• Journal of Broadcast Engineering
• /
• v.28 no.3
• /
• pp.275-284
• /
• 2023

Gene expression data can be utilized in various studies, including the prediction of disease prognosis. However, there are challenges associated with collecting enough data due to cost constraints. In this paper, we propose a gene expression data generation model based on Conditional Variational Autoencoder. Our results demonstrate that the proposed model generates synthetic data with superior quality compared to two other state-of-the-art models for gene expression data generation, namely the Wasserstein Generative Adversarial Network with Gradient Penalty based model and the structured data generation models CTGAN and TVAE.

• The KIPS Transactions:PartD
• /
• v.18D no.2
• /
• pp.89-100
• /
• 2011

The CNV (Copy Number Variation) which is one of the genetic structural variations in human genome is closely related with the function of gene. In particular, the genome-wide association studies for genetic diseased persons have been researched. However, there have been few studies which infer the genetic function of CNV with normal human. In this paper, we propose the analysis method to reveal the functional relationship between common CNV and genes without considering their genomic loci. To achieve that, we propose the data integration method for heterogeneity biological data and novel measurement which can calculate the correlation between common CNV and genes. To verify the significance of proposed method, we has experimented several verification tests with GO database. The result showed that the novel measurement had enough significance compared with random test and the proposed method could systematically produce the candidates of genetic function which have strong correlation with common CNV.

• Asian Pacific Journal of Cancer Prevention
• /
• v.15 no.4
• /
• pp.1817-1822
• /
• 2014

Objective: The aim of this study was to screen for possible biomarkers of metastatic osteosarcoma (OS) using a DNA microarray. Methods: We downloaded the gene expression profile GSE49003 from Gene Expression Omnibus database, which included 6 gene chips from metastatic and 6 from non-metastatic OS patients. The R package was used to screen and identify differentially expressed genes (DEGs) between metastatic and non-metastatic OS patients. Then we compared the expression of DEGs in the two groups and sub-grouped into up-regulated and down-regulated, followed by functional enrichment analysis using the DAVID system. Subsequently, we constructed an miRNA-DEG regulatory network with the help of WebGestalt software. Results: A total of 323 DEGs, including 134 up-regulated and 189 down-regulated, were screened out. The up-regulated DEGs were enriched in 14 subcategories and most significantly in cytoskeleton organization, while the down-regulated DEGs were prevalent in 13 subcategories, especially wound healing. In addition, we identified two important miRNAs (miR-202 and miR-9) pivotal for OS metastasis, and their relevant genes, CALD1 and STX1A. Conclusions: MiR-202 and miR-9 are potential key factors affecting the metastasis of OS and CALD1 and STX1A may be possible targets beneficial for the treatment of metastatic OS. However, further experimental studies are needed to confirm our results.

• Journal of Veterinary Science
• /
• v.21 no.6
• /
• pp.91.1-91.15
• /
• 2020

Background: Sulforaphane (SFN) is an isothiocyanate compound present in cruciferous vegetables. Although the anti-inflammatory effects of SFN have been reported, the precise mechanism related to the inflammatory genes is poorly understood. Objectives: This study examined the relationship between the anti-inflammatory effects of SFN and the differential gene expression pattern in SFN treated ob/ob mice. Methods: Nitric oxide (NO) level was measured using a Griess assay. The inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2) expression levels were analyzed by Western blot analysis. Pro-inflammatory cytokines (tumor necrosis factor [TNF]-α, interleukin [IL]-1β, and IL-6) were measured by enzyme-linked immunosorbent assay (ELISA). RNA sequencing analysis was performed to evaluate the differential gene expression in the liver of ob/ob mice. Results: The SFN treatment significantly attenuated the iNOS and COX-2 expression levels and inhibited NO, TNF-α, IL-1β, and IL-6 production in lipopolysaccharide (LPS)-stimulated RAW 264.7 cells. RNA sequencing analysis showed that the expression levels of 28 genes related to inflammation were up-regulated (> 2-fold), and six genes were down-regulated (< 0.6-fold) in the control ob/ob mice compared to normal mice. In contrast, the gene expression levels were restored to the normal level by SFN. The protein-protein interaction (PPI) network showed that chemokine ligand (Cxcl14, Ccl1, Ccl3, Ccl4, Ccl17) and chemokine receptor (Ccr3, Cxcr1, Ccr10) were located in close proximity and formed a "functional cluster" in the middle of the network. Conclusions: The overall results suggest that SFN has a potent anti-inflammatory effect by normalizing the expression levels of the genes related to inflammation that were perturbed in ob/ob mice.

