• Journal of Preventive Medicine and Public Health
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• 제42권6호
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• pp.349-355
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• 2009

Biomarkers are characteristic biological properties that can be detected and measured in a variety of biological matrices in the human body, including the blood and tissue, to give an indication of whether there is a threat of disease, if a disease already exists, or how such a disease may develop in an individual case. Along the continuum from exposure to clinical disease and progression, exposure, internal dose, biologically effective dose, early biological effect, altered structure and/or function, clinical disease, and disease progression can potentially be observed and quantified using biomarkers. While the traditional discovery of biomarkers has been a slow process, the advent of molecular and genomic medicine has resulted in explosive growth in the discovery of new biomarkers. In this review, issues in evaluating biomarkers will be discussed and the biomarkers of environmental exposure, early biologic effect, and susceptibility identified and validated in epidemiological studies will be summarized. The spectrum of genomic approaches currently used to identify and apply biomarkers and strategies to validate genomic biomarkers will also be discussed.

• Asian-Australasian Journal of Animal Sciences
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• 제29권7호
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• pp.938-943
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• 2016

Development of body hair is an important physiological and cellular process that leads to better adaption in tropical environments for dairy cattle. Various studies suggested a major gene and, more recently, associated genes for hairy locus in dairy cattle. Main aim of this study was to i) employ a variant of the discordant sib pair model, in which half sibs from the same sires are randomly sampled using their affection statues, ii) use various single marker regression approaches, and iii) use whole genome regression approaches to dissect genetic architecture of the hairy gene in the cattle. Whole and single genome regression approaches detected strong genomic signals from Chromosome 23. Although there is a major gene effect on hairy phenotype sourced from chromosome 23: whole genome regression approach also suggested polygenic component related with other parts of the genome. Such a result could not be obtained by any of the single marker approaches.

• Journal of Preventive Medicine and Public Health
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• 제36권3호
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• pp.213-222
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• 2003

Genomic epidemiology is defined as 'an evoking field of inquiring that uses the systematic application of epidemiologic methods are approaches in population-based studies of the impact of human genetic variation on health and disease (Khoury, 1998)'. Most human diseases are caused by the intricate interaction among environmental exposures and genetic susceptibility factors. Susceptibility genes involved in disease pathogenesis are categorized into two groups: high penetrance genes (i.e., BRAC1, RB, etc.) and lour penetranoe genes (i.e., GSTs, Cyps, XRCC1, ets.), and low penetrance susceptibility genes has the higher priority for epidemiological research due to high population attributable risk. In this paper, the summarized results of the association study between single nucleotide polymorphisms (SNPs) and breast cancer in Korea were introduced and the international trends of genomic epidemiology research were reviewed with an emphasis on internee-based case-control and cohort consortium.

• Genomics & Informatics
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• 제11권4호
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• pp.180-185
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• 2013

Development of liver cancers is driven largely by genomic alterations that deregulate signaling pathways, influencing growth and survival of cancer cells. Because of the hundreds or thousands of genomic/epigenomic alterations that have accumulated in the cancer genome, it is very challenging to find and test candidate genes driving tumor development and progression. Systematic studies of the liver cancer genome have become available in recent years. These studies have uncovered new potential driver genes, including those not previously known to be involved in the development of liver cancer. Novel approaches combining multiple datasets from patient tissues have created an unparalleled opportunity to uncover potential new therapeutic targets and prognostic/predictive biomarkers for personalized therapy that can improve clinical outcomes of the patients with liver cancer.

• 영어영문학
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• 제53권2호
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• pp.243-260
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• 2007

This article explores how Richard Powers' The Gold Bug Variations, an interdisciplinary novel through the new concepts of biocriticism and bioliterature is connected with literature/art and science/technology. Powers uses Edgar Allen Poe's "The Gold Bug" and Johann Sebastian Bach's "The Goldberg Variations" for decoding DNA in order to analogize a genomic metaphor. He imagines literature as "the book of life" genome, written by DNA code due to the complexity and multiplicity of the genome. His novel, as 'genomic narrative,' shows the articulation of the genomic reading, and expression in the life language through the discourses of the information technology and the rhetorical tropes in biology. New biological ideas are continually required to articulate these processes. In the present tendency of the Human Genome Project, such advanced devices as biocybernetics offer the potential to open up new possibilities to researching the complexity of the genome. This can only happen if the following two ideas are followed: One is to comply with advanced technologies for processing the rapidly increasing data of the genome sequence; The other is to admit the necessary paradigm shift in biology. As shown above, the complexity and multiplicity of the genomic reality is not so simple. We must go beyond determinism, even if representation of a biological reality reveals the possibility of expressing its constituent elements by the advanced biotechnology. Consequently, in the unstoppable advances of the art of decoding the genome, The Gold Bug Variations interrelates to the interdisciplinary approaches through the rhetorical tropes that unfold the complex discursive world of the genome. Powers shows that the complex mechanisms of the genome in the microworld of every cell as the plot of "the book of life" can be designed and written using DNA language. At the same time, his genomic reading and writing demonstrate the historical processes of the shifting center of new genomic development and polysemous interpretation.

