• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.555-559
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• 1998

The human chromosome analysis is widely used to diagnose genetic disease and various congenital anomalies. Many researches on automated chromosome karyotype analysis have been carried out, some of which produced commercial systems. However, there still remains much room for improving the accuracy of chromosome classification. In this paper, We proposed an optimal pattern classifier by neural network to improve the accuracy of chromosome classification. The proposed pattern classifier was built up of two-step multi-layer neural network(TMANN). We reconstructed chromosome image to improve the chromosome classification accuracy and extracted four morphological features parameters such as centromeric index (C.I.), relative length ratio(R.L.), relative area ratio(R.A.) and chromosome length(C.L.). These Parameters employed as input in neural network by preprocessing twenty human chromosome images. The experiment results shown that the chromosome classification error was reduced much more than that of the other classification methods.

• Animal cells and systems
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• v.16 no.6
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• pp.438-446
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• 2012

In 1964, Susumu Ohno, an evolutionary biologist, hypothesized that the size of X chromosome was conserved in mammalian evolution, and that this was based on chromosomal length. Today, unlike Ohno's method which was based on estimated lengths, we know the exact lengths of some mammalian sequences. The aim of this study was to reanalyze Ohno's hypothesis. In mammalian species, variation in the length of the X chromosome is greater than in the autosomes; however, this variation is not statistically significant. This means that differences in chromosomal length occur equally in the X chromosome and in the autosomes. Interspersed nuclear elements and genetic rearrangements were analyzed to maintain the same variance between the length of the X chromosome and the autosomes. The X chromosome contained fewer short interspersed elements (SINEs) (0.90 on average); however, it did contain more long interspersed elements (LINEs) than did autosomes (1.56 on average). An overall correlation of LINEs and SINEs with genetic rearrangements was observed; however, synteny breaks were more closely associated with LINEs in the autosomes, and with SINEs in the X chromosome. These results suggest that the chromosome-specific activities of LINEs and SINEs result in the same variance between the lengths of the X chromosome and the autosomes. This is based on the function of interspersed nuclear elements, such as LINEs, which can inactivate the X chromosome and the reliance of non-autonomous SINEs on LINEs for transposition.

• The Korean Journal of Zoology
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• v.31 no.2
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• pp.104-110
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• 1988

The comparative karyological analysis of the Korean treefrog, Hyla japonica and Hyla suweonensis performed by conventional giemsa-staining and NOR-staining method. The karyotypes of both species were the same (2n=24). However, according to the Karyological analysis, the 6th chromosomes of the two species distinctly different. Eventhough the 6th chromosomes of the two species shown the same % length, construction of the 6th chromosome of H.japonica was subtelocentric chromosome while H. suweonensis was submetacentric chromosome. This phenomena could explain that the morphological differences in the 6th chromosomes might be caused by pericentric inversion. The two species have 1 pair of NOR site in the 6th chromosome.

• Korean Journal of Poultry Science
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• v.13 no.2
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• pp.167-172
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• 1986

Chromosome size, number and shape were studied by the centromeric index, the arm ratio and the relative length of chromosome. The chromosomes of 50 early chick embryos which were derived from a pure line of Single Comb White Leghorns were examined. Using a colchicine, hypotonic treatment, fixation and air-drying technique, the clear prometaphase figures were obtained from the whole embryo. The results of the present investigation of chromosome pairs were as follows, 1. Pair 1 and 2; metacentric and submetacentric chromosomes which could be clearly distinguished from each other by size. 2. Pair 3 and 4: acrocentric chromosomes of similar length but the 4th pair had a distinct short arm which was not present in the 3rd. 3, Pair 5; metacentric sex chromosomes, 2 chromosome had relative 5th length but the W chromosome had slightly shorter length than 7th pair of chromosomes. 4. Pair 6; acrocentric chromosomes similar in shape to pair 3 but of little more than half the size. 5, Pair 7 and 8; acrocentric chrocentric but the 7th pairs had a definite short arm. 6. Pair 9; similar length to the 7, 8 pairs but had a medially placed centromere. 7. microchromosomes of 30 pairs ; nearly all acrocentric chromosomes which appeared as paired dots. The total number of diploid was appeared to 72-78. But a number of observations presented the total diploid number in 78 (58%). The inconstancy in number observed in this study was presumably due to the minute size of the microchromosomes. Thus, the modal numbers for the diploid chromosome was at least 78.

• Journal of Biomedical Engineering Research
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• v.18 no.3
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• pp.233-241
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• 1997

The research on chromosomes is very significant in cytogenetics since genes of the chromosomes control revelation of the inheritance plasma. The human chromosome analysis is widely used to study leukemia, malignancy, radiation hazard, and mutagen dosimetry as well as various congenital anomalies such as Down's, Klinefelter's, Edward's, and Patau's syndrome. The framing and analysis of the chromosome karyogram, which requires specific cytogenetic knowledge is most important in this field. Many researches on automated chromosome karyotype analysis methods have been carried out, some of which produced commercial systems. However, there still remains much room to improve the accuracy of chromosome classification and to reduce the processing time in real clinic environments. In this paper, we proposed a hierarchical artificial neural network(HANN) to classify the chromosome karyotype. We extracted three or four chromosome morphological feature parameters such as centromeric index, relative length ratio, relative area ratio, and chromosome length by preprocessing from ten human chromosome images. The feature parameters of five human chromosome images were used to learn HANN and the rest of them were used to classify the chromosome images. The experiment results show that the chromosome classification error is reduced much more than that of the other researchers using less feature parameters.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.279-279
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• 2022