• Journal of The Korean Society of Grassland and Forage Science
• /
• v.43 no.3
• /
• pp.168-176
• /
• 2023

Silicon (Si) has the potential to improve plant growth and stress tolerance. The study aimed to explore Si-involving plant responses and molecular characterization of different Si-responsive genes in alfalfa. In this study, the exogenous supplementation of Si enhanced plant growth, and biomass yield. Si-acquisition in alfalfa root and shoot was higher in Si-supplemented compared to silicon deficient (-Si) plants, implying Si-acquisition has beneficial on alfalfa plants. As a consequence, the quantum efficiency of photosystem II (Fv/Fm) was significantly increased in silicon-sufficient (+Si) plants. The quantitative gene expression analysis exhibited a significant upregulation of the Lsi1, Lsi2, Lsi3, NIP5;1, and NIP6;1 genes in alfalfa roots, while BOR1, BOR4, NIP2, and NIP3 showed no significant variation in their expression. The MEME results further noticed the association of four motifs related to the major intrinsic protein (MIP). The interaction analysis revealed that NIP5;1 and Lsi1 showed a shared gene network with NIP2, BOR1, and BOR4, and Lsi2, Lsi3 and NIP3-1, respectively. These results suggest that members of the major intrinsic proteins (MIPs) family especially Lsi1, Lsi2, Lsi3, NIP5;1, and NIP6;1 genes helped to pass water and other neutral solutes through the cell membrane and those played significant roles in Si uptake and transport in plants. Together, these insights might be useful for alfalfa breeding and genome editing approaches for alfalfa improvement.

• Journal of Microbiology and Biotechnology
• /
• v.34 no.5
• /
• pp.1164-1177
• /
• 2024

Esophageal squamous cell carcinoma (ESCC) is among the most common malignant tumors of the digestive tract, with the sixth highest fatality rate worldwide. The ESCC-related dataset, GSE20347, was downloaded from the Gene Expression Omnibus (GEO) database, and weighted gene co-expression network analysis was performed to identify genes that are highly correlated with ESCC. A total of 91 transcriptome expression profiles and their corresponding clinical information were obtained from The Cancer Genome Atlas database. A mitochondria-associated risk (MAR) model was constructed using the least absolute shrinkage and selection operator Cox regression analysis and validated using GSE161533. The tumor microenvironment and drug sensitivity were explored using the MAR model. Finally, in vitro experiments were performed to analyze the effects of hub genes on the proliferation and invasion abilities of ESCC cells. To confirm the predictive ability of the MAR model, we constructed a prognostic model and assessed its predictive accuracy. The MAR model revealed substantial differences in immune infiltration and tumor microenvironment characteristics between high- and low-risk populations and a substantial correlation between the risk scores and some common immunological checkpoints. AZD1332 and AZD7762 were more effective for patients in the low-risk group, whereas Entinostat, Nilotinib, Ruxolutinib, and Wnt.c59 were more effective for patients in the high-risk group. Knockdown of TYMS significantly inhibited the proliferation and invasive ability of ESCC cells in vitro. Overall, our MAR model provides stable and reliable results and may be used as a prognostic biomarker for personalized treatment of patients with ESCC.

