• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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• pp.280-282
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• 2005

A ribonucleic acid (RNA) is one of the two types of nucleic acids found in living organisms. An RNA molecule represents a long chain of monomers called nucleotides. The sequence of nucleotides of an RNA molecule constitutes its primary structure, and the pattern of pairing between nucleotides determines the secondary structure of an RNA. Non-coding RNA genes produce transcripts that exert their function without ever producing proteins. Predicting the secondary structure of non-coding RNAs is very important for understanding their functions. We focus on Nussinov's algorithm as useful techniques for predicting RNA secondary structures. We introduce a new traceback matrix and scoring table to improve above algorithm. And the improved algorithm provides better levels of performance than the originals.

• Asian Pacific Journal of Cancer Prevention
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• 제14권9호
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• pp.5281-5286
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• 2013

Purpose: Prostate cancer caused by the abnormal disorderly growth of prostatic acinar cells is the most prevalent cancer of men in western countries. We aimed to screen out differentially expressed genes (DEGs) and explore small molecule drugs for prostate cancer. Materials and Methods: The GSE3824 gene expression profile of prostate cancer was downloaded from Gene Expression Omnibus database which including 21 normal samples and 18 prostate cancer cells. The DEGs were identified by Limma package in R language and gene ontology and pathway enrichment analyses were performed. In addition, potential regulatory microRNAs and the target sites of the transcription factors were screened out based on the molecular signature database. In addition, the DEGs were mapped to the connectivity map database to identify potential small molecule drugs. Results: A total of 6,588 genes were filtered as DEGs between normal and prostate cancer samples. Examples such as ITGB6, ITGB3, ITGAV and ITGA2 may induce prostate cancer through actions on the focal adhesion pathway. Furthermore, the transcription factor, SP1, and its target genes ARHGAP26 and USF1 were identified. The most significant microRNA, MIR-506, was screened and found to regulate genes including ITGB1 and ITGB3. Additionally, small molecules MS-275, 8-azaguanine and pyrvinium were discovered to have the potential to repair the disordered metabolic pathways, abd furthermore to remedy prostate cancer. Conclusions: The results of our analysis bear on the mechanism of prostate cancer and allow screening for small molecular drugs for this cancer. The findings have the potential for future use in the clinic for treatment of prostate cancer.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2005년도 추계학술발표대회 및 정기총회
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• pp.15-18
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• 2005

A ribonucleic acid (RNA) is one of the two types of nucleic acids found in living organisms. An RNA molecule represents a long chain of monomers called nucleotides. The sequence of nucleotides of an RNA molecule constitutes its primary structure, and the pattern of pairing between nucleotides determines the secondary structure of an RNA. Non-coding RNA genes produce transcripts that exert their function without ever producing proteins. Predicting the secondary structure of non-coding RNAs is very important for understanding their functions. We focus on Nussinov's algorithm as useful techniques for predicting RNA secondary structures. We introduce a new traceback matrix and scoring table to improve above algorithm. And the improved prediction algorithm provides better levels of performance than the originals.

• Asian Pacific Journal of Cancer Prevention
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• 제16권8호
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• pp.3131-3135
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• 2015

Objective: To investigate whether the expression of serum soluble neural cell adhesion molecule (sNCAM) is associated with hepatic encephalopathy (HE) in hepatocelular carcinoma (HCC) patients. Materials and Methods: The Oncomine Cancer Microarray database was used to determine the clinical relevance of NCAM expression in different kinds of human cancers. Sera from 75 HCC cases enrolled in this study were assessed for expression of sNCAM by enzyme linked immunosorbent assay (ELISA). Results: Dependent on the Oncomine Cancer Microarray database analysis, NCAM was down regulated in 10 different kinds of cancer, like bladder cancer, brain and central nervous system cancer, while up-regulated in lung cancer, uterine corpus leiomyoma and sarcoma, compared to normal groups. Puzzlingly, NCAM expression demonstrated no significant difference between normal and HCC groups. However, we found by quantitative ELISA that the level of sNCAM in sera from HCC patients with HE ($347.4{\pm}151.9ng/ml$) was significantly more up-regulated than that in HCC patients without HE ($260.3{\pm}104.2ng/ml$), the p-value being 0.008. sNCAM may be an important risk factor of HE in HCC patients, the correlation coefficients was 0.278 (P<0.05) on rank correlation analysis. Conclusions: This study highlights that up-regulated level of serum sNCAM is associated with HE in HCC patients and suggests that the high expression can be used as an indicator.

• Asian Pacific Journal of Cancer Prevention
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• 제15권24호
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• pp.10847-10853
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• 2015

Background: Lapatinib, a dual tyrosine kinase inhibitor that interrupts the epidermal growth factor receptor (EGFR) and HER2/neu pathways, has been indicated to have significant efficacy in treating HER2-positive breast cancer. However, acquired drug resistance has become a very serious clinical problem that hampers the use of this agent. In this study, we aimed to screen small molecule drugs that might reverse lapatinib-resistance of breast cancer by exploring differentially expressed genes (DEGs) via a bioinformatics method. Materials and Methods: We downloaded the gene expression profile of BT474-J4 (acquired lapatinib-resistant) and BT474 (lapatinib-sensitive) cell lines from the Gene Expression Omnibus (GEO) database and selected differentially expressed genes (DEGs) using dChip software. Then, gene ontology and pathway enrichment analyses were performed with the DAVID database. Finally, a connectivity map was utilized for predicting potential chemicals that reverse lapatinib-resistance. Results: A total of 1, 657 DEGs were obtained. These DEGs were enriched in 10 pathways, including cell cycling, regulation of actin cytoskeleton and focal adhesion associate examples. In addition, several small molecules were screened as the potential therapeutic agents capable of overcoming lapatinib-resistance. Conclusions: The results of our analysis provided a novel strategy for investigating the mechanism of lapatinib-resistance and identifying potential small molecule drugs for breast cancer treatment.

