• The KIPS Transactions:PartD
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• v.12D no.5 s.101
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• pp.755-764
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• 2005

Recently, as it is considered more important to identify the function of ail unknown genes in living things, many tools for gene prediction have been developed to identify genes in the DNA sequences. Unfortunately, most of those tools use their own schemes to represent their programs results, requiring researchers to make additional efforts to understand the result generated by them So, it is desirable to provide a standardized method of representing predicted gene information, which makes it possible to automatically produce the predicted results for a given set of gene data In this paper, we describe an effective U representation for various predicted gene information, and present an XML-based analysis tool for gene predication results based on this representation. The developed system helps users of gene prediction tools to conveniently analyze the predicted results and to automatically produce the statistical results of the prediction. To show the usefulness of the tool, we applied our programs to the results generated by GenScan and GeneID, which are widely used gene prediction systems.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.7
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• pp.3145-3149
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• 2014

Gene expression profiling facilitates the understanding of biological characteristics of gliomas. Previous studies mainly used regression/variance analysis without considering various background biological and environmental factors. The aim of this study was to investigate gene expression differences between grade III and IV gliomas through partial least squares (PLS) based analysis. The expression data set was from the Gene Expression Omnibus database. PLS based analysis was performed with the R statistical software. A total of 1,378 differentially expressed genes were identified. Survival analysis identified four pathways, including Prion diseases, colorectal cancer, CAMs, and PI3K-Akt signaling, which may be related with the prognosis of the patients. Network analysis identified two hub genes, ELAVL1 and FN1, which have been reported to be related with glioma previously. Our results provide new understanding of glioma pathogenesis and prognosis with the hope to offer theoretical support for future therapeutic studies.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2001.08a
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• pp.103-127
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• 2001

Gene expression studies require statistical experimental designs and validation before laboratory confirmation. Various clustering approaches, such as hierarchical, Kmeans, SOM are commonly used for unsupervised learning in gene expression data. Several classification methods, such as gene voting, SVM, or discriminant analysis are used for supervised lerning, where well-defined response classification is possible. Estimating gene-condition interaction effects require advanced, computationally-intensive statistical approaches.

• Journal of Korean Neurosurgical Society
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• v.65 no.5
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• pp.697-709
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• 2022

Objective : The present study aimed to identify the function of ischemic stroke (IS) patients' peripheral blood and its role in IS, explore the pathogenesis, and provide direction for clinical research progress by comprehensive bioinformatics analysis. Methods : Two datasets, including GSE58294 and GSE22255, were downloaded from Gene Expression Omnibus database. GEO2R was utilized to obtain differentially expressed genes (DEGs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of DEGs were performed using the database annotation, visualization and integrated discovery database. The protein-protein interaction (PPI) network of DEGs was constructed by search tool of searching interactive gene and visualized by Cytoscape software, and then the Hub gene was identified by degree analysis. The microRNA (miRNA) and miRNA target genes closely related to the onset of stroke were obtained through the miRNA gene regulatory network. Results : In total, 36 DEGs, containing 27 up-regulated and nine down-regulated DEGs, were identified. GO functional analysis showed that these DEGs were involved in regulation of apoptotic process, cytoplasm, protein binding and other biological processes. KEGG enrichment analysis showed that these DEGs mediated signaling pathways, including human T-cell lymphotropic virus (HTLV)-I infection and microRNAs in cancer. The results of PPI network and cytohubba showed that there was a relationship between DEGs, and five hub genes related to stroke were obtained : SOCS3, KRAS, PTGS2, EGR1, and DUSP1. Combined with the visualization of DEG-miRNAs, hsa-mir-16-5p, hsa-mir-181a-5p and hsa-mir-124-3p were predicted to be the key miRNAs in stroke, and three miRNAs were related to hub gene. Conclusion : Thirty-six DEGs, five Hub genes, and three miRNA were obtained from bioinformatics analysis of IS microarray data, which might provide potential targets for diagnosis and treatment of IS.

• Journal of Microbiology
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• v.45 no.2
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• pp.139-145
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• 2007

The Bombyx mori parvo-like virus (China isolate) DNA polymerase (BmDNV-3 dnapol) gene has been tentatively identified based on the presence of conserved motifs. In the present study, we perform a transcriptional analysis of the BmDNV-3 dnapol gene using the total RNA isolated from BmDNV-3 infected silkworm at different times. Northern blot analysis with a BmDNV-3 dnapol-specific riboprobe showed a major transcript of 3.3 kb. 5'-RACE revealed that the major transcription start point was located 20 nucleotides downstream of the TATA box. In a temporal expression analysis using differential RT-PCR, BmDNV-3 dnapol transcript was detected at low levels at 6 h.p.i., increased from 6 to 36 h.p.i., and remained fairly constant thereafter. Analysis of the predicted DNA polymerase sequence using neighborjoining and protein parsimony algorithms indicated that the predicted 1115-residue polypeptide contained five motifs associated with DNA polymerases synthetic activities and three additional motifs associated with polymerases possessing 3' to 5' exonuclease activity. The molecular phylogenetic analysis of this gene supported the placement of Bombyx mori parvo-like virus in a separate virus family.

