics faces the problems of comparison and integration across different sources of data. Cause of unusual characteristics of toxicogenomic data, researcher should be assisted by data analysis and annotation for getting meaningful information. There are already existing repositories which claim to stand for toxicogenomics database. However, those just contain limited abilities for toxicogenomic research. For supporting toxicologist who comes up against toxicogenomic data flood, now we propose novel toxicogenomics knowledgebase system, XPERANTO-TOX. XPERANTO-TOX is an integrated system for toxicogenomic data management and analysis. It is composed of three distinct but closely connected parts. Firstly, Data Storage System is for reposit many kinds of '-omics' data and conventional toxicology data. Secondly, Data Analysis System consists of analytical modules for integrated toxicogenomics data. At last, Data Annotation System is for giving extensive insight of data to researcher.

• Genomics & Informatics
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• 제18권1호
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• pp.8.1-8.10
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• 2020

The explosive growth of next-generation sequencing data has resulted in ultra-large-scale datasets and ensuing computational problems. In Korea, the amount of genomic data has been increasing rapidly in the recent years. Leveraging these big data requires researchers to use large-scale computational resources and analysis pipelines. A promising solution for addressing this computational challenge is cloud computing, where CPUs, memory, storage, and programs are accessible in the form of virtual machines. Here, we present a cloud computing-based system, Bio-Express, that provides user-friendly, cost-effective analysis of massive genomic datasets. Bio-Express is loaded with predefined multi-omics data analysis pipelines, which are divided into genome, transcriptome, epigenome, and metagenome pipelines. Users can employ predefined pipelines or create a new pipeline for analyzing their own omics data. We also developed several web-based services for facilitating downstream analysis of genome data. Bio-Express web service is freely available at https://www. bioexpress.re.kr/.

• 한국작물학회:학술대회논문집
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• 한국작물학회 2022년도 추계학술대회
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• pp.207-207
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• 2022

Eating and cooking quality (ECQ) is one of the most complex quantitative traits in rice. The understanding of genetic regulation of transcript expression levels attributing to phenotypic variation in ECQ traits is limited. We integrated whole-genome resequencing, transcriptome, and phenotypic variation data from 84 Japonica accessions to build a transcriptome-wide association study (TWAS) based regulatory network. All ECQ traits showed a large phenotypic variation and significant phenotypic correlations among the traits. TWAS analysis identified a total of 285 transcripts significantly associated with six ECQ traits. Genome-wide mapping of ECQ-associated transcripts revealed 66,905 quantitative expression traits (eQTLs), including 21,747 local eQTLs, and 45,158 trans-eQTLs, regulating the expression of 43 genes. The starch synthesis-related genes (SSRGs), starch synthase IV-1 (SSIV-1), starch branching enzyme 1 (SBE1), granule-bound starch synthase 2 (GBSS2), and ADP-glucose pyrophosphorylase small subunit 2a (OsAGPS2a) were found to have eQTLs regulating the expression of ECQ associated transcripts. Further, in co-expression analysis, 130 genes produced at least one network with 22 master regulators. In addition, we developed CRISPR/Cas9-edited glbl mutant lines that confirmed the role of alpha-globulin (glbl) in starch synthesis to validate the co-expression analysis. This study provided novel insights into the genetic regulation of ECQ traits, and transcripts associated with these traits were discovered that could be used in further rice breeding.

• Biotechnology and Bioprocess Engineering:BBE
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• 제10권5호
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• pp.418-424
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• 2005

The complexity of the biological system/biological systems has been fascinating and challenging for a long time. With the advent of mathematical tools with various omics technology, systems biology was born and is already ubiquitous in every area of biology and biotechnology. Microalgal biotechnology is no exception in this new trend. As tens of microalgal genomes become publicly available on the Internet, vast amounts of data from genomics, transcriptomics, and proteomics are reported everyday. Though there has not yet been enough data gathered on microalgal metabolomics, the in silica models for relatively simple cyanobacteria or for organelles, such as chloroplasts, will appear presently. With the help of systems biology, a more in-depth understanding of microalgae will be possible. Consequently, most industrially-interested microalgae can be metabolically redesigned/reconfigured as cell factories. Microalgae will be served as the hosts in white biotechnology.

• Communications for Statistical Applications and Methods
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• 제25권3호
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• pp.307-319
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• 2018

High-throughput technologies enable the simultaneous evaluation of thousands of genes that could discriminate different subclasses of complex diseases. Ranking genes according to differential expression is an important screening step for follow-up analysis. Many statistical measures have been proposed for this purpose. A good ranked list should provide a stable rank (at least for top-ranked gene), and the top ranked genes should have a high power in differentiating different disease status. However, there is a lack of emphasis in the literature on ranking genes based on these two criteria simultaneously. To achieve the above two criteria simultaneously, we proposed to apply a previously reported metric, the modified area under the receiver operating characteristic cure, to gene ranking. The proposed ranking method is found to be promising in leading to a stable ranking list and good prediction performances of top ranked genes. The findings are illustrated through studies on both synthesized data and real microarray gene expression data. The proposed method is recommended for ranking genes or other biomarkers for high-dimensional omics studies.

• Molecules and Cells
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• 제43권12호
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• pp.1011-1022
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• 2020

Cell type specification is a delicate biological event in which every step is under tight regulation. From a molecular point of view, cell fate commitment begins with chromatin alteration, which kickstarts lineage-determining factors to initiate a series of genes required for cell specification. Several important neuronal differentiation factors have been identified from ectopic over-expression studies. However, there is scarce information on which DNA regions are modified during induced pluripotent stem cell (iPSC) to neuronal progenitor cell (NPC) differentiation, the cis regulatory factors that attach to these accessible regions, or the genes that are initially expressed. In this study, we identified the DNA accessible regions of iPSCs and NPCs via the Assay for Transposase-Accessible Chromatin sequencing (ATAC-seq). We identified which chromatin regions were modified after neuronal differentiation and found that the enhancer regions had more active histone modification changes than the promoters. Through motif enrichment analysis, we found that NEUROD1 controls iPSC differentiation to NPC by binding to the accessible regions of enhancers in cooperation with other factors such as the Hox proteins. Finally, by using Hi-C data, we categorized the genes that directly interacted with the enhancers under the control of NEUROD1 during iPSC to NPC differentiation.