• Molecules and Cells
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• v.38 no.3
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• pp.210-220
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• 2015

Athletic performance is an important criteria used for the selection of superior horses. However, little is known about exercise-related epigenetic processes in the horse. DNA methylation is a key mechanism for regulating gene expression in response to environmental changes. We carried out comparative genomic analysis of genome-wide DNA methylation profiles in the blood samples of two different thoroughbred horses before and after exercise by methylated-DNA immunoprecipitation sequencing (MeDIP-Seq). Differentially methylated regions (DMRs) in the pre-and post-exercise blood samples of superior and inferior horses were identified. Exercise altered the methylation patterns. After 30 min of exercise, 596 genes were hypomethy-lated and 715 genes were hypermethylated in the superior horse, whereas in the inferior horse, 868 genes were hypomethylated and 794 genes were hypermethylated. These genes were analyzed based on gene ontology (GO) annotations and the exercise-related pathway patterns in the two horses were compared. After exercise, gene regions related to cell division and adhesion were hypermethylated in the superior horse, whereas regions related to cell signaling and transport were hypermethylated in the inferior horse. Analysis of the distribution of methylated CpG islands confirmed the hypomethylation in the gene-body methylation regions after exercise. The methylation patterns of transposable elements also changed after exercise. Long interspersed nuclear elements (LINEs) showed abundance of DMRs. Collectively, our results serve as a basis to study exercise-based reprogramming of epigenetic traits.

• Journal of Physiology & Pathology in Korean Medicine
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• v.26 no.4
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• pp.551-556
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• 2012

The database for the oriental medicine had been existed in documentation in past times and it has been developed to the database type for random accesses in the information society. However, the aspects of the database are not so diversified and the database for the bio herbal material exists in widened type dictionary style. It is a situation that the database which handles the in-depth raw herbal medicines is not sufficient in its quantity and quality. Korean wild grape is a deciduous plant categorized into the Vitaceae and it was found experimentally that it has various medical effects. It is one of the medical materials with higher potentiality of academic study and commercialization recently because it has a bigger possibility to be applied into diverse industrial fields including the medical product for health, food and beauty. We constituted the cooperative system among the Muju cluster business group for Korean mountain wild grapes, Physiology Laboratory in Kyung Hee University Oriental Medicine and Medical Classics Laboratory in Kyung Hee University Oriental Medicine with a view to focusing on such potentiality and a database for Korean wild grapes was made a touchstone for establishing the in-depth database for the single bio medical materials. First of all, the literatures based on the North East Asia in ancient times had been categorized into the classical literature (Korean literature published by government organization, Korean classical literature, Chinese classical literature and classical literature fro Korean and Chinese oriental medicine) and modern literature (Modern literature for oriental medicine, modern literature for domestic and foreign herbal medicine) to cover the eastern and western research records and writings related to Korean wild grapes and the text-mining work has been performed through the cooperation system with the Medical Classics Laboratory in Kyung Hee University Oriental Medicine. First of all, the data for the experiment and theory for Korean wild grape were collected for the Medline database controlled by the Parliament Library of USA to arrange the domestic and foreign theses with topic for Korean wild grapes and the network hyperlink function and down load function were mounted for self-thesis searching function and active view based on the collected data. The thesis searching function provides various auxiliary functions and the searching is available according to the diverse searching/queries such as the name of sub species of Korean wild grape, the logical intersection index for the active ingredients, efficacy and elements. It was constituted for the researchers who design the Korean wild grape study to design of easier experiment. In addition, the data related to the patents for Korean wild grape which were collected from European Patent Office in response to the commercialization possibility and the system available for searching and view was established in the same viewpoint. Perl was used for the query programming and MS-SQL for database establishment and management in the designing of this database. Currently, the data is available for free use and the address is as follows. http://163.180.41.43:8011/index.html

• Asian-Australasian Journal of Animal Sciences
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• v.29 no.11
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• pp.1653-1663
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• 2016

