• IMMUNE NETWORK
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• v.11 no.6
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• pp.324-335
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• 2011

The human leukocyte antigen (HLA), the major histocompatibility complex (MHC) in humans has been known to reside on chromosome 6 and encodes cell-surface antigen-presenting proteins and many other proteins related to immune system function. The HLA is highly polymorphic and the most genetically variable coding loci in humans. In addition to a critical role in transplantation medicine, HLA and disease associations have been widely studied across the populations worldwide and are found to be important in prediction of disease susceptibility, resistance and of evolutionary maintenance of genetic diversity. Because recently developed molecular based HLA typing has several advantages like improved specimen stability and increased resolution of HLA types, the association between HLA alleles and a given disease could be more accurately quantified. Here, in this review, we have collected HLA association data on some autoimmune diseases, infectious diseases, cancers, drug responsiveness and other diseases with unknown etiology in Koreans and attempt to summarize some remarkable HLA alleles related with specific diseases.

• Korean Journal of Breeding Science
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• v.41 no.1
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• pp.9-15
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• 2009

Recently, giant embryonic rice and functional rice food are preferred by more consumers, which are attributed to the fact that the embryo has high concentrations of essential amino acids, fatty acids, and vitamins relative to other parts of rice grains. In this report, the heredity and stability of giant embryo mutations in successive generations were analyzed regarding a giant embryonic line, 'P47', induced by T-DNA insertion and a $F_2$ population from a cross between 'P47' and 'Junam'. The mutant lines with increases of 1.5, 1.7 and 1.8 times on embryo length, width and 100-embryo weight to those of the control showed stable inheritance across three generations. The continuous frequency distributions of embryo size in the $F_2$ population showed that the embryo size is a quantitative trait of polygene controlled. In addition, wide range of transgressive segregations of six traits affecting embryo size confirmed exchange of genetic materials and recombination between genes controlling embryo size. Five giant embryo mutant lines selected from the $F_2$ population will be used for artificial selection and improvement of giant embryonic varieties.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2011.04a
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• pp.397-400
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• 2011

MDO Optimization for a low pressure axial compressor rotor has been carried out to improve aerodynamic performance and structural stability. Global optimized solution was obtained from an artificial neural network model with genetic algorithm. Optimized rotor model has a high blade loading near hub and near zero incidence flow angle near tip region to reduce the incidence loss and flow separation at trailing edge region. Also the rotor shape is converged to a trapezoid shape to reduce the maximum stress occurred at the root of the blade. Numerical simulation results show that rotor has 87.6% rotor efficiency and safety factor over than 3.

• Smart Structures and Systems
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• v.18 no.3
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• pp.425-448
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• 2016

In this paper, a new Pigeon Colony Algorithm (PCA) based on the features of a pigeon colony flying is proposed for solving global numerical optimization problems. The algorithm mainly consists of the take-off process, flying process and homing process, in which the take-off process is employed to homogenize the initial values and look for the direction of the optimal solution; the flying process is designed to search for the local and global optimum and improve the global worst solution; and the homing process aims to avoid having the algorithm fall into a local optimum. The impact of parameters on the PCA solution quality is investigated in detail. There are low-dimensional functions, high-dimensional functions and systems of nonlinear equations that are used to test the global optimization ability of the PCA. Finally, comparative experiments between the PCA, standard genetic algorithm and particle swarm optimization were performed. The results showed that PCA has the best global convergence, smallest cycle indexes, and strongest stability when solving high-dimensional, multi-peak and complicated problems.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.33 no.s01
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• pp.64-85
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• 1988

