• Genomics & Informatics
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• v.21 no.2
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• pp.21.1-21.14
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• 2023

Fusobacterium nucleatum is a gram-negative bacteria associated with diverse infections like appendicitis and colorectal cancer. It mainly attacks the epithelial cells in the oral cavity and throat of the infected individual. It has a single circular genome of 2.7 Mb. Many proteins in F. nucleatum genome are listed as "Uncharacterized." Annotation of these proteins is crucial for obtaining new facts about the pathogen and deciphering the gene regulation, functions, and pathways along with discovery of novel target proteins. In the light of new genomic information, an armoury of bioinformatic tools were used for predicting the physicochemical parameters, domain and motif search, pattern search, and localization of the uncharacterized proteins. The programs such as receiver operating characteristics determine the efficacy of the databases that have been employed for prediction of different parameters at 83.6%. Functions were successfully assigned to 46 uncharacterized proteins which included enzymes, transporter proteins, membrane proteins, binding proteins, etc. Apart from the function prediction, the proteins were also subjected to string analysis to reveal the interacting partners. The annotated proteins were also put through homology-based structure prediction and modeling using Swiss PDB and Phyre2 servers. Two probable virulent factors were also identified which could be investigated further for potential drug-related studies. The assigning of functions to uncharacterized proteins has shown that some of these proteins are important for cell survival inside the host and can act as effective drug targets.

• The Journal of the Korea Contents Association
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• v.8 no.10
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• pp.11-19
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• 2008

In this paper, we propose a prediction method of lung cancer susceptibility using an importance evaluation of SNP data and the SVM learning, a gene data concerning getting sick with the lung cancer. Since the number of negative data is much larger that of positive data, which are to be used in the SVM learning, for each positive data, a negative data is first searched which has the same sex and the minimum age difference with the positive data. The searched negative data is then coupled with the positive data. For the importance evaluation of each SNP data, an equation which calculates the influence of each SNP data on the prediction of getting sick is adopted. The SNP data are sorted according to the evaluated importance. In experiments, we observed the prediction accuracy which varies according to the number of sorted SNP data used in the learning. LOOCV test results showed that the proposed method yields the prediction accuracy of maximum 65.0% for test data.

• Steel and Composite Structures
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• v.17 no.3
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• pp.215-236
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• 2014

The flexural behaviour of steel beams significantly affects the structural performance of the steel frame structures. In particular, the flexural overstrength (namely the ratio between the maximum bending moment and the plastic bending strength) that steel beams may experience is the key parameter affecting the seismic design of non-dissipative members in moment resisting frames. The aim of this study is to present a new formulation of flexural overstrength factor for steel beams by means of artificial neural network (NN). To achieve this purpose, a total of 141 experimental data samples from available literature have been collected in order to cover different cross-sectional typologies, namely I-H sections, rectangular and square hollow sections (RHS-SHS). Thus, two different data sets for I-H and RHS-SHS steel beams were formed. Nine critical prediction parameters were selected for the former while eight parameters were considered for the latter. These input variables used for the development of the prediction models are representative of the geometric properties of the sections, the mechanical properties of the material and the shear length of the steel beams. The prediction performance of the proposed NN model was also compared with the results obtained using an existing formulation derived from the gene expression modeling. The analysis of the results indicated that the proposed formulation provided a more reliable and accurate prediction capability of beam overstrength.

• Genomics & Informatics
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• v.5 no.3
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• pp.102-106
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• 2007

Radiofrequency (RF) radiation at the frequency of mobile phones has been not reported to induce cellular responses in in vitro and in vivo models. We exposed HEI-OC1, conditionally-immortalized mouse auditory cells, to RF radiation to characterize cellular responses to 1763 MHz RF radiation. While we could not detect any differences upon RF exposure, whole-genome expression profiling might provide the most sensitive method to find the molecular responses to RF radiation. HEI-OC1 cells were exposed to 1763 MHz RF radiation at an average specific absorption rate (SAR) of 20 W/kg for 24 hr and harvested after 5 hr of recovery (R5), alongside sham-exposed samples (S5). From the whole-genome profiles of mouse neurons, we selected 9 differentially-expressed genes between the S5 and R5 groups using information gain-based recursive feature elimination procedure. Based on support vector machine (SVM), we designed a prediction model using the 9 genes to discriminate the two groups. Our prediction model could predict the target class without any error. From these results, we developed a prediction model using biomarkers to determine the RF radiation exposure in mouse auditory cells with perfect accuracy, which may need validation in in vivo RF-exposure models.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2003.10a
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• pp.73-78
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• 2003