Meat quality is a complex trait influenced by many factors, including genetics, nutrition, feeding environment, animal handling, and their interactions. To elucidate relevant factors affecting pork quality associated with oxidative stress and muscle development, we analyzed protein expression in high quality longissimus dorsi muscles (HQLD) and low quality longissimus dorsi muscles (LQLD) from Duroc pigs by liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based proteomic analysis. Between HQLD (n = 20) and LQLD (n = 20) Duroc pigs, 24 differentially expressed proteins were identified by LC-MS/MS. A total of 10 and 14 proteins were highly expressed in HQLD and LQLD, respectively. The 24 proteins have putative functions in the following seven categories: catalytic activity (31%), ATPase activity (19%), oxidoreductase activity (13%), cytoskeletal protein binding (13%), actin binding (12%), calcium ion binding (6%), and structural constituent of muscle (6%). Silver-stained image analysis revealed significant differential expression of lactate dehydrogenase A (LDHA) between HQLD and LQLD Duroc pigs. LDHA was subjected to in vitro study of myogenesis under oxidative stress conditions and LDH activity assay to verification its role in oxidative stress. No significant difference of mRNA expression level of LDHA was found between normal and oxidative stress condition. However, LDH activity was significantly higher under oxidative stress condition than at normal condition using in vitro model of myogenesis. The highly expressed LDHA was positively correlated with LQLD. Moreover, LDHA activity increased by oxidative stress was reduced by antioxidant resveratrol. This paper emphasizes the importance of differential expression patterns of proteins and their interaction for the development of meat quality traits. Our proteome data provides valuable information on important factors which might aid in the regulation of muscle development and the improvement of meat quality in longissimus dorsi muscles of Duroc pigs under oxidative stress conditions.

• Nuclear Medicine and Molecular Imaging
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• v.41 no.4
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• pp.299-308
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• 2007

Purpose: The aim of this study was to develop a bioinformatics software and to test it in serum samples of papillary thyroid cancer using mass spectrometry (SELDI-TOF-MS). Materials and Methods: Development of 'Protein analysis' software performing decision tree analysis was done by customizing C4.5. Sixty-one serum samples from 27 papillary thyroid cancer, 17 autoimmune thyroiditis, 17 controls were applied to 2 types of protein chips, CM10 (weak cation exchange) and IMAC3 (metal binding - Cu). Mass spectrometry was performed to reveal the protein expression profiles. Decision trees were generated using 'Protein analysis' software, and automatically detected biomarker candidates. Validation analysis was performed for CM10 chip by random sampling. Results: Decision tree software, which can perform training and validation from profiling data, was developed. For CM10 and IMAC3 chips, 23 of 113 and 8 of 41 protein peaks were significantly different among 3 groups (p<0.05), respectively. Decision tree correctly classified 3 groups with an error rate of 3.3% for CM10 and 2.0% for IMAC3, and 4 and 7 biomarker candidates were detected respectively. In 2 group comparisons, all cancer samples were correctly discriminated from non-cancer samples (error rate = 0%) for CM10 by single node and for IMAC3 by multiple nodes. Validation results from 5 test sets revealed SELDI-TOF-MS and decision tree correctly differentiated cancers from non-cancers (54/55, 98%), while predictability was moderate in 3 group classification (36/55, 65%). Conclusion: Our in-house software was able to successfully build decision trees and detect biomarker candidates, therefore it could be useful for biomarker discovery and clinical follow up of papillary thyroid cancer.

• Journal of Life Science
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• v.27 no.10
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• pp.1215-1224
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• 2017

Until now, various oncogenic pathways were idenfied. The accumulation of DNA mutation induces genomic instability in the cell, and it makes cancer. The development of bioinformatics and genomics, to find the precise and reliable biomarker is available. This biomarker could be applied the early-dignosis, prediction and convalescence of cancer. Recently, Transposable elements (TEs) have been attracted as the regulator of genes, because they occupy a half of human genome, and the cause of various diseases. TEs induce DNA mutation, as well as the regulation of gene expression, that makes to cancer development. So, we confirmed the relationship between TEs and colon cancer, and provided the clue for colon cancer biomarker. First, we confirmed long interspersed nuclear element-1 (LINE-1), Alu, and long terminal repeats (LTRs) and their relationship to colon cancer. Because these elements have large composition and enormous effect to the human genome. Interestingly, colon cancer specific patterns were detected, such as the hypomethylation of LINE-1, LINE-1 insertion in the APC gene, hypo- or hypermethylation of Alu, and isoform derived from LTR insertion. Moreover, hypomethylation of LINE-1 in proto-oncogene is used as the biomarker of colon cancer metastasis, and MLH1 mutation induced by Alu is detected in familial or hereditary colon cancer. The genes, effected by TEs, were analyzed their expression patterns by in silico analysis. Then, we provided tissue- and gender-specific expression patterns. This information can provide reliable cancer biomarker, and apply to prediction and diagnosis of colon cancer.