• Animal Bioscience
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• 제37권4호
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• pp.622-630
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• 2024

Objective: Pig breeders cannot obtain phenotypic information at the time of selection for sow lifetime productivity (SLP). They would benefit from obtaining genetic information of candidate sows. Genomic data interpreted using deep learning (DL) techniques could contribute to the genetic improvement of SLP to maximize farm profitability because DL models capture nonlinear genetic effects such as dominance and epistasis more efficiently than conventional genomic prediction methods based on linear models. This study aimed to investigate the usefulness of DL for the genomic prediction of two SLP-related traits; lifetime number of litters (LNL) and lifetime pig production (LPP). Methods: Two bivariate DL models, convolutional neural network (CNN) and local convolutional neural network (LCNN), were compared with conventional bivariate linear models (i.e., genomic best linear unbiased prediction, Bayesian ridge regression, Bayes A, and Bayes B). Phenotype and pedigree data were collected from 40,011 sows that had husbandry records. Among these, 3,652 pigs were genotyped using the PorcineSNP60K BeadChip. Results: The best predictive correlation for LNL was obtained with CNN (0.28), followed by LCNN (0.26) and conventional linear models (approximately 0.21). For LPP, the best predictive correlation was also obtained with CNN (0.29), followed by LCNN (0.27) and conventional linear models (approximately 0.25). A similar trend was observed with the mean squared error of prediction for the SLP traits. Conclusion: This study provides an example of a CNN that can outperform against the linear model-based genomic prediction approaches when the nonlinear interaction components are important because LNL and LPP exhibited strong epistatic interaction components. Additionally, our results suggest that applying bivariate DL models could also contribute to the prediction accuracy by utilizing the genetic correlation between LNL and LPP.

• Molecules and Cells
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• 제24권1호
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• pp.105-112
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• 2007

Most neuroblastoma cells have chromosomal aberrations such as gains, losses, amplifications and deletions of DNA. Conventional approaches like fluorescence in situ hybridization (FISH) or metaphase comparative genomic hybridization (CGH) can detect chromosomal aberrations, but their resolution is low. In this study we used array-based comparative genomic hybridization to identify the chromosomal aberrations in human neuroblastoma SH-SY5Y cells. The DNA microarray consisting of 4000 bacterial artificial chromosome (BAC) clones was able to detect chromosomal regions with aberrations. The SH-SY5Y cells showed chromosomal gains in 1q12~ q44 (Chr1:142188905-246084832), 7 (over the whole chro-mosome), 2p25.3~p16.3 (Chr2:18179-47899074), and 17q 21.32~q25.3 (Chr17:42153031-78607159), while chromosomal losses detected were the distal deletion of 1p36.33 (Chr1:552910-563807), 14q21.1~q21.3 (Chr14:37666271-47282550), and 22q13.1~q13.2 (Chr22:36885764-4190 7123). Except for the gain in 17q21 and the loss in 1p36, the other regions of gain or loss in SH-SY5Y cells were newly identified.

• 한국미생물학회:학술대회논문집
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• 한국미생물학회 2007년도 International Meeting of the Microbiological Society of Korea
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• pp.29-31
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• 2007

• BMB Reports
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• 제44권5호
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• pp.291-297
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• 2011

Aging is one of the most complicated biological processes in all species. A number of different model organisms from yeast to monkeys have been studied to understand the aging process. Until recently, many different age-related genes and age-regulating cellular pathways, such as insulin/IGF-1-like signal, mitochondrial dysfunction, Sir2 pathway, have been identified through classical genetic studies. Parallel to genetic approaches, genome-wide approaches have provided valuable insights for the understanding of molecular mechanisms occurring during aging. Gene expression profiling analysis can measure the transcriptional alteration of multiple genes in a genome simultaneously and is widely used to elucidate the mechanisms of complex biological pathways. Here, current global gene expression profiling studies on normal aging and age-related genetic/environmental interventions in widely-used model organisms are briefly reviewed.

• Journal of Microbiology
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• 제44권2호
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• pp.137-144
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• 2006

The problems associated with gene identification and the prediction of gene structure in DNA sequences have been the focus of increased attention over the past few years with the recent acquisition by large-scale sequencing projects of an immense amount of genome data. A variety of prediction programs have been developed in order to address these problems. This paper presents a review of the computational approaches and gene-finders used commonly for gene prediction in eukaryotic genomes. Two approaches, in general, have been adopted for this purpose: similarity-based and ab initio techniques. The information gleaned from these methods is then combined via a variety of algorithms, including Dynamic Programming (DP) or the Hidden Markov Model (HMM), and then used for gene prediction from the genomic sequences.