• Korean Chemical Engineering Research
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• v.62 no.3
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• pp.274-280
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• 2024

Machine learning techniques utilizing neural networks have been employed in various fields such as disease gene discovery and diagnosis, drug development, and prediction of drug-induced liver injury. Disease features can be investigated by molecular information of DNA. In this study, we developed a neural network to predict the length of DNA and the number of DNA species in mixture solution which are representative molecular information of DNA. In order to address the time-consuming limitations of gel electrophoresis as conventional analysis, we analyzed the dynamic data of a microfluidic concentrating device. The dynamic data were reconstructed into a spatiotemporal map, which reduced the computational cost required for training and prediction. We employed a convolutional neural network to enhance the accuracy to analyze the spatiotemporal map. As a result, we successfully performed single DNA length prediction as single-variable regression, simultaneous prediction of multiple DNA lengths as multivariable regression, and prediction of the number of DNA species in mixture as binary classification. Additionally, based on the composition of training data, we proposed a solution to resolve the problem of prediction bias. By utilizing this study, it would be effectively performed that medical diagnosis using optical measurement such as liquid biopsy of cell-free DNA, cancer diagnosis, etc.

• Journal of Plant Biotechnology
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• v.33 no.4
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• pp.309-313
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• 2006

Discovery of single nucleotide polymorphisms (SNPs), including small insertions and deletions, is one of the hot topics in genetic research. The most common type of sequence variant consists of single base differences or small insertions and deletions at specific nucleotide positions. Significance of SNPs in rice is increasing for genetic research, positional cloning and molecular breeding. $F_2$ 170 lines and $F_3$ 194 lines derived from Sangjuchalbyeo/HR13721-53-3-1-3-3-2-2 Were used for Searching SNP markers related to bacterial blight resistance. Sangjuchalbyeo is susceptible to bacterial blight, but HR13721-53-3-1-3-3-2-2 has Xa1 gene resistant to bacterial blight. Individual lines were inoculated with $K_1$ race of bacterial blight and resistant or susceptible was evaluated after 3 weeks from inoculation. The genotypes of population were analysed by PCR-RFLP for SNP marker developing. The segregation of $F_2\;and\;F_3$ population showed almost 3:1, 1:1 ratio, respectively. Analysis of genotype using SNP marker is capable of confirming resistance for $K_1$ race and genotype through amplifying the gene using 16PFXal primer and digested the PCR product with Eco RV. There were close relation between resistance test for $K_1$ race and SNP marker genotype. Especially, DNA analysis using SNP marker is capable of judging homozygote/heterozygote in $F_2$ population compared with resistant test for Kl race. So, it seems to improve the selection efficiency in disease resistant breeding.