유전 연구를 통해 밝혀지고 있는 단백질은 각각의 기능적 특성을 가지고 서로 영향을 주고받으며 상호 작용한다. 단백질의 기능적 특성은 생물체에서는 단백질이 나타내는 기능으로 단백질 이름은 이들 단백질의 기능을 정확히 나타낼 수 있도록 붙여진다. 기능적 특성에 의해 명명된 단백질은 단백질을 구성하는 단어도 단백질과 유사한 기능 특성을 가질 가능성이 높다. 이는 텍스트 기반의 연구에서 단어가 가지는 중요성에서 비롯된다. 본 논문에서는 단백질을 구성하는 단어들을 단백질의 기능적 특성으로 분류하고, 이 기능분포에 의해서 단백질의 기능을 역으로 예측하고 판단하고자 하였다.

• Korean Journal of Poultry Science
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• v.22 no.2
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• pp.97-104
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• 1995

Recently, DNA fingerprinting has been utilized as the most powerful tool for genetic analysis and improvement of poultry. This technique enables us to solve several problems of poultry breeding ; traits of low heritability, difficulty in keeping the performance records, measuring in late of life, and sex limited traits. Application of DNA fingerprinting is chiefly focused to individual and population identification, evolution force, quantitative trait marker, introgression of new gene, and prediction of heterosis. Thus, research work on DNA fingerprinting will he accelerated to analyze genetic components exactly and improve the performance of poultry.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2000.11a
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• pp.39-40
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• 2000

Knowledge discovery has attracted increased attention in the biomedical industry in recent years is due to the increased availability of huge amount of biomedical data and the imminent need to turn such data into useful information and knowledge. In this talk, we discuss knowledge discovery techniques for gene expression analysis and MHC-peptide binding prediction in the context of discovering protein antigens and hot spots in these antigens.

• Proceedings of the Korean Society of Crop Science Conference
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• 2019.09a
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• pp.157-157
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• 2019

• Journal of Life Science
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• v.25 no.11
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• pp.1304-1310
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• 2015

The period circadian clock gene 3 (PER3) plays a role in the mammalian circadian clocksystem. A regular exercise regime may affect the PER3 transcription in skeletal muscle. Although the effects of day length on circadian and circannual processes are well established in humans and mice, the influence of exercise on these processes in the horse has not been investigated. The present study investigated the expression of the PER3 gene following exercise in a thoroughbred breed of Korean horse. In addition, a comprehensive in silico nonsynonymous single nucleotide polymorphism (nsSNP) analysis of the horse PER3 gene and predicted effects of nsSNPs on proteins were examined. The expression of PER3 in skeletal muscle was significantly upregulated after exercise. Four nsSNPs were functionally annotated and analyzed by computational prediction. The total free energy and RMSD values of PER3 gene showed causative mutations. The results showed that nsSNP s395916798 (G72R) was associated with residues that have stabilizing effects on structure and function of PER3 gene. This study documented role of PER3 gene in phenotypic adaptation related to exercise in skeletal muscle. Further, the SNPs in PER3 could serve as useful biomarkers of early recovery after exercise in racehorses.

• Molecular & Cellular Toxicology
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• v.1 no.4
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• pp.256-261
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• 2005

The recent DNA microarray technology enables us to understand gene expression profiling in cell line and animal models. The technology has potential possibility to comprehend mechanism of multiple genes were related to compounds which have toxicity in biological system. So, microarray system has been used for the prediction of toxicity through gene expression induced by toxicants. It has been shown that compounds with similar toxic mechanisms produce similar changes in gene expression in vivo system. Here we focus on the use of toxicogenomics for the determination of gene expression analysis associated with hepatotoxicity in rat liver and cell line (WB-F344). Methotrexate (MTX) is a chemotherapy agent that has been used for many years in the treatment of cancer because it affects cells that are rapidly dividing. Also it has been known the toxicity of MTX, in a MTX abortion, it stops embryonic cells from dividing and multiplying and is a non-surgical method of ending pregnancy in its early stages. We have shown DNA microarray analyses to assess MTX-specific expression profiles in vivo and in vitro. Male Sprague-Dawely VAF+ albino rats of 5-6 weeks old and WB-F344 cell line have been treated with MTX. Total RNA was isolated from Rat liver and cell line that has treated with MTX. 4.8 K cDNA microarray in house has been used for gene expression profiling of MTX treatment. We have found quite distinct gene expression patterns induced by MTX in a cell line and in vivo system.