• Molecules and Cells
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• v.25 no.2
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• pp.279-288
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• 2008

The analysis of microarray data is essential for large amounts of gene expression data. In this review we focus on clustering techniques. The biological rationale for this approach is the fact that many co-expressed genes are co-regulated, and identifying co-expressed genes could aid in functional annotation of novel genes, de novo identification of transcription factor binding sites and elucidation of complex biological pathways. Co-expressed genes are usually identified in microarray experiments by clustering techniques. There are many such methods, and the results obtained even for the same datasets may vary considerably depending on the algorithms and metrics for dissimilarity measures used, as well as on user-selectable parameters such as desired number of clusters and initial values. Therefore, biologists who want to interpret microarray data should be aware of the weakness and strengths of the clustering methods used. In this review, we survey the basic principles of clustering of DNA microarray data from crisp clustering algorithms such as hierarchical clustering, K-means and self-organizing maps, to complex clustering algorithms like fuzzy clustering.

• Molecular & Cellular Toxicology
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• v.2 no.3
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• pp.170-175
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• 2006

The extensive isolation of genes responsive to stressful conditions from a soft coral Scleronephthya gracillimum was described. Soft coral colonies were exposed to thermal and chemical stressors to induce the expression of stress related genes. Differentially expressed genes by natural or anthropogenic stressors were identified by construction of standard and stress exposed-paired subtractive cDNA library. Thirty-two and thirty-seven kinds of candidate genes were identified from thermal or benzo[a]pyrene stress exposed group, respectively, which are associated with cell cycle, cell signaling, transcription, translation, protein metabolism, and other cellular functions. The expected function of each gene was described. The isolated and identified differentially expressed genes have a great potential to identify environmental stressors in global environmental changes and could act as molecular biomarkers for biological responses against environmental changes. Finally, it may open a new paradigm on soft coral health assessment.

• 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.

• Asian-Australasian Journal of Animal Sciences
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• v.18 no.2
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• pp.170-178
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• 2005

An in silico approach was developed to survey the genes expressed in four internal organs of pig: liver, kidney, spleen and small intestine. The major procedures of the approach included: (1) BLAST searching against GenBank "est_others" database using human cDNA sequences as queries to screen the porcine orthologous expressed sequence tags (ESTs), (2) classifying the porcine ESTs records by resources according to certain criteria and (3) analyzing data for ESTs specifically expressed in each organ. In order to do so, four Java programs were developed. Based on the ESTs available in the GenBank database, it was found that there were at least 2,100 genes expressed in these four organs, including 128 in the liver, 81 in the kidney, 780 in the spleen, and 1,423 in the small intestine respectively (a few genes co-expressed in these tissues). Gene expression patterns, such as co-expressed genes, preferentially expressed genes and basic active genes were also compared and characterized among these organs. This study provides a comprehensive model on how to use the bioinformatics approach and Genbank databases to facilitate the discovery of new genes in livestock species.

• Reproductive and Developmental Biology
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• v.37 no.4
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• pp.185-192
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• 2013

Many countries have implemented genetic evaluation for fertility traits in recent years. In particular, reproductive trait is a complex trait and need to require a system-level approach for identifying candidate genes related to the trait. To find the candidate gene associated with reproductive trait, we applied a weighted gene co-expression network analysis from expression value of bovine genes. We identified three co-expressed modules associated with reproductive trait from bovine microarray data. Hub genes (ZP4, FHL2 and EGR4) were determined in each module; they were topologically centered with statistically significant value in the gene co-expression network. We were able to find the highly co-expressed gene pairs with a correlation coefficient. Finally, the crucial functions of co-expressed modules were reported from functional enrichment analysis. We suggest that the network-based approach in livestock may an important method for analyzing the complex effects of candidate genes associated with economic traits like reproduction.

• Communications for Statistical Applications and Methods
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• v.29 no.5
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• pp.591-601
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• 2022

In gene set analysis with microarray expression data, a group of genes such as a gene regulatory pathway and a signaling pathway is often tested if there exists either differentially expressed (DE) or differentially co-expressed (DC) genes between two biological conditions. Recently, a statistical test based on covariance estimation have been proposed in order to identify DC genes. In particular, covariance regularization by hard thresholding indeed improved the power of the test when the proportion of DC genes within a biological pathway is relatively small. In this article, we compare covariance thresholding methods using four different regularization penalties such as lasso, hard, smoothly clipped absolute deviation (SCAD), and minimax concave plus (MCP) penalties. In our extensive simulation studies, we found that both SCAD and MCP thresholding methods can outperform the hard thresholding method when the proportion of DC genes is extremely small and the number of genes in a biological pathway is much greater than a sample size. We also applied four thresholding methods to 3 different microarray gene expression data sets related with mutant p53 transcriptional activity, and epithelium and stroma breast cancer to compare genetic pathways identified by each method.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2003.04a
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• pp.121-121
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• 2003

