• Title/Summary/Keyword: Bayesian clustering analysis

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Genetic Diversity and Relationships of Korean Chicken Breeds Based on 30 Microsatellite Markers

  • Suh, Sangwon;Sharma, Aditi;Lee, Seunghwan;Cho, Chang-Yeon;Kim, Jae-Hwan;Choi, Seong-Bok;Kim, Hyun;Seong, Hwan-Hoo;Yeon, Seong-Hum;Kim, Dong-Hun;Ko, Yeoung-Gyu
    • Asian-Australasian Journal of Animal Sciences
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    • v.27 no.10
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    • pp.1399-1405
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    • 2014
  • The effective management of endangered animal genetic resources is one of the most important concerns of modern breeding. Evaluation of genetic diversity and relationship of local breeds is an important factor towards the identification of unique and valuable genetic resources. This study aimed to analyze the genetic diversity and population structure of six Korean native chicken breeds (n = 300), which were compared with three imported breeds in Korea (n = 150). For the analysis of genetic diversity, 30 microsatellite markers from FAO/ISAG recommended diversity panel or previously reported microsatellite markers were used. The number of alleles ranged from 2 to 15 per locus, with a mean of 8.13. The average observed heterozygosity within native breeds varied between 0.46 and 0.59. The overall heterozygote deficiency ($F_{IT}$) in native chicken was $0.234{\pm}0.025$. Over 30.7% of $F_{IT}$ was contributed by within-population deficiency ($F_{IS}$). Bayesian clustering analysis, using the STRUCTURE software suggested 9 clusters. This study may provide the background for future studies to identify the genetic uniqueness of the Korean native chicken breeds.

Context-Dependent Classification of Multi-Echo MRI Using Bayes Compound Decision Model (Bayes의 복합 의사결정모델을 이용한 다중에코 자기공명영상의 context-dependent 분류)

  • 전준철;권수일
    • Investigative Magnetic Resonance Imaging
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    • v.3 no.2
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    • pp.179-187
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    • 1999
  • Purpose : This paper introduces a computationally inexpensive context-dependent classification of multi-echo MRI with Bayes compound decision model. In order to produce accurate region segmentation especially in homogeneous area and along boundaries of the regions, we propose a classification method that uses contextual information of local enighborhood system in the image. Material and Methods : The performance of the context free classifier over a statistically heterogeneous image can be improved if the local stationary regions in the image are disassociated from each other through the mechanism of the interaction parameters defined at he local neighborhood level. In order to improve the classification accuracy, we use the contextual information which resolves ambiguities in the class assignment of a pattern based on the labels of the neighboring patterns in classifying the image. Since the data immediately surrounding a given pixel is intimately associated with this given pixel., then if the true nature of the surrounding pixel is known this can be used to extract the true nature of the given pixel. The proposed context-dependent compound decision model uses the compound Bayes decision rule with the contextual information. As for the contextual information in the model, the directional transition probabilities estimated from the local neighborhood system are used for the interaction parameters. Results : The context-dependent classification paradigm with compound Bayesian model for multi-echo MR images is developed. Compared to context free classification which does not consider contextual information, context-dependent classifier show improved classification results especially in homogeneous and along boundaries of regions since contextual information is used during the classification. Conclusion : We introduce a new paradigm to classify multi-echo MRI using clustering analysis and Bayesian compound decision model to improve the classification results.

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Population Structure and Biodiversity of Chinese Indigenous Duck Breeds Revealed by 15 Microsatellite Markers