• Journal of Life Science
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• v.27 no.11
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• pp.1331-1339
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• 2017

DNA barcoding is the identification of a species based on the DNA sequence of a fragment of the cytochrome C oxidase subunit I (COI) gene in the mitochondrial genome. It is widely applied to assist with the sustainable development of fishery-product resources and the protection of fish biodiversity. This study attempted to verify horse-head fish (Branchiostegus japonicus) and fake horse-head fish (Branchiostegus albus) species, which are commonly consumed in Korea. For the validation of the two species, a real-time PCR method was developed based on the species' mitochondrial DNA genome. Inter-species variations in mitochondrial DNA were observed in a bioinformatics analysis of the mitochondrial genomic DNA sequences of the two species. Some highly conserved regions and a few other regions were identified in the mitochondrial COI of the species. In order to test whether variations in the sequences were definitive, primers that targeted the varied regions of COI were designed and applied to amplify the DNA using the real-time PCR system. Threshold-cycle (Ct) range results confirmed that the Ct ranges of the real-time PCR were identical to the expected species of origin. Efficiency, specificity and cross-reactivity assays showed statistically significant differences between the average Ct of B. japonicus DNA ($21.85{\pm}3.599$) and the average Ct of B. albus DNA ($33.49{\pm}1.183$) for confirming B. japonicus. The assays also showed statistically significant differences between the average Ct of B. albus DNA ($22.49{\pm}0.908$) and the average Ct of B. japonicus DNA ($33.93{\pm}0.479$) for confirming B. albus. The methodology was validated by using ten commercial samples. The genomic DNA-based molecular technique that used the real-time PCR was a reliable method for the taxonomic classification of animal tissues.

• Journal of Life Science
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• v.20 no.3
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• pp.381-387
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• 2010

To find offspring of Jeju Black cattle (JBC) produced by embryo transfer (ET) and artificial insemination (AI), a molecular genetic study was carried out in candidate cattle populations collected from cattle farms in Jeju Island, Korea. The genetic marker set was composed of 11 ISAG microsatellite (MS) markers, 11 SAES MS markers selected by our preliminary analysis for population diversity of JBC and two major coat color related genes: MC1R and ASIP. The results showed a combined non-exclusion probability for first parent (NE-P1) that was higher than that recommended by ISAG (above 0.9995), and a combined non-exclusion probability for sib identity of $5.3{\times}10^{-10}$. Parentage analysis showed that the cases identified the candidate's father only (77.0%), mother only (54.0%), and both parents (40.5%) in the candidate offspring population. The ET and AI calves were identified as 14.7% in the in vitro fertilized eggs provided and 32.4% in total population, respectively. However, the result from ISAG marker analysis showed 3 identical allele-combinations in 7 calves, and that from ISAG/SAES MS marker combination also showed 1 identical allele-combination in 2 calves. Data from MS and coat-color gene analyses provided information for complete identification of all animals tested. Because the present JBC population was mostly bred using small nuclear founders through bioengineering techniques such as AI and ET, the genetic diversity levels obtained from MS analysis in the JBC population were relatively lower than those of other cattle populations, including Hanwoo. The results suggested that the more efficient marker combinations, including coat color related genotypes, should be studied and used for constructing a system for identification and molecular breeding of JBC as well.

• Journal of Plant Biotechnology
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• v.33 no.3
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• pp.153-160
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• 2006

Brassica rape is an important species used as a vegetable, oil, and fodder worldwide. It is related phylogenically to Arabidopsis thaliana, which has already been fully sequenced as a model plant. The 'Multinational Brassica Genome Project (MBGP)'was launched by the international Brassica community with the aim of sequencing the whole genome of B. rapa in 2003 on account of its value and the fact that it has the smallest genome among the diploid Brassica. The genome study was carried out not only to know the structure of genome but also to understand the function and the evolution of the genes comprehensively. There are two mapping populations, over 1,000 molecular markers and a genetic map, 2 BAC libraries, physical map, a 22 cDHA libraries as suitable genomic materials for examining the genome of B. rapa ssp. pekinensis Chinese cabbage. As the first step for whole genome analysis, 220,000 BAC-end sequences of the KBrH and KBrB BAC library are achieved by cooperation of six countries. The results of BAC-end sequence analysis will provide a clue in understanding the structure of the genome of Brassica rapa by analyzing the gene sequence, annotation and abundant repetitive DHA. The second stage involves sequencing of the genetically mapped seed BACs and identifying the overlapping BACs for complete genome sequencing. Currently, the second stage is comprises of process genetic anchoring using communal populations and maps to identify more than 1,000 seed BACs based on a BAC-to-BAC strategy. For the initial sequencing, 629 seed BACs corresponding to the minimum tiling path onto Arabidopsis genome were selected and fully sequenced. These BACs are now anchoring to the genetic map using the development of SSR markers. This information will be useful for identifying near BAC clones with the seed BAC on a genome map. From the BAC sequences, it is revealed that the Brassica rapa genome has extensive triplication of the DNA segment coupled with variable gene losses and rearrangements within the segments. This article introduces the current status and prospective of Korea Brassica Genome Project and the bioinformatics tools possessed in each national team. In the near future, data of the genome will contribute to improving Brassicas for their economic use as well as in understanding the evolutional process.