• Horticultural Science & Technology
• /
• v.32 no.6
• /
• pp.845-852
• /
• 2014

Among various abiotic stress factors, soil salinity decreases the photosynthetic rate, growth, and yield of plants. Recently, many genes have been reported to enhance salt tolerance. The objective of this study was to characterize the Brassica rapa Salt Stress Resistance (BrSSR) gene, of which the function was unclear, although the full-length sequence was known. To characterize the role of BrSSR, a B. rapa Chinese cabbage inbred line ('CT001') was transformed with pSL94 vector containing the full length BrSSR cDNA. Quantitative real-time polymerase chain reaction (qRT-PCR) analysis showed that the expression of BrSSR in the transgenic line was 2.59-fold higher than that in the wild type. Analysis of phenotypic characteristics showed that plants overexpressing BrSSR were resistant to salinity stress and showed normal growth. Microarray analysis of BrSSR over-expressing plants confirmed that BrSSR was strongly associated with ERD15 (AT2G41430), a gene encoding a protein containing a PAM2 motif (AT4G14270), and GABA-T (AT3G22200), all of which have been associated with salt tolerance, in the co-expression network of genes related to salt stress. The results of this study indicate that BrSSR plays an important role in plant growth and tolerance to salinity.

• Asian Pacific Journal of Cancer Prevention
• /
• v.16 no.2
• /
• pp.457-463
• /
• 2015

The pathogenesis of mantle cell lymphoma, a special subtype of lymphoma that is invasive and indolent and has a median survival of 3 to 4 years, is still partially unexplained. Much research about genes and miRNAs has been conducted in recent years, but interactions and regulatory relations of genetic elements which may play a vital role in genesis of MCL have attracted only limited attention. The present study concentrated on regulatory relations about genes and miRNAs contributing to MCL pathogenesis. Numerous experimentally validated raw data were organized into three topology networks, comprising differentially expressed, associated and global examples. Comparison of similarities and dissimilarities of the three regulating networks, paired with the analysis of the interactions between pairs of elements in every network, revealed that the differentially expressed network illuminated the carcinogenicity mechanism of MCL and the related network further described the regulatory relations involved, including prevention, diagnosis, development and therapy. Three kinds of regulatory relations for host genes including miRNAs, miRNAs targeting genes and genes regulating miRNAs were concluded macroscopically. Regulation of the differentially expressed miRNAs was also analyzed, in terms of abnormal gene expression affecting the MCL pathogenesis. Special regulatory relations were uncovered. For example, auto-regulatory loops were found in the three topology networks, key pathways of the nodes being highlighted. The present study focused on a novel point of view revealing important influencing factors for MCL pathogenesis.

• Horticultural Science & Technology
• /
• v.35 no.2
• /
• pp.243-251
• /
• 2017

Plants have evolved to adapt to abiotic stresses, such as salt, cold, and drought stress. In this study, we conducted an in-depth analysis of drought resistance mechanisms by constructing a gene co-expression network in Chinese cabbage (Brassica rapa ssp. pekinensis L.). This drought stress co-expression network has 1,560 nodes, 4,731 edges, and 79 connected components. Based on genes that showed significant co-expression in the network, drought tolerance was associated with the induction of reactive oxygen species removal by raffinose family oligosaccharides and inositol metabolism. This network could be a useful tool for predicting the functions of genes involved in drought stress resistance in Chinese cabbage.

• Journal of the Korean Society for Industrial and Applied Mathematics
• /
• v.9 no.2
• /
• pp.83-89
• /
• 2005

In this paper a new algorithm of learning and evolving artificial neural networks using gene expression programming (GEP) is presented. Compared with other traditional algorithms, this new algorithm has more advantages in self-learning and self-organizing, and can find optimal solutions of artificial neural networks more efficiently and elegantly. Simulation experiments show that the algorithm of evolving weights or thresholds can easily find the perfect architecture of artificial neural networks, and obviously improves previous traditional evolving methods of artificial neural networks because the GEP algorithm imitates the evolution of the natural neural system of biology according to genotype schemes of biology to crossover and mutate the genes or chromosomes to generate the next generation, and the optimal architecture of artificial neural networks with evolved weights or thresholds is finally achieved.