Peanut seeds are characterized by high oils and proteins with good quality, and are utilized as an edible oil source and a protein-rich food products. The end products, being peanut butter, salted seed, confections, roasting stock and other by-products are favored in world-wide because of their unique roasted peanut flavor. As with many other foods, interest in the composition and chemistry of peanut is largely a result of thier use as human food. Thus, a more complete knowledge of thier chemical and food quality and flavor properties is desired. Literatures are reviewed mainly focucing on the physicochemical properties and nutritional quality of oil, protein and flavor in peanuts. Chemical properties of protein and oil, and volatile flavor component in peanut seeds are studied extensively in view point of chemical and food nutritional value. But in crop base, the synthesis and genetic studies of the chemicals could not provide valuable informations on the breeding for quality improvement. Some essential amino acids are limiting in peanut seeds and the tocopherols are very important in oil stability and for dietary adequacy ratio in high linoleic acid peanut oil, but it is thought to be quite difficult to improve by breeding technique as their lack information of gene actions. However, the selections of high protein and oil, and some essential amino acids and linoleic acid rich genotypes could be helpful for the quality improving. Research studies are also needed to elucidate the relationships between flavor components and consumer perception of peanut flavor.

• Journal of Forest and Environmental Science
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• v.26 no.2
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• pp.65-73
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• 2010

Biodiversity, referring to the variety and abundance of species, their genetic composition, and the communities, ecosystem, and landscapes, is essential to maintain healthy and productive forests, and to provide useful hedge against the future uncertainties in conditions of the environment and natural resources. To realize the long-term sustainability for forest production of goods and services is dependent upon maintaining and enhancing the biodiversity in the forest ecosystem. Because we can not always recognized which portion of biodiversity is essential to maintain the stability and sustainability of the natural system, conserving biodiversity is even unconditionally important. Even though the activities of forest resource management may have a variety of negative impacts on biodiversity by modification of the natural ecosystem into economically effective artificial ecosystem, forest professionals have been developing intelligent scheme to coexist management and conservation. However, conservation of biodiversity must be a complex problem encircled by ecological, economical, and social considerations. There seems to be no such a simple and easy solution. Strategies for ecologically deliberated forest resource management, which could play an important role to conserve biodiversity, were discussed.

• Journal of Korea Artificial Intelligence Association
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• v.2 no.1
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• pp.7-14
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• 2024

In this paper, we explore the application of RNA-sequencing data and ensemble machine learning to predict lung cancer and treatment strategies for lung cancer, a leading cause of cancer mortality worldwide. The research utilizes Random Forest, XGBoost, and LightGBM models to analyze gene expression profiles from extensive datasets, aiming to enhance predictive accuracy for lung cancer prognosis. The methodology focuses on preprocessing RNA-seq data to standardize expression levels across samples and applying ensemble algorithms to maximize prediction stability and reduce model overfitting. Key findings indicate that ensemble models, especially XGBoost, substantially outperform traditional predictive models. Significant genetic markers such as ADGRF5 is identified as crucial for predicting lung cancer outcomes. In conclusion, ensemble learning using RNA-seq data proves highly effective in predicting lung cancer, suggesting a potential shift towards more precise and personalized treatment approaches. The results advocate for further integration of molecular and clinical data to refine diagnostic models and improve clinical outcomes, underscoring the critical role of advanced molecular diagnostics in enhancing patient survival rates and quality of life. This study lays the groundwork for future research in the application of RNA-sequencing data and ensemble machine learning techniques in clinical settings.

• Horticultural Science & Technology
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• v.31 no.6
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• pp.772-781
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• 2013

