• Title/Summary/Keyword: Gene Prediction

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Prediction and Analysis of Breast Cancer Related Deleterious Non-Synonymous Single Nucleotide Polymorphisms in the PTEN Gene

  • Naidu, C Kumaraswamy;Suneetha, Y
    • Asian Pacific Journal of Cancer Prevention
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    • v.17 no.4
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    • pp.2199-2203
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    • 2016
  • One of the most common cancer types faced by the women around the world is breast cancer. Among the several low, moderate and high penetrance genes conferring susceptibility to breast cancer, PTEN is one which is known to be mutated in many tumor types. In this study, we predicted and analyzed the impact of three deleterious coding non-synonymous single nucleotide polymorphisms rs121909218 (G129E), rs121909229 (R130Q) and rs57374291 (D107N) in the PTEN gene on the phenotype of breast tumors using computational tools SIFT, Polyphen-2, PROVEAN, MUPro, POPMusic and the GETAREA server.

Quantitative Assessment of the Diagnostic Role of CDH13 Promoter Methylation in Lung Cancer

  • Zhong, Yun-Hua;Peng, Hao;Cheng, Hong-Zhong;Wang, Ping
    • Asian Pacific Journal of Cancer Prevention
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    • v.16 no.3
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    • pp.1139-1143
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    • 2015
  • In order to explore the association between cadherin 13 (CDH13) gene promoter methylation and lung carcinoma (LC) risk, we carried out a meta-analysis with searching of PubMed, Web of Science. Ultimately, 17 articles were identified and analysised by STATA 12.0 software. Overall, we found a significant relationship between CDH13 promoter methylation and LC risk (odds ratio=6.98, 95% confidence interval: 4.21-11.56, p<0.001). Subgroup analyses further revealed that LC risk was increased for individuals carrying the methylated CDH13 compared with those with unmethylated CDH13. Hence, our study identified a strong association between CDH13 gene promoter methylation and LC and highlighted a promising potential for CDH13 methylation in LC risk prediction.

Detection of Mycoplasma Infection in Cultured Cells on the Basis of Molecular Profiling of Host Responses

  • Chung, Tae Su;Kim, Ju Han;Lee, Young-Ju;Park, Woong-Yang
    • Genomics & Informatics
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    • v.3 no.3
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    • pp.63-67
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    • 2005
  • Adaptive responses to diverse microbial pathogens might be limited in relatively few types. Host cell responses to pathogens are believed to be patterned or stereotyped along with species or class. We tried to compose the host response to Mycoplasma in terms of cellular gene expression. Although gene expression profile of two host HeLa and 293 cells were quite different each other, 30 genes were differentially expressed by mycoplasma infection in both of HeLa and 293 cells. Six of them (PR48, MADH4, MKPX, CRK, RBM7, NEK3) were related to cell cycle or proliferation. Another category of genes like IL1 HY1, KLRF1, TNFSF14, GBP1 were host defense to elicit immune responses. With this set of genes, we establish the prediction model for mycoplasma contamination.

Application of Multivariate Adaptive Regression Spline-Assisted Objective Function on Optimization of Heat Transfer Rate Around a Cylinder

  • Dey, Prasenjit;Das, Ajoy K.
    • Nuclear Engineering and Technology
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    • v.48 no.6
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    • pp.1315-1320
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    • 2016
  • The present study aims to predict the heat transfer characteristics around a square cylinder with different corner radii using multivariate adaptive regression splines (MARS). Further, the MARS-generated objective function is optimized by particle swarm optimization. The data for the prediction are taken from the recently published article by the present authors [P. Dey, A. Sarkar, A.K. Das, Development of GEP and ANN model to predict the unsteady forced convection over a cylinder, Neural Comput. Appl. (2015) 1-13]. Further, the MARS model is compared with artificial neural network and gene expression programming. It has been found that the MARS model is very efficient in predicting the heat transfer characteristics. It has also been found that MARS is more efficient than artificial neural network and gene expression programming in predicting the forced convection data, and also particle swarm optimization can efficiently optimize the heat transfer rate.

Genome-Wide Comparison of Carbohydrate-Active Enzymes (CAZymes) Repertoire of Flammulina ononidis

  • Park, Young-Jin;Kong, Won-Sik
    • Mycobiology
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    • v.46 no.4
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    • pp.349-360
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    • 2018
  • Whole-genome sequencing of Flammulina ononidis, a wood-rotting basidiomycete, was performed to identify genes associated with carbohydrate-active enzymes (CAZymes). A total of 12,586 gene structures with an average length of 2009 bp were predicted by the AUGUSTUS tool from a total 35,524,258 bp length of de novo genome assembly (49.76% GC). Orthologous analysis with other fungal species revealed that 7051 groups contained at least one F. ononidis gene. In addition, 11,252 (89.5%) of 12,586 genes for F. ononidis proteins had orthologs among the Dikarya, and F. ononidis contained 8 species-specific genes, of which 5 genes were paralogous. CAZyme prediction revealed 524 CAZyme genes, including 228 for glycoside hydrolases, 21 for polysaccharide lyases, 87 for glycosyltransferases, 61 for carbohydrate esterases, 87 with auxiliary activities, and 40 for carbohydrate-binding modules in the F. ononidis genome. This genome information including CAZyme repertoire will be useful to understand lignocellulolytic machinery of this white rot fungus F. ononidis.

