• Title/Summary/Keyword: Gene prediction

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Prediction of the Secondary Structure of the AgfA Subunit of Salmonella enteritidis Overexpressed as an MBP-Fused Protein

  • Won, Mi-Sun;Kim, So-Youn;Lee, Seung-Hwan;Kim, Chul-Jung;Kim, Hyun-Su;Jun, Moo-Hyung;Song, Kyung-Bin
    • Journal of Microbiology and Biotechnology
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    • v.11 no.1
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    • pp.164-166
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    • 2001
  • To examine the characteristics of the recombinant thin aggregative fimbriae of Salmonella, the AgfA subunit gene was amplified from Salmonella enteritidis using a PCR. The maltose binding protein (MBP)-AgfA fusion protein was overproduced in E. coli and purified. The secondary structure of AgfA was then elucidated from the difference CD spectra. An estimation of the secondary structure of AgfA using the self-consistent method revealed a mostly ${\beta}-sheet$ structure.

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Toxicoinformatics: The Master Key for Toxicogenomics

  • Lee, Wan-Sun;Kim, Yang-Seok
    • Molecular & Cellular Toxicology
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    • v.1 no.1
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    • pp.13-16
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    • 2005
  • The current vision of toxicogenomics is the development of methods or platforms to predict toxicity of un characterized chemicals by using '-omics' information in pre-clinical stage. Because each chemical has different ADME (absorption, distribution, mechanism, excretion) and experimental animals have lots of variation, precise prediction of chemical's toxicity based on '-omics' information and toxicity data of known chemicals is very difficult problem. So, the importance of bioinformatics is more emphasized on toxicogenomics than other functional genomics studies because these problems can not be solved only with experiments. Thus, toxicoinformatics covers all information-based analytical methods from gene expression (bioinformatics) to chemical structures (cheminformatics) and it also deals with the integration of wide range of experimental data for further extensive analyses. In this review, the overall strategy to toxicoinformatics is discussed.

Recent Advancement of the Molecular Diagnosis in Pediatric Brain Tumor

  • Bae, Jeong-Mo;Won, Jae-Kyung;Park, Sung-Hye
    • Journal of Korean Neurosurgical Society
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    • v.61 no.3
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    • pp.376-385
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    • 2018
  • Recent discoveries of brain tumor-related genes and fast advances in genomic testing technologies have led to the era of molecular diagnosis of brain tumor. Molecular profiling of brain tumor became the significant step in the diagnosis, the prediction of prognosis and the treatment of brain tumor. Because traditional molecular testing methods have limitations in time and cost for multiple gene tests, next-generation sequencing technologies are rapidly introduced into clinical practice. Targeted sequencing panels using these technologies have been developed for brain tumors. In this article, focused on pediatric brain tumor, key discoveries of brain tumor-related genes are reviewed and cancer panels used in the molecular profiling of brain tumor are discussed.

Empirical modeling of flexural and splitting tensile strengths of concrete containing fly ash by GEP

  • Saridemir, Mustafa
    • Computers and Concrete
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    • v.17 no.4
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    • pp.489-498
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    • 2016
  • In this paper, the flexural strength ($f_{fs}$) and splitting tensile strength ($f_{sts}$) of concrete containing different proportions of fly ash have been modeled by using gene expression programming (GEP). Two GEP models called GEP-I and GEP-II are constituted to predict the $f_{fs}$ and $f_{sts}$ values, respectively. In these models, the age of specimen, cement, water, sand, aggregate, superplasticizer and fly ash are used as independent input parameters. GEP-I model is constructed by 292 experimental data and trisected into 170, 86 and 36 data for training, testing and validating sets, respectively. Similarly, GEP-II model is constructed by 278 experimental data and trisected into 142, 70 and 66 data for training, testing and validating sets, respectively. The experimental data used in the validating set of these models are independent from the training and testing sets. The results of the statistical parameters obtained from the models indicate that the proposed empirical models have good prediction and generalization capability.