The objective of this study was to develop simple sequence repeat (SSR) markers from expressed sequence tags (EST) of lettuce (Lactuca sativa) and identify 9 germplasms from 3 wild species of lettuce and 61 commercial cultivars using the developed EST-SSR markers. A total of 81,330 lettuce ESTs from NCBI databases were used to search for SSR and 4,229 SSR loci were identified. The highest proportion (59.12%, 2500) was represented by trinucleotide, followed by dinucleotide (29.70%, 1256) and hexanucleotide (6.62%, 280) among SSR repeat motifs. Totally 474 EST-SSR primers were developed from EST and a random set of 267 primers was used to assess the genetic diversity among 9 germplasms and 61 cultivars. Out of 267 primers, 47 EST-SSR markers showed polymorphism between 7 cultivars. Twenty-six EST-SSR markers among 47 EST-SSR markers showed high polymorphism, reproducibility, and band clearance. The relationship between 26 markers genotypes and 70 accessions was analyzed. Totally 127 polymorphic amplified fragments were obtained by 26 EST-SSR markers and two to nine SSR alleles were detected for each locus with an average of 4.88 alleles per locus. Average polymorphism information content was 0.542, ranging from 0.269 to 0.768. Genetic distance of clusters ranged from 0.05 to 0.94 between 70 accessions and dendrogram at a similarity of 0.34 gave 7 main clusters. Analysis of genetic diversity revealed by these 26 EST-SSR markers showed that the 9 germplasms and 61 commercial cultivars were discriminated by marker genotypes. These newly developed EST-SSR markers will be useful for cultivar identification and distinctness, uniformity and stability test of lettuce.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.19
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• pp.8051-8055
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• 2014

Background: A common genetic variant rs3757318, located in intron of C6orf97, was firstly identified to be associated with breast cancer (BC) risk by a genome-wide association (GWA) study. However, subsequent validation studies with different ethnicities have yielded conflicting results. Materials and Methods: We performed a meta-analysis to synthesize all available data for evaluating the precise effect of this variant on BC susceptibility. Results: A total of 8 articles containing 11 studies with 62,891 cases and 65,635 controls were included in this meta-analysis. When compared to the G allele, the rs3757318-A allele was significantly associated with BC risk with the pooled OR of 1.21 (95% CI=1.15 - 1.29, P<0.001) but with obvious between-study heterogeneity (P=0.040). Stratified analysis suggested that diversity of ethnicity along with control source may explain part of the heterogeneity. Similarly, significant associations were also identified in heterozygote, homozygote, dominant and recessive genetic models. Sensitivity and publication bias analyses indicated robust stability of our results. Conclusions: Our present meta-analysis demonstrated that the variant rs3757318 is associated with increased BC risk. Nevertheless, further studies are needed to clarify the underlying biological mechanisms.

• Korean journal of applied entomology
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• v.22 no.2 s.55
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• pp.52-66
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• 1983

The brown planthopper, N. lugens (Stal), has become a serious pest of rice in tropical Asia during the last decade. At high pest density, its feeding damage causes 'hopperburn' or complete wilting and drying of the rice plant. It also transmits grassy and ragged stunt virus diseases. The estimated losses caused by the pest in tropical Asia exceed $US\$300$ millions. While cultivation of resistant rice varieties has proved to be highly effective against the pest, their long-term stability is threatened because of the evolution of prolific biotypes which can destroy these varieties. At present, identification of biotypes is based principally on the differential reactions of host rice varieties to the pest and on host-mediated behavioral and physiological responses of the pest. Recent findings of morphological differences in adult rostrum, legs, and antennae, body parts that possess receptors for host plant location and discrimination, and cytological differences in N. lugens populations maintained as stock cultures strongly complement other biotype studies. So far, three N. lugens biotypes have been identified in the Philippines. Biotype I can survive on and damage varieties that do not carry and genes for resistance, while Biotype 2 survives on resistant varieties carrying Bph 1 gene and Biotype 3 on varieties carrying gene bph 2. However, none of these biotypes can survive on varieties with genes Bph 3 or bph 4. Several varieties which are resistant in the Philippines are susceptible in India and Sri Lanka as the South Asian biotypes of N. lugens are more virulent than Southeast Asian biotypes. To monitor the pest biotypes in different geographical regions and to identify new sources of resistance, an International Brown Planthopper Nursery has been established in many cooperating countries. The evolution of biotypes is an exceedingly complex process which is governed by the interactions of genetic and biological factors of the pest populations and the genetic makeup of the cultivated varieties. While the strategy for sequential release of varieties with major resistance genes has been fairly successful so far, the monegenic resistance of these varieties makes them vulnerable to the development of the pest biotypes. Therefore, present breeding endeavors envisage utilizing both major and minor resistance genes for effective control of the pest.