  • Liu, W.;Hou, Z.C.;Qu, L.J.;Huang, Y.H.;Yao, J.F.;Li, N.;Yang, N.
    • Asian-Australasian Journal of Animal Sciences
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    • v.21 no.3
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    • pp.314-319
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    • 2008
  • Duck (Anas platyrhynchos) is one of the most important domestic avian species in the world. In the present research, fifteen polymorphic microsatellite markers were used to evaluate the diversity and population structure of 26 Chinese indigenous duck breeds across the country. The Chinese breeds showed high variation with the observed heterozygosity (Ho) ranging from 0.401 (Jinding) to 0.615 (Enshi), and the expected heterozygosity (He) ranging from 0.498 (Jinding) to 0.707 (Jingjiang). In all of the breeds, the values of Ho were significantly lower than those of He, suggesting high selection pressure on these local breeds. AMOVA and Bayesian clustering analysis showed that some breeds had mixed together. The FST value for all breeds was 0.155, indicating medium differentiation of the Chinese indigenous breeds. The FST value also indicated the short domestication history of most of Chinese indigenous ducks and the admixture of these breeds after domestication. Understanding the genetic relationship and structure of these breeds will provide valuable information for further conservation and utilization of the genetic resources in ducks.

Survey of genetic structure of geese using novel microsatellite markers

  • Lai, Fang-Yu;Tu, Po-An;Ding, Shih-Torng;Lin, Min-Jung;Chang, Shen-Chang;Lin, En-Chung;Lo, Ling-Ling;Wang, Pei-Hwa
    • Asian-Australasian Journal of Animal Sciences
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    • v.31 no.2
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    • pp.167-179
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    • 2018
  • Objective: The aim of this study was to create a set of microsatellite markers with high polymorphism for the genetic monitoring and genetic structure analysis of local goose populations. Methods: Novel microsatellite markers were isolated from the genomic DNA of white Roman geese using short tandem repeated probes. The DNA segments, including short tandem repeats, were tested for their variability among four populations of geese from the Changhua Animal Propagation Station (CAPS). The selected microsatellite markers could then be used to monitor genetic variability and study the genetic structures of geese from local geese farms. Results: 14 novel microsatellite loci were isolated. In addition to seven known loci, two multiplex sets were constructed for the detection of genetic variations in geese populations. The average of allele number, the effective number of alleles, the observed heterozygosity, the expected heterozygosity, and the polymorphism information content were 11.09, 5.145, 0.499, 0.745, and 0.705, respectively. The results of analysis of molecular variance and principal component analysis indicated a contracting white Roman cluster and a spreading Chinese cluster. In white Roman populations, the CAPS populations were depleted to roughly two clusters when K was set equal to 6 in the Bayesian cluster analysis. The founders of private farm populations had a similar genetic structure. Among the Chinese geese populations, the CAPS populations and private populations represented different clads of the phylogenetic tree and individuals from the private populations had uneven genetic characteristics according to various analyses. Conclusion: Based on this study's analyses, we suggest that the CAPS should institute a proper breeding strategy for white Roman geese to avoid further clustering. In addition, for preservation and stable quality, the Chinese geese in the CAPS and the aforementioned proper breeding scheme should be introduced to geese breeders.

A Study on Differences of Contents and Tones of Arguments among Newspapers Using Text Mining Analysis (텍스트 마이닝을 활용한 신문사에 따른 내용 및 논조 차이점 분석)