Reliability-based modeling of punching shear capacity of FRP-reinforced two-way slabs

  • Kurtoglu, Ahmet Emin;Cevik, Abdulkadir;Albegmprli, Hasan M.;Gulsan, Mehmet Eren;Bilgehan, Mahmut
    • Computers and Concrete
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    • v.17 no.1
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    • pp.87-106
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    • 2016
  • This paper deals with the reliability analysis of design formulations derived for predicting the punching shear capacity of FRP-reinforced two-way slabs. Firstly, a new design code formulation was derived by means of gene expression programming. This formulation differs from the existing ones as the slab length (L) was introduced in the equation. Next, the proposed formulation was tested for its generalization capability by a parametric study. Then, the stochastic analyses of derived and existing formulations were performed by Monte Carlo simulation. Finally, the reliability analyses of these equations were carried out based on the results of stochastic analysis and the ultimate state function of ASCE-7 and ACI-318 (2011). The results indicate that the prediction performance of new formulation is significantly higher as compared to available design equations and its reliability index is within acceptable limits.

Segregational Instability of a Recombinant Plasmid pDML6 in Streptomyces lividans

  • LEE, JUNG HYUN;JAE DEOG JANG;KYE JOON LEE
    • Journal of Microbiology and Biotechnology
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    • v.2 no.2
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    • pp.129-134
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    • 1992
  • Segregational instability of a recombinant plasmid, pDML6, encoding extracellular $\beta$-lactamase in Streptomyces lividans PD6 was characterized by growth kinetic analysis. The quantitative determination of the plasmid harbored in the mycelia was evaluated with mycelia fragmented mechanically, and also with colonies regenerated from protoplasts. Conditions for the formation of protoplasts and regeneration of protoplasts were established. The maximal specific growth rates of the host strain and the plasmid-harboring strain in a chemically defined medium without selection pressure were the same. The probability of plasmid loss from the harbouring cells was higher at higher growth rates. Mathematical models for the prediction of cell growth, substrate uptake, and accumulation of the cloned gene product were developed.

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Gene Prediction Using Phylogenomics and COG (계통유전체학과 COG를 이용한 유전자 기능예측)

  • 신창진;강병철;박준형;신동훈;김철민
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2004.04a
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    • pp.255-258
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    • 2004
  • 본 연구는 유전자 기능예측에 있어서 유사성 검색과 비교유전체학이 가진 한계를 극복하기 위하여 9종의 Human Herpesvirus를 대상으로 COG와 계통유전학적 방법을 적용하여 향상된 유전자 기능예측을 하고자 하였다. COG의 방법을 이용하여 114 HCOGs (Human Herpesvvirus COGs)를 구축하고, HCOGs를 바탕으로 유전자 컨텐츠트리를 제작하였다. 이 트리를 통하여 각 HCOG는 $\alpha$-특이적 그룹, $\beta$-특이적 그룹, $\alpha$, $\beta$, ${\gamma}$ -특이적 그룹 중 하나에 속함을 보였다. 계통유전체학의 적용을 위하여 u, $\beta$, ${\gamma}$ -특이 그룹에 속하는 ORF중 DNA polymerase를 이용하여 종트리를 제작하였다. SDI (Speciation and Duplication) 알고리즘을 통하여 148개의 당단백질에서 47개의 복제점을 예측하였고, 초기 HCOG의 제작에서 제외되었던 7 ORF는 당단백질과 관련된 5개의 HCOG로 재 정의 하였다. 이 연구를 통하여 COG는 ortholog 그룹을 를러스터링하는데 효과적인 방법이며, 이를 더욱 보완할 수 있는 방법으로 비교유전체학이 사용될 수 있음을 확인하였다. 이는 비교유전체학의 방법과 계통유전체학적 방법을 조화시켜 유전자 기능 예측을 보완할 수 있음을 보여 주었다.

