• Proceedings of the Korean Society for Bioinformatics Conference
• /
• 2001.10a
• /
• pp.97-115
• /
• 2001

cDNA microarray technology allows the monitoring of expression levels for thousands of genes simultaneously. Many statistical analysis tools become widely applicable to the analysis of cDNA microarray data. In this talk, we consider a two-way ANOVA model to differentiate genes that have high variability and ones that do not. Using this model, we detect genes that have different gene expression profiles among experimental groups. The two-way ANOVA model is illustrated using cDNA microarrays of 3,800 genes obtained in an experiment to search for changes in gene expression profiles during neuronal differentiation of cortical stem cells.

• Journal of Physiology & Pathology in Korean Medicine
• /
• v.18 no.5
• /
• pp.1291-1300
• /
• 2004

Baicalin, a biologically active flavonoid form the roots of Scutallaria baicalensis (Skullcap), have been reported to not only function as anti-oxidants but also cause anticancer effect. We investigated the mechanism of baicalin-induced cytotoxicity and the macro scale gene expression analysis in leukemia cell line, HL-60 cells. Baicalin (10 μM) were used to treat the cells for 6h, 12h, 24h, 48h and 72h. In a human cDNAchip study of 65,000 genes evaluated 6, 12, 24, 48. 72 hours after treated with Baicalin in HL-60 cells. Hierarchical cluster against the genes which showed expression changes by more than two fold. One hundred one genes were grouped into 6 clusters according to their profile of expression by a hierarchical clustering algorithm. For genes differentially expressed in response to baicalin treatment, we tested functional classes based on Gene Ontology (GO) terms. This study provides the most comprehensive available survey of gene expression changes in response to baicalin treatment in HL-60 cell line.

• Journal of KIISE:Software and Applications
• /
• v.37 no.1
• /
• pp.1-8
• /
• 2010

Recently lots of attention has been paid to gene set analysis for identifying differentially expressed gene-sets between two sample groups. Unlike earlier approaches, the gene set analysis enables us to find significant gene-sets along with their functional characteristics. For this reason, various novel approaches have been suggested lately for gene set analysis. As one of such, PAGE is a parametric approach that employs average difference (AD) as an expression metric to quantify expression differences between two sample groups and assumes that the distribution of gene scores is normal. This approach is preferred to non-parametric approach because of more effective performance. However, the metric AD does not reflect either gene expression intensities or variances over samples in calculating gene scores. Thus, in this paper, we investigate the usefulness of several other expression metrics for parametric gene-set analysis, which consider actual expression intensities of genes or their expression variances over samples. For this purpose, we examined three expression metrics, WAD (weighted average difference), FC (Fisher's criterion), and Abs_SNR (Absolute value of signal-to-noise ratio) for parametric gene set analysis and evaluated their experimental results.

• Korean Journal of Environmental Biology
• /
• v.23 no.3 s.59
• /
• pp.269-274
• /
• 2005

The 2D/E gel analysis for polypeptide expression reflecting I-18 C gene (early-ecdysterone inducible gene) has conducted the emerged C. riparius adults from larval phase exposure to tebufenozide acting as an ecdysteroidal molting hormone. Control group, the amount of ORE II of the I-18 C gene was larger than that of ORE I of this gene. After treatments, ORE I of the I-18 C gene was overexpressed as the polypeptide, whereas ORF II of this gene was expressed as the polypeptide and was clearly reduced expression. Accordingly, we consider that tebufenozide exhibited endocrine disruptions related processing of ecdysteroid receptor protein reflecting ORF II of I-18 C gene. Also, earlier emergence day was related overexpressed polypeptide reflecting ORE I of I-18 C gene. In this study result, tebufenozide induced changing of physiological condition, and then polypeptide expression reflecting early-ecdysterone inducible I-18 C gene was different between control group and exposure group.

• The Korean Journal of Applied Statistics
• /
• v.24 no.2
• /
• pp.315-321
• /
• 2011

Gene expression microarray data often include multiple missing values. Most gene expression analysis (including gene clustering analysis); however, require a complete data matric as an input. In ordinary clustering methods, just a single missing value makes one abandon the whole data of a gene even if the rest of data for that gene was intact. The quality of analysis may decrease seriously as the missing rate is increased. In the opposite aspect, the imputation of missing value may result in an artifact that reduces the reliability of the analysis. To clarify this contradiction in microarray clustering analysis, this paper compared the accuracy of clustering with and without imputation over several microarray data having different missing rates. This paper also tested the clustering efficiency of several imputation methods including our propose algorithm. The results showed it is worthwhile to check the clustering result in this alternative way without any imputed data for the imperfect microarray data.

• Genes and Genomics
• /
• v.40 no.11
• /
• pp.1127-1136
• /
• 2018

The Greater Sudbury Region has been known as one of the most ecologically disturbed areas in Canada for the past century. Plant adaptation to environmental stressors often results in modifications in gene expression at the transcriptional level. The main objective of the present study was to compare the expression of genes associated with nickel resistance in Acer rubrum and Populus tremuloides growing in areas contaminated and uncontaminated with metals. Primers targeting Nramps4, Nas 3, At2G, MRP4 and alpha-tubulin genes were used to amplify cDNA of both species. The expression of the At2G gene, was $2{\times}$ and $9{\times}$ higher in P. tremuloides than in A. rubrum for St. Charles (uncontaminated site) and Kelly Lake (metal contaminated site), respectively. There was a much smaller difference between the two species for the Nramps 4 gene as its expression was $2.5{\times}$ and $3{\times}$ higher in P. tremuloides compared to A. rubrum from St. Charles and Kelly Lake, respectively. The same trend was observed for the MRP4 gene whose expression was $2{\times}$ and $14{\times}$ higher in P. tremuloides than in A. rubrum from St. Charles and Kelly Lake, respectively. For the Nas 3 gene, the expression was similar in both sites. This gene was upregulated $11{\times}$ and $10{\times}$ in P. tremuloides compared to A. rubrum in samples from St. Charles and Kelly Lake, respectively. In general, no significant difference was observed between the metal contaminated and uncontaminated sites for gene expression. In depth analysis revealed that AT2G and MRP4 genes were significantly down regulated in A. rubrum from the metal contaminated sites compared to those from uncontaminated areas, but environmental factors driving this differential gene expression couldn't be established.