  • Kam, Miah;Song, Min
    • Journal of Intelligence and Information Systems
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    • v.18 no.3
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    • pp.53-77
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    • 2012
  • This study analyses the difference of contents and tones of arguments among three Korean major newspapers, the Kyunghyang Shinmoon, the HanKyoreh, and the Dong-A Ilbo. It is commonly accepted that newspapers in Korea explicitly deliver their own tone of arguments when they talk about some sensitive issues and topics. It could be controversial if readers of newspapers read the news without being aware of the type of tones of arguments because the contents and the tones of arguments can affect readers easily. Thus it is very desirable to have a new tool that can inform the readers of what tone of argument a newspaper has. This study presents the results of clustering and classification techniques as part of text mining analysis. We focus on six main subjects such as Culture, Politics, International, Editorial-opinion, Eco-business and National issues in newspapers, and attempt to identify differences and similarities among the newspapers. The basic unit of text mining analysis is a paragraph of news articles. This study uses a keyword-network analysis tool and visualizes relationships among keywords to make it easier to see the differences. Newspaper articles were gathered from KINDS, the Korean integrated news database system. KINDS preserves news articles of the Kyunghyang Shinmun, the HanKyoreh and the Dong-A Ilbo and these are open to the public. This study used these three Korean major newspapers from KINDS. About 3,030 articles from 2008 to 2012 were used. International, national issues and politics sections were gathered with some specific issues. The International section was collected with the keyword of 'Nuclear weapon of North Korea.' The National issues section was collected with the keyword of '4-major-river.' The Politics section was collected with the keyword of 'Tonghap-Jinbo Dang.' All of the articles from April 2012 to May 2012 of Eco-business, Culture and Editorial-opinion sections were also collected. All of the collected data were handled and edited into paragraphs. We got rid of stop-words using the Lucene Korean Module. We calculated keyword co-occurrence counts from the paired co-occurrence list of keywords in a paragraph. We made a co-occurrence matrix from the list. Once the co-occurrence matrix was built, we used the Cosine coefficient matrix as input for PFNet(Pathfinder Network). In order to analyze these three newspapers and find out the significant keywords in each paper, we analyzed the list of 10 highest frequency keywords and keyword-networks of 20 highest ranking frequency keywords to closely examine the relationships and show the detailed network map among keywords. We used NodeXL software to visualize the PFNet. After drawing all the networks, we compared the results with the classification results. Classification was firstly handled to identify how the tone of argument of a newspaper is different from others. Then, to analyze tones of arguments, all the paragraphs were divided into two types of tones, Positive tone and Negative tone. To identify and classify all of the tones of paragraphs and articles we had collected, supervised learning technique was used. The Na$\ddot{i}$ve Bayesian classifier algorithm provided in the MALLET package was used to classify all the paragraphs in articles. After classification, Precision, Recall and F-value were used to evaluate the results of classification. Based on the results of this study, three subjects such as Culture, Eco-business and Politics showed some differences in contents and tones of arguments among these three newspapers. In addition, for the National issues, tones of arguments on 4-major-rivers project were different from each other. It seems three newspapers have their own specific tone of argument in those sections. And keyword-networks showed different shapes with each other in the same period in the same section. It means that frequently appeared keywords in articles are different and their contents are comprised with different keywords. And the Positive-Negative classification showed the possibility of classifying newspapers' tones of arguments compared to others. These results indicate that the approach in this study is promising to be extended as a new tool to identify the different tones of arguments of newspapers.

Genetic Traceability of Black Pig Meats Using Microsatellite Markers

  • Oh, Jae-Don;Song, Ki-Duk;Seo, Joo-Hee;Kim, Duk-Kyung;Kim, Sung-Hoon;Seo, Kang-Seok;Lim, Hyun-Tae;Lee, Jae-Bong;Park, Hwa-Chun;Ryu, Youn-Chul;Kang, Min-Soo;Cho, Seoae;Kim, Eui-Soo;Choe, Ho-Sung;Kong, Hong-Sik;Lee, Hak-Kyo
    • Asian-Australasian Journal of Animal Sciences
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    • v.27 no.7
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    • pp.926-931
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    • 2014
  • Pork from Jeju black pig (population J) and Berkshire (population B) has a unique market share in Korea because of their high meat quality. Due to the high demand of this pork, traceability of the pork to its origin is becoming an important part of the consumer demand. To examine the feasibility of such a system, we aim to provide basic genetic information of the two black pig populations and assess the possibility of genetically distinguishing between the two breeds. Muscle samples were collected from slaughter houses in Jeju Island and Namwon, Chonbuk province, Korea, for populations J and B, respectively. In total 800 Jeju black pigs and 351 Berkshires were genotyped at thirteen microsatellite (MS) markers. Analyses on the genetic diversity of the two populations were carried out in the programs MS toolkit and FSTAT. The population structure of the two breeds was determined by a Bayesian clustering method implemented in structure and by a phylogenetic analysis in Phylip. Population J exhibited higher mean number of alleles, expected heterozygosity and observed heterozygosity value, and polymorphism information content, compared to population B. The $F_{IS}$ values of population J and population B were 0.03 and -0.005, respectively, indicating that little or no inbreeding has occurred. In addition, genetic structure analysis revealed the possibility of gene flow from population B to population J. The expected probability of identify value of the 13 MS markers was $9.87{\times}10^{-14}$ in population J, $3.17{\times}10^{-9}$ in population B, and $1.03{\times}10^{-12}$ in the two populations. The results of this study are useful in distinguishing between the two black pig breeds and can be used as a foundation for further development of DNA markers.