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Evolutionary Optimization of Models for Mature microRNA Prediction (Mature microRNA 위치 예측 모델의 진화적 최적화)

  • Kim Jin-Han;Nam Jin-Wu;Zhang Byoung-Tak
    • Proceedings of the Korean Information Science Society Conference
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    • 2006.06a
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    • pp.67-69
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    • 2006
  • MicroRNA (miRNA)는 생체내에서 gene regulation에 관여하는 핵심 small RNA 중 하나이다. miRNA는 Primary miRNA, Precursor miRNA, mature miRNA의 과정으로 processing 된다. miRNA 최종 형태인 mature miRNA의 정확한 위치 예측은 miRNA 예측의 필수적인 부분이다. 본 논문에서는, 진화적 최적화 예측 모델 중 하나인 유전 알고리즘을 이용하여 mature miRNA의 정확한 위치 예측을 수행한다. 제시된 방법은 이미 알려진 mature miRNA 위치를 positive example로 하고 임의로 생성한 위치를 negative example로 하여 서로의 linear scoring function 적합성 함수의 값 차이가 최대한으로 되도록 예측 모델을 진화시킨다. 유전 알고리즘을 이용한 진화적 최적화 모델로부터 mature miRNA 위치 예측에서 약 1.7nt 오차를 보여 기존의 방법 보다 개선된 성능을 보인다.

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An XML-Based Analysis Tool for Gene Prediction Results (XML 기반의 유전자 예측결과 분석도구)

  • 변상희;윤형석;안건태;박양수;이명준
    • Proceedings of the Korean Information Science Society Conference
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    • 2004.04b
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    • pp.280-282
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    • 2004
  • 염기서열의 분석이 유전체에 대한 연구를 가능하게 해 줄 수 있다는 것이 밝혀짐에 따라 다양한 생명체에 대한 유전체 염기서열 분석 도구의 개발이 활발히 진행되었다. 이러한 유전자 예측 도구들은 고유의 단순 텍스트 형식으로 결과를 제공하므로 사용자는 결과를 분석하고 통계정보를 산출하는데 많은 노력이 필요하다. 본 논문에서는 유전자 예측결과를 보다 효율적으로 표현하고 분석하기 위한 XML 기반의 분석도구를 개발하였다. 개발된 시스템은 유전자 예측결과를 효과적으로 표현하는 GenStructML, 이 정보를 분석한 GenPredML과 PredAccuracyML로 구성되어 있다. GenPredML과 PredAccuracyML은 GenStructML에 대하여 뉴클레오티드 수준(nucleotide level), 엑손 수준(exon level) 그리고 신호 수준(signal level)에서의 예측 정확도(Accuracy)를 계산하고 Genbank의 정보와 비교하여 통계정보를 산출함으로써 보다 자세한 정보를 제공한다.

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Comparison of Gene Selection Method for Prediction of Non-muscle Bladder Cancer Recurrence (비침윤성 방광암 환자의 재발 예측을 위한 유전자 선택 기법 비교)

  • Lee, Kyung Seok;Park, Hyun Woo;Park, Soo Ho;Yun, Seok Joong;Ryu, Keun Ho
    • Proceedings of the Korea Information Processing Society Conference
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    • 2013.11a
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    • pp.87-89
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    • 2013
  • 이 논문에서는 비침윤성 방광암 환자의 재발 예측을 위해 마이크로어레이 데이터에서 최적의 속성 부분 집합을 찾고 이를 비교 평가한다. 정보 이득(information gain)을 통해 구한 상위 40개, 80개, 100개의 속성 집합과 FCBF(fast correlation based filter) 알고리즘을 적용하여 구한 최적의 속성 부분집합을 SVM 분류 모델에 적용하여 정확도를 비교 평가한 결과 정보 이득을 적용한 상위 100개 속성 부분집합의 분류 정확도가 가장 높게 나왔으며, FCBF 알고리즘을 적용한 속성 집합은 비교적 적은 속성을 사용하면서 이와 비슷한 분류 정확도를 보임을 확인할 수 있었다.