Expressed sequence tags (EST) are help to quickly identify functions of expressed genes and to understand the complexity of gene expression. To assist genetic study of the root development in Panax ginseng, which is one of the most important medicinal plant, expressed sequence tags (EST) analysis was carried out. We constructed a CDNA library using the 4-year Chunpoon root. Partial sequences were obtained from 3,841 clone. The ESTs could be clustered into 2,056 (64%) non-redundant groups. Similarity search of the non-redundant ESTs against public non-redundant databases of both protein and DNA indicated that 1,498 groups show similarity to genes of known function. These ESTs clones were divided into eighteen categories depending upon gene function. The most abundant transcripts were major latex protein (41), ribonuclease 2 (36), metallothionein 2(35). Our extensive EST analysis of genes expressed in 4-year Chunpoong root not only contributes to the understanding of the dynamics of genome expression patterns in root organ development but also adds data to the repertoire of all genomic genes.

• Journal of Radiation Protection and Research
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• v.38 no.4
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• pp.166-171
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• 2013

While high-dose ionizing radiation results in long term cellular cytotoxicity, chronic low-dose (<0.2 Gy) of X- or ${\gamma}$-ray irradiation can be beneficial to living organisms by inducing radiation hormesis, stimulating immune function, and adaptive responses. During chronic low-dose-rate radiation (LDR) exposure, whole body of mice is exposed to radiation, however, it remains unclear if LDR causes changes in gene expression of the whole brain. Therefore, we aim to investigate expressed genes (EGs) and signaling pathways specifically regulated by LDR-irradiation ($^{137}Cs$, a cumulative dose of 1.7 Gy for total 100 days) in the whole brain. Using microarray analysis of whole brain RNA extracts harvested from ICR and AKR/J mice after LDR-irradiation, we discovered that two mice strains displayed distinct gene regulation patterns upon LDR-irradiation. In ICR mice, genes involved in ion transport, transition metal ion transport, and developmental cell growth were turned on while, in AKR/J mice, genes involved in sensory perception, cognition, olfactory transduction, G-protein coupled receptor pathways, inflammatory response, proteolysis, and base excision repair were found to be affected by LDR. We validated LDR-sensitive EGs by qPCR and confirmed specific upregulation of S100a7a, Olfr624, and Gm4868 genes in AKR/J mice whole brain. Therefore, our data provide the first report of genetic changes regulated by LDR in the mouse whole brain, which may affect several aspects of brain function.

• Mycobiology
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• v.50 no.5
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• pp.357-365
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• 2022

Schizophyllum commune has emerged as the most promising model mushroom to study developmental stages (mycelium, primordium), which are two primary processes of fruit body development. Long non-coding RNA (lncRNA) has been proved to participate in fruit development and sex differentiation in fungi. However, potential lncRNAs have not been identified in S. commune from mycelium to primordium developmental stages. In this study, lncRNA-seq was performed in S. commune and 61.56 Gb clean data were generated from mycelium and primordium developmental stages. Furthermore, 191 lncRNAs had been obtained and a total of 49 lncRNAs were classified as differently expressed lncRNAs. Additionally, 26 up-regulated differently expressed lncRNAs and 23 down-regulated between mycelium and primordia libraries were detected. Further, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that differentially expressed lncRNAs target genes from the MAPK pathway, phosphatidylinositol signal, ubiquitin-mediated proteolysis, autophagy, and cell cycle. This study provides a new resource for further research on the relationship between lncRNA and two developmental stages (mycelium, primordium) in S. commune.

• Journal of Microbiology and Biotechnology
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• v.24 no.3
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• pp.363-370
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• 2014

Campylobacter jejuni is a prevalent foodborne pathogen worldwide. Human infection by C. jejuni primarily arises from contaminated poultry meats. Genes expressed in vivo may play an important role in the pathogenicity of C. jejuni. We applied an immunoscreening method, in vivo-induced antigen technology (IVIAT), to identify in vivo-induced genes during human infection by C. jejuni. An inducible expression library of genomic proteins was constructed from sequenced C. jejuni NCTC 11168 and was then screened using adsorbed, pooled human sera obtained from clinical patients. We successfully identified 24 unique genes expressed in vivo. These genes were implicated in metabolism, molecular biosynthesis, genetic information processing, transport, and other processes. We selected six genes with different functions to compare their expression levels in vivo and in vitro using real-time RT-PCR. The results showed that the selected six genes were significantly upregulated in vivo but not in vitro. In short, these identified in vivo-induced genes may contribute to human infection of C. jejuni, some of which may be meaningful vaccine candidate antigens or diagnosis serologic markers for campylobacteriosis. IVIAT may present a significant and efficient method for understanding the pathogenicity mechanism of Campylobacter and for finding targets for its prevention and control.