Genetic Variation of Korean Fir Sub-Populations in Mt. Jiri for the Restoration of Genetic Diversity (유전다양성 복원을 위한 지리산 구상나무 아집단의 유전변이)

  • Ahn, Ji Young;Lim, Hyo-In;Ha, Hyun-Woo;Han, Jingyu;Han, Sim-Hee
    • Journal of Korean Society of Forest Science
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    • v.106 no.4
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    • pp.417-423
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    • 2017
  • To provide a ecological restoration strategy considering genetic diversity of Abies koreana in Mt. Jiri, the genetic diversity and the genetic differentiation among sub-populations such as Banyabong, Byeoksoryeong, and Cheonwangbong were investigated. The average number of alleles (A) was 7.8, the average number of effective alleles ($A_e$) was 4.9, observed heterozygosity ($H_o$) was 0.578, and expected heterozygosity ($H_e$) was 0.672, respectively. The level of genetic diversity within sub-populations ($H_e=0.672$) was lower than those of both population ($H_e=0.778$) and species ($H_e=0.759$) level. However, the level of genetic diversity was high compared those of Genus Abies. Genetic differentiation was 0.014 from F-statistics ($F_{ST}$) and was 0.004 from AMOVA analysis (${\Phi}_{ST}$). There was no almost genetic differentiation among sub-populations in Mt. Jiri from bayesian clustering. Therefore, If the seeds are sampled sufficiently by selecting the parameters from three sub-populations, it is possible that we could obtain genetically appropriate materials for ecological restoration.

A Study on derivation of drought severity-duration-frequency curve through a non-stationary frequency analysis (비정상성 가뭄빈도 해석 기법에 따른 가뭄 심도-지속기간-재현기간 곡선 유도에 관한 연구)

  • Jeong, Minsu;Park, Seo-Yeon;Jang, Ho-Won;Lee, Joo-Heon
    • Journal of Korea Water Resources Association
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    • v.53 no.2
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    • pp.107-119
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    • 2020
  • This study analyzed past drought characteristics based on the observed rainfall data and performed a long-term outlook for future extreme droughts using Representative Concentration Pathways 8.5 (RCP 8.5) climate change scenarios. Standardized Precipitation Index (SPI) used duration of 1, 3, 6, 9 and 12 months, a meteorological drought index, was applied for quantitative drought analysis. A single long-term time series was constructed by combining daily rainfall observation data and RCP scenario. The constructed data was used as SPI input factors for each different duration. For the analysis of meteorological drought observed relatively long-term since 1954 in Korea, 12 rainfall stations were selected and applied 10 general circulation models (GCM) at the same point. In order to analyze drought characteristics according to climate change, trend analysis and clustering were performed. For non-stationary frequency analysis using sampling technique, we adopted the technique DEMC that combines Bayesian-based differential evolution ("DE") and Markov chain Monte Carlo ("MCMC"). A non-stationary drought frequency analysis was used to derive Severity-Duration-Frequency (SDF) curves for the 12 locations. A quantitative outlook for future droughts was carried out by deriving SDF curves with long-term hydrologic data assuming non-stationarity, and by quantitatively identifying potential drought risks. As a result of performing cluster analysis to identify the spatial characteristics, it was analyzed that there is a high risk of drought in the future in Jeonju, Gwangju, Yeosun, Mokpo, and Chupyeongryeong except Jeju corresponding to Zone 1-2, 2, and 3-2. They could be efficiently utilized in future drought management policies.