• Bulletin of the Korean Chemical Society
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• 제26권3호
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• pp.399-408
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• 2005

We have utilized neural network (NN) studies to predict impact sensitivities of various types of explosive molecules. Two hundreds and thirty four explosive molecules have been taken from a single database, and thirty nine molecular descriptors were computed for each explosive molecule. Optimization of NN architecture has been carried out by examining seven different sets of molecular descriptors and varying the number of hidden neurons. For the optimized NN architecture, we have utilized 17 molecular descriptors which were composed of compositional and topological descriptors in an input layer, and 2 hidden neurons in a hidden layer.

• 한국CDE학회논문집
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• 제14권6호
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• pp.404-414
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• 2009

In the computational molecular analysis, 3D structural comparison for protein searching plays a very important role. As protein databases have been grown rapidly in size, exhaustive search methods cannot provide satisfactory performance. Because exhaustive search methods try to handle the structure of protein by using sphere set which is converted from atoms set, the similarity calculation about two sphere sets is very expensive. Instead, the filter-and-refine paradigm offers an efficient alternative to database search without compromising the accuracy of the answers. In recent, a very fast algorithm based on the inter-atomic distance has been suggested by Ballester and Richard. Since they adopted the moments of distribution with inter-atomic distance between atoms which are rotational invariant, they can eliminate the structure alignment and orientation fix process and perform the searching faster than previous methods. In this paper, we propose a new 3D shape descriptor. It has properties of the general shape distribution and useful property in screening the molecular database. We show some experimental results for the validity of our method.

• 한국잠사곤충학회지
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• 제42권2호
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• pp.126-141
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• 2000

A major step towards understanding of the genetic basis of an organism is the complete sequence determination of all genes in target genome. The nucleotide sequence encoded in the genome contains the information that specifies the amino acid sequence of every protein and functional RNA molecule. In principle, it will be possible to identify every protein resposible for the structure and function of the body of the target organism. The pattern of expression in different cell types will specify where and when each protein is used. The amino acid sequence of the proteins encoded by each gene will be derived from the conceptional translation of the nucleotide sequence. Comparison of these sequences with those of known proteins, whose sequences are sorted in database, will suggest an approximate function for many proteins. This mini review describes the development of new sequencing methods and the optimization of sequencing strategies for whole genome, various cDNA and genomic analysis.

• 대한임상검사과학회지
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• 제37권3호
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• pp.139-142
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• 2005

Most expressed HLA(human leukocyte antigen) loci exhibit a remarkable degree of allelic polymorphism, which is derived from sequenceing differences predominantly localized to discrete hypervariable regions of the amino-terminal domain of the molecule. In this study, the HLA-DRB1 genotypes were determined in twenty students using the PCR-SSP (polymerase chain reaction-sequence specific primer) technique. Two specific primer pairs in assigning the DRB1 gene were used. The results of PCR-SSP, the $HLA-DRB1^{\ast}0101$ primer detected nine and $HLA-DRB1^{\ast}1501$ primer detected three people. This study shows that the PCR-SSP technique is relatively simple, fast and a practical tool for the determination of the HLA-DRB1 genotypes. Moreover, these genotype frequency results of the HLA DRB1 gene could be useful for database study before being applied to individual identification and transplantation immunity.

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2005년도 BIOINFO 2005
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• pp.139-143
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• 2005

Cytochrome P450 14${\alpha}$-sterol demethylase enzyme (CYP51) is the target a of azole type antifungals. The azole blocks the ergosterol synthesis and thereby inhibits fungal growth. A three-dimensional (3D) homology model of CYP51 from Candida albicans was constructed based on the X-ray crystal structure of CYP51 from Mycobacterium tuberculosis. Using this model, the binding modes for the substrate (24-methylene-24, 25-dihydrolanosterol) and the known inhibitors (fluconazole, voriconazole, oxiconazole, miconazole) were predicted from docking. Virtual screening was performed employing Structure Based Focusing (SBF). In this procedure, the pharmacophore models for database search were generated from the protein-ligands interactions each other. The initial structure-based virtual screening selected 15 compounds from a commercial available 3D database of approximately 50,000 molecule library, Being evaluated by a cell-based assay, 5 compounds were further identified as the potent inhibitors of Candida albicans CYP51 (CACYP51) with low minimal inhibitory concentration (MIC) range. BMD-09-01${\sim}$BMD-09-04 MIC range was 0.5 ${\mu}$g/ml and BMD-09-05 was 1 ${\mu}$g/ml. These new inhibitors provide a basis for some non-azole antifungal rational design of new, and more efficacious antifungal agents.