• Journal of the Korean Data and Information Science Society
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• v.18 no.2
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• pp.489-506
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• 2007

Gene structure prediction, which is to predict protein coding regions in a given nucleotide sequence, is the most important process in annotating genes and greatly affects gene analysis and genome annotation. As eukaryotic genes have more complicated structures in DNA sequences than those of prokaryotic genes, analysis programs for eukaryotic gene structure prediction have more diverse and more complicated computational models. There are Ab Initio method, Similarity-based method, and Ensemble method for gene prediction method for eukaryotic genes. Each Method use various algorithms. This paper introduce how to predict genes using HMM(Hidden Markov Model) algorithm and present the process of gene prediction with well-known gene prediction programs.

• Genomics & Informatics
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• v.18 no.4
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• pp.41.1-41.8
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• 2020

We provide an algorithm for the construction and analysis of autocorrelation (information) functions of gene nucleotide sequences. As a measure of correlation between discrete random variables, we use normalized mutual information. The information functions are indicative of the degree of structuredness of gene sequences. We construct the information functions for selected gene sequences. We find a significant difference between information functions of genes of different types. We hypothesize that the features of information functions of gene nucleotide sequences are related to phenotypes of these genes.

• Genomics & Informatics
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• v.14 no.4
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• pp.166-172
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• 2016

Although a large number of genetic variants have been identified to be associated with common diseases through genome-wide association studies, there still exits limitations in explaining the missing heritability. One approach to solving this missing heritability problem is to investigate gene-gene interactions, rather than a single-locus approach. For gene-gene interaction analysis, the multifactor dimensionality reduction (MDR) method has been widely applied, since the constructive induction algorithm of MDR efficiently reduces high-order dimensions into one dimension by classifying multi-level genotypes into high- and low-risk groups. The MDR method has been extended to various phenotypes and has been improved to provide a significance test for gene-gene interactions. In this paper, we propose a simple method, called accelerated failure time (AFT) UM-MDR, in which the idea of a unified model-based MDR is extended to the survival phenotype by incorporating AFT-MDR into the classification step. The proposed AFT UM-MDR method is compared with AFT-MDR through simulation studies, and a short discussion is given.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.6
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• pp.2857-2861
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• 2014

More and more evidence indicates that the G801A polymorphism in the CXCL12 gene might be associated with susceptibility to breast carcinoma in humans being. However, individually published results have been inconsistent. The purpose of this meta-analysis was to investigate the association between the G801A polymorphism in the CXCL12 gene and breast carcinoma risk. A complete search strategy was done by the electronic databases including PubMed and Chinese Biomedical Literature Database. A meta-analysis including seven individual studies was carried out in order to explore the association between the G801A polymorphism in the CXCL12 gene polymorphisms and breast carcinoma. The pooled odds ratios (ORs) and their corresponding 95% confidence intervals (95%CIs) between the G801A polymorphism in the CXCL12 gene and breast carcinoma risk were assessed by the random-effects model. A significant relationship between the G801A polymorphism in the CXCL12 gene and breast carcinoma was discovered in an allelic genetic model (OR: 1.214, 95%CI: 1.085-1.358, p=0.001), a homozygote model (OR: 1.663, 95%CI: 1.240-2.232, p=0.001), a heterozygote model (OR: 1.392, 95%CI: 1.190-1.629, p=0.000), a recessive genetic model (OR: 1.407, 95%CI: 1.060-1.868, p=0.018) and a dominant genetic model (OR: 1.427, 95%CI: 1.228-1.659, p=0.000). On sub-group analysis based on ethnicity, significance was observed between the European group and the mixed group. A significant relationship was found between the G801A polymorphism in the CXCL12 gene and breast carcinoma risk. Individuals with the A allele of the G801A polymorphism in the CXCL12 gene are under a higher risk for breast carcinoma.

• Asian-Australasian Journal of Animal Sciences
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• v.31 no.4
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• pp.467-472
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• 2018

Objective: Molecular cloning and bioinformatics analysis of annexin A2 (ANXA2) gene in sika deer antler tip were conducted. The role of ANXA2 gene in the growth and development of the antler were analyzed initially. Methods: The reverse transcriptase polymerase chain reaction (RT-PCR) was used to clone the cDNA sequence of the ANXA2 gene from antler tip of sika deer (Cervus Nippon hortulorum) and the bioinformatics methods were applied to analyze the amino acid sequence of Anxa2 protein. The mRNA expression levels of the ANXA2 gene in different growth stages were examined by real time reverse transcriptase polymerase chain reaction (real time RT-PCR). Results: The nucleotide sequence analysis revealed an open reading frame of 1,020 bp encoding 339 amino acids long protein of calculated molecular weight 38.6 kDa and isoelectric point 6.09. Homologous sequence alignment and phylogenetic analysis indicated that the Anxa2 mature protein of sika deer had the closest genetic distance with Cervus elaphus and Bos mutus. Real time RT-PCR results showed that the gene had differential expression levels in different growth stages, and the expression level of the ANXA2 gene was the highest at metaphase (rapid growing period). Conclusion: ANXA2 gene may promote the cell proliferation, and the finding suggested Anxa2 as an important candidate for regulating the growth and development of deer antler.