The gene prediction method considering stages of cancer, obtained by integrating gene expression, genetic interaction data and document (문헌정보와 유전자 발현 및 상호 작용 데이터를 통합, 암의 단계를 고려한 질병 유전자 예측 방법)

  • Kim, Jungrim;Yeu, Yunku;Park, Sanghyun
    • Proceedings of the Korea Information Processing Society Conference
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    • 2013.11a
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    • pp.1113-1116
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    • 2013
  • 유전체에 대한 관심이 크게 증가하면서, 이에 따른 다양한 연구가 이루어졌다. 그 결과 유전체와 관련된 다양한 종류의 데이터가 얻어졌으며, 그것을 해석하고 다른 데이터와 통합하는 것이 중요한 연구과제 중 하나가 되었다. 본 논문은 유전자 상호작용(genetic interaction) 데이터, 유전자 발현 데이터, 문헌으로부터 텍스트마이닝 기술을 통해 얻은 이종(heterogeneous) 데이터를 통합하여 암과 관련이 있는 유전자를 찾는 실험을 수행하였다. 또한, 단순히 질병(disease)-정상(normal)의 대조가 아니라 암의 단계(stage)를 고려한 실험을 수행하였다. 데이터를 통합하지 않거나 암의 단계를 고려하지 않았을 경우에 비하여 제안하는 방법이 더 높은 유전자 예측 성능을 나타냈다.

Predicting Survival of DLBCL Patients in Pathway-Based Microarray Analysis (DLBCL 환자의 대사경로 정보를 이용한 생존예측)

  • Lee, Kwang-Hyun;Lee, Sun-Ho
    • The Korean Journal of Applied Statistics
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    • v.23 no.4
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    • pp.705-713
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    • 2010
  • Predicting survival from microarray data is not easy due to the problem of high dimensionality of data and the existence of censored observations. Also the limitation of individual gene analysis causes the shift of focus to the level of gene sets with functionally related genes. For developing a survival prediction model based on pathway information, the methods for selecting a supergene using principal component analysis and testing its significance for each pathway are discussed. Besides, the performance of gene filtering is compared.

A Case of Galactosemia with Novel Mutation in the GALT Gene (새로운 GALT 유전자의 돌연변이에 의한 갈락토스혈증)

  • Kim, Shin Ah;Shin, Young Lim;Hong, Yong Hee
    • Journal of The Korean Society of Inherited Metabolic disease
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    • v.13 no.2
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    • pp.126-130
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    • 2013
  • Galactosemia is a metabolic disorder inherited by the recessive autosome, and appears by the deficiency of one enzyme out of GALT (Galactose-1-Phosphate Uridyltransferase), GALK (galactokinase), and GALE (epimerase) enzymes, among which the GALT deficiency disease is denominated as classical galactosemia and known to have symptoms such as severe nausea, jaundice, hepatomegaly, sucking difficulty and so on. We report the case of a 16-day-old female baby with the new p.A101D mutation together with p.N413d in the GALT gene analysis found in the neonatal screening test and diagnosed to have galactosemia by the GALT deficiency through the enzyme analysis. For the prognosis prediction, the treatment, the genetic counseling and the prenatal diagnosis of the patients, more detailed genetic diagnosis is required by performing GALT gene analysis, and it is deemed to be necessary to analyze the correlation between the phenotype and the genotype of the domestic galactosemia patients.

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A Korean Case of Neonatal Nemaline Myopathy Carrying KLHL40 Mutations Diagnosed Using Next Generation Sequencing

  • Suh, Yoong-a;Sohn, Young Bae;Park, Moon Sung;Lee, Jang Hoon
    • Neonatal Medicine
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    • v.28 no.2
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    • pp.89-93
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    • 2021
  • Nemaline myopathy is a genetically heterogeneous neuromuscular disorder and one of the most common congenital myopathies. The clinical manifestations usually vary depending on the age of onset. Neonatal nemaline myopathy has the worst prognosis, primarily due to respiratory failure. Several genes associated with nemaline myopathy have been identified, including NEB, ACTA1, TPM3, TPM2, TNNT1, CFL2, KBTBD13, KLHL40, KLHL41, LMOD3, and KBTBD13. Here, we report a neonatal Korean female patient with nemaline myopathy carrying compound heterozygous mutations in the gene KLHL40 as revealed using next generation sequencing (NGS). The patient presented with postnatal cyanosis, respiratory failure, dysphagia, and hypotonia just after birth. To identify the genetic cause underlying the neonatal myopathy, NGS-based gene panel sequencing was performed. Compound heterozygous pathogenic variants were detected in KLHL40: c.[1405G>T];[1582G>A] (p. [Gly469cys];[Glu528Lys]). NGS allows quick and accurate diagnosis at a lower cost compared to traditional serial single gene sequencing, which is greatly advantageous in genetically heterogeneous disorders such as myopathies. Rapid diagnosis will facilitate efficient and timely genetic counseling, prediction of disease prognosis, and establishment of treatments.

Microbial Community Dysbiosis and Functional Gene Content Changes in Apple Flowers due to Fire Blight

  • Kong, Hyun Gi;Ham, Hyeonheui;Lee, Mi-Hyun;Park, Dong Suk;Lee, Yong Hwan
    • The Plant Pathology Journal
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    • v.37 no.4
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    • pp.404-412
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    • 2021
  • Despite the plant microbiota plays an important role in plant health, little is known about the potential interactions of the flower microbiota with pathogens. In this study, we investigated the microbial community of apple blossoms when infected with Erwinia amylovora. The long-read sequencing technology, which significantly increased the genome sequence resolution, thus enabling the characterization of fire blight-induced changes in the flower microbial community. Each sample showed a unique microbial community at the species level. Pantoea agglomerans and P. allii were the most predominant bacteria in healthy flowers, whereas E. amylovora comprised more than 90% of the microbial population in diseased flowers. Furthermore, gene function analysis revealed that glucose and xylose metabolism were enriched in diseased flowers. Overall, our results showed that the microbiome of apple blossoms is rich in specific bacteria, and the nutritional composition of flowers is important for the incidence and spread of bacterial disease.