Rice is 34% of the world's population used as a staple food. But the world population is increasing. Food security is not well protected. Improving cultivar development can address food security. Quantitative trait locus (QTL) mapping is a statistical analysis using both phenotypic and genotypic dates. The purpose of QTL mapping is to determine a gene. Increasing grain size is a way to increase yield in rice. Grain size-related genes were mapped using CNDH population obtained by cross-breeding Cheongcheong (Indica) and Nagdong (Japonica) through anther culture. Grain harvested from experimental field of Kyungpook National University in Gunwi in 2021. Genes related to grain length were detected between RM5964-RM12285, RM20924-RM20967 in chromosome 1, 7. LOD score is 5.88 and 5.6. Genes related to grain width was detected between RM289-RM18130 in chromosome 5. LOD score is 4.57. Genes related to grain length/width ratio were detected between RM5459-RM3482, RM5699-RM1211 and RM3838-RM3381 in chromosome 1, 2, 5. LOD score is 3.75, 3.14 and 3.41. 4 genes was detected in chromosome 1 and 2 genes was detected in chromosome 2 and 7 genes was detected in chromosome 5. 2 genes related to grain shape and quality were detected. 4 genes related to grain length were detected. 4 genes related to grain size were detected. 1 gene related to grain size and weight was detected. 2 genes related to grain length and weight were detected. By finding the gene related to grain size, it provides food to people threatened by food security and solves the food shortage.

• Journal of Biomedical Engineering Research
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• v.17 no.4
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• pp.545-552
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• 1996

Researches on chromosome are very significant in cytogenetics since a gene of the chromosome controls revelation of the inheritance plasma The human chromosome analysis is widely used to diagnose genetic disease and various congenital anomalies. Many researches on automated chromosome karyotype analysis has been carried out, some of which produced commercial systems. However, there still remains much room for improving the accuracy of chromosome classification. In this paper, we propose an algorithm for reconstruction of the chromosDme image to improve the chromosome classification accuracy. Morphological feature parameters are extracted from the reconstructed chromosome images. The reconstruction method from chromosome image is the 32 direction line algorithm. We extract three morphological feature parameters, centromeric index(C.I.), relative length ratio(R.L.), and relative area ratio(R.A.), by preprocessing ten human chromosDme images. The experimental results show that proposed algorithm is better than that of other researchers'comparing by feature parameter errors.

• Animal Bioscience
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• v.36 no.2
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• pp.191-199
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• 2023

Objective: This study aimed to investigate the significant single nucleotide polymorphisms (SNPs) and genes associated with nine reproduction and morphological traits in three breed populations of Chinese goats. Methods: The genome-wide association of nine reproduction and morphological traits (litter size, nipple number, wattle, skin color, coat color, black dorsal line, beard, beard length, and hind leg hair) were analyzed in three Chinese native goat breeds (n = 336) using an Illumina Goat SNP50 Beadchip. Results: A total of 17 genome-wide or chromosome-wide significant SNPs associated with one reproduction trait (litter size) and six morphological traits (wattle, coat color, black dorsal line, beard, beard length, and hind leg hair) were identified in three Chinese native goat breeds, and the candidate genes were annotated. The significant SNPs and corresponding putative candidate genes for each trait are as follows: two SNPs located on chromosomes 6 (CSN3) and 24 (TCF4) for litter size trait; two SNPs located on chromosome 9 (KATNA1) and 1 (UBASH3A) for wattle trait; three SNPs located on chromosome 26 (SORCS3), 24 (DYM), and 20 (PDE4D) for coat color trait; two SNPs located on chromosome 18 (TCF25) and 15 (CLMP) for black dorsal line trait; four SNPs located on chromosome 8, 2 (PAX3), 5 (PIK3C2G), and 28 (PLA2G12B and OIT3) for beard trait; one SNP located on chromosome 18 (KCNG4) for beard length trait; three SNPs located on chromosome 17 (GLRB and GRIA2), 28 (PGBD5), and 4 for hind leg hair trait. In contrast, there were no SNPs identified for nipple number and skin color. Conclusion: The significant SNPs or genes identified in this study provided novel insights into the genetic mechanism underlying important reproduction and morphological traits of three local goat breeds in Southern China as well as further potential applications for breeding goats.

• Korean Journal of Medicinal Crop Science
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• v.10 no.2
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• pp.144-146
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• 2002

Cytogenetic analysis of Anemarrhena ashodeloides BUNGE, which is one of medicinal plants belonging to Haemodoraceae was carried out using Feulgen staining. The somatic metaphase chromosome number was identified to 2n=22 (x=11) and the size of chromosomes ranges from $1.27-3.80\;{\mu}m$. Three pairs of chromosomes were relatively long in total length and the others were short. The karyotype was bimodal in chromosome length and arm ratios. The chromosome complement comprise eight pairs of metacentric (chromosome 2, 3, 6, 7, 8, 9, 10, and 11), two pairs of submetacentric (chromosome 4 and 5), and one pair of subtelocentric (chromosome 1).

• Proceedings of the KOSOMBE Conference
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• v.1995 no.11
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• pp.197-200
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• 1995

In this paper, we proposed the multi-step multi-layer artificial neural network(MMANN) to classify the chromosome, Which is used as a chromosome pattern classifier after learning. We extracted three chromosome morphological feature parameters such as centromeric index, relative length ratio, and relative area ratio by means of preprocessing method from ten chromosome images. The feature parameters of five chromosome images were used to learn neural network and the rest of them were used to classify the chromosome images. The experiment results show that the chromosome classification error is reduced much more, comparing with less feature parameters than that of the other researchers.