• Journal of Applied Biological Chemistry
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• v.57 no.2
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• pp.145-152
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• 2014

To evaluate the improving effects of antioxidant activity, we observed antioxidant capacities such as electron donating ability (EDA), Ferric reducing antioxidant power (FRAP), inhibitory activity of xanthine oxidase (XO) and aldehyde oxidase (AO), and sensory characteristics on mixture of Smilax china L. root water extract added with water extract of fermented S. china L. leaf by Aspergillus oryzae (FSCL). Those contents of mixture with higher ratio of FSCL were proportionally high. And OD475 of mixture with higher ratio of FSCL was almost proportionally high ($R^2=0.9850$). Antioxidant capacities of EDA and FRAP of the mixture was higher than that of non-mixture. In addition, XO inhibitory activity ($IC_{50}$) of A (1.19) was 59.80% higher than that of F (2.96), and the activity of mixture by the higher ratio of FSCL was proportionally low ($R^2=0.9490$). Taste acceptability of A was slightly higher than that of F, whereas that of C was highest. And color acceptability of 40-80% mixture was higher than those of A, F, and B. Overall acceptability of C and D was highest than those of others. Moreover, hot water extract of S. china L. leaf fermented with A. oryzae was maroon color, which looks like Puerh tea style, and mixture of S. china L. root extract added with hot water extract of S. china L. leaf was high acceptability of beverage. These results suggest that mixture of extract of S. china L. root and hot water extract of S. china L. leaf fermented with A. oryzae could improve antioxidant activities.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.127-142
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• 2016

Deep learning model is a kind of neural networks that allows multiple hidden layers. There are various deep learning architectures such as convolutional neural networks, deep belief networks and recurrent neural networks. Those have been applied to fields like computer vision, automatic speech recognition, natural language processing, audio recognition and bioinformatics where they have been shown to produce state-of-the-art results on various tasks. Among those architectures, convolutional neural networks and recurrent neural networks are classified as the supervised learning model. And in recent years, those supervised learning models have gained more popularity than unsupervised learning models such as deep belief networks, because supervised learning models have shown fashionable applications in such fields mentioned above. Deep learning models can be trained with backpropagation algorithm. Backpropagation is an abbreviation for "backward propagation of errors" and a common method of training artificial neural networks used in conjunction with an optimization method such as gradient descent. The method calculates the gradient of an error function with respect to all the weights in the network. The gradient is fed to the optimization method which in turn uses it to update the weights, in an attempt to minimize the error function. Convolutional neural networks use a special architecture which is particularly well-adapted to classify images. Using this architecture makes convolutional networks fast to train. This, in turn, helps us train deep, muti-layer networks, which are very good at classifying images. These days, deep convolutional networks are used in most neural networks for image recognition. Convolutional neural networks use three basic ideas: local receptive fields, shared weights, and pooling. By local receptive fields, we mean that each neuron in the first(or any) hidden layer will be connected to a small region of the input(or previous layer's) neurons. Shared weights mean that we're going to use the same weights and bias for each of the local receptive field. This means that all the neurons in the hidden layer detect exactly the same feature, just at different locations in the input image. In addition to the convolutional layers just described, convolutional neural networks also contain pooling layers. Pooling layers are usually used immediately after convolutional layers. What the pooling layers do is to simplify the information in the output from the convolutional layer. Recent convolutional network architectures have 10 to 20 hidden layers and billions of connections between units. Training deep learning networks has taken weeks several years ago, but thanks to progress in GPU and algorithm enhancement, training time has reduced to several hours. Neural networks with time-varying behavior are known as recurrent neural networks or RNNs. A recurrent neural network is a class of artificial neural network where connections between units form a directed cycle. This creates an internal state of the network which allows it to exhibit dynamic temporal behavior. Unlike feedforward neural networks, RNNs can use their internal memory to process arbitrary sequences of inputs. Early RNN models turned out to be very difficult to train, harder even than deep feedforward networks. The reason is the unstable gradient problem such as vanishing gradient and exploding gradient. The gradient can get smaller and smaller as it is propagated back through layers. This makes learning in early layers extremely slow. The problem actually gets worse in RNNs, since gradients aren't just propagated backward through layers, they're propagated backward through time. If the network runs for a long time, that can make the gradient extremely unstable and hard to learn from. It has been possible to incorporate an idea known as long short-term memory units (LSTMs) into RNNs. LSTMs make it much easier to get good results when training RNNs, and many recent papers make use of LSTMs or related ideas.