• Genomics & Informatics
• /
• v.16 no.4
• /
• pp.36.1-36.3
• /
• 2018

Next generation sequencing (NGS), a high-throughput DNA sequencing technology, is widely used for molecular biological studies. In NGS, RNA-sequencing (RNA-Seq), which is a short-read massively parallel sequencing, is a major quantitative transcriptome tool for different transcriptome studies. To utilize the RNA-Seq data, various quantification and analysis methods have been developed to solve specific research goals, including identification of differentially expressed genes and detection of novel transcripts. Because of the accumulation of RNA-Seq data in the public databases, there is a demand for integrative analysis. However, the available RNA-Seq data are stored in different formats such as read count, transcripts per million, and fragments per kilobase million. This hinders the integrative analysis of the RNA-Seq data. To solve this problem, we have developed a web-based application using Shiny, COEX-seq (Convert a Variety of Measurements of Gene Expression in RNA-Seq) that easily converts data in a variety of measurement formats of gene expression used in most bioinformatic tools for RNA-Seq. It provides a workflow that includes loading data set, selecting measurement formats of gene expression, and identifying gene names. COEX-seq is freely available for academic purposes and can be run on Windows, Mac OS, and Linux operating systems. Source code, sample data sets, and supplementary documentation are available as well.

• KSBB Journal
• /
• v.16 no.4
• /
• pp.381-388
• /
• 2001

A program for integrated gene expression profile analysis such as hierarchical clustering, K-means, fuzzy c-means, self-organizing map(SOM), principal component analysis(PCA), and singular value decomposition(SVD) was made for DNA chip data anlysis by using Matlab. It also contained the normalization method of gene expression input data. The integrated data anlysis program could be effectively used in DNA chip data analysis and help researchers to get more comprehensive analysis view on gene expression data of their own.

• Journal of Aquaculture
• /
• v.16 no.1
• /
• pp.8-14
• /
• 2003

To generate expressed sequence tags for genomics research involving genetic linkage analysis, to examine gene expression profiles in muscles of channel catfish in a non-normalized muscle cDNA library, to compare gene expression in young and mature channel catfish muscles using the EST reagents and gene filters to demonstrate the feasibility of functional genomics research in small laboratories. 102 randomly picked cDNA clones were analyzed from the catfish muscle cDNA library. Of the sequences generated, 90.2% of ESTs was identified as known genes by identity comparisons. These 92 clones of known gene products represent transcriptional products of 24 genes. The 10 clones of unknown gene products represent 8 genes. The major transcripts (70.1% of the analyzed ESTs) in the catfish muscle are from many major genes involved in muscle contraction, relaxation, energy metabolism and calcium binding such as alpha actin, creatine kinase, parvalbumin, myosin, troponins, and tropomyosins. Gene expression of the unique ESTs was comparatively studied in the young and adult catfish muscles. Significant differences were observed for aldolase, myostatin, myosin light chain, parvalbumin, and an unknown gene. While myosin light chain and an unknown gene (CM 192) are down-regulated in the mature fish muscle, the aldolase, myostatin, and parvalbumin are significantly up-regulated in the mature fish muscle. Although the physiological significance of the changes in expression levels needs to be further addressed, this research demonstrates the feasibility and power of functional genomics in channel catfish. Channel catfish muscle gene expression profiles provide a valuable molecular muscle physiology blueprint for functional comparative genomics.

• Journal of Gastric Cancer
• /
• v.17 no.1
• /
• pp.43-51
• /
• 2017

Purpose: This study aimed to analyze G3BP1 and VEZT expression profiles in patients with gastric cancer, and examine the possible relationship between the expressions of each gene and clinicopathological factors. Materials and Methods: Expression of these genes in formalin-fixed paraffin embedded (FFPE) tissues, collected from 40 patients with gastric cancer and 40 healthy controls, was analyzed. Differences in gene expression among patient and normal samples were identified using the GraphPad Prism 5 software. For the analysis of real-time polymerase chain reaction products, GelQuantNET software was used. Results: Our findings demonstrated that both VEZT and G3BP1 mRNA expression levels were downregulated in gastric cancer samples compared with those in the normal controls. No significant relationship was found between the expression of these genes and gender (P-value, 0.4835 vs. 0.6350), but there were significant changes associated with age (P-value, 0.0004 vs. 0.0001) and stage of disease (P-value, 0.0019 vs. 0.0001). In addition, there was a direct relationship between VEZT gene expression and metastasis (P-value, 0.0462), in contrast to G3BP1 that did not demonstrate any significant correlation (P-value, 0.1833). Conclusions: The results suggest that expression profiling of VEZT and G3BP1 can be used for diagnosis of gastric cancer, and specifically, VEZT gene could be considered as a biomarker for the detection of gastric cancer progression.