• International Journal of Computer Science & Network Security
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• v.21 no.12spc
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• pp.526-538
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• 2021

Machine and deep learning-based models are emerging techniques that are being used to address prediction problems in biomedical data analysis. DNA sequence prediction is a critical problem that has attracted a great deal of attention in the biomedical domain. Machine and deep learning-based models have been shown to provide more accurate results when compared to conventional regression-based models. The prediction of the gene sequence that leads to cancerous diseases, such as prostate cancer, is crucial. Identifying the most important features in a gene sequence is a challenging task. Extracting the components of the gene sequence that can provide an insight into the types of mutation in the gene is of great importance as it will lead to effective drug design and the promotion of the new concept of personalised medicine. In this work, we extracted the exons in the prostate gene sequences that were used in the experiment. We built a Deep Neural Network (DNN) and Bi-directional Long-Short Term Memory (Bi-LSTM) model using a k-mer encoding for the DNA sequence and one-hot encoding for the class label. The models were evaluated using different classification metrics. Our experimental results show that DNN model prediction offers a training accuracy of 99 percent and validation accuracy of 96 percent. The bi-LSTM model also has a training accuracy of 95 percent and validation accuracy of 91 percent.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1998.10a
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• pp.223-223
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• 1998

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.12C
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• pp.1142-1148
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• 2007

In this paper, we propose ASLM (Adaptive Selective Mapping; ASLM) scheme based on peak observation for PAPR (Peak-to-Average Power Ratio) reduction of OFDM (Orthogonal Frequency Division Multiplexing) signals. The proposed scheme is composed of three steps: peak scaling, sequence selection, and SLM procedures. In the first step, the peak signal samples in the IFFT (Inverse Fast Fourier Transform) outputs of the original input sequence are scaled down. In the second step, the sub-carrier positions where the power difference between the original input sequence and the FFT output of the scaled signal is large, are identified. Then, the phase sequences having the maximum number of phase-reversed sequence words only for these positions are selected. Finally, the generic SLM procedure is performed by using only the selected phase sequences for the original input sequence. Simulation results show that the proposed scheme significantly reduces the complexity in terms of IFFT and PAPR calculation than the conventional SLM, while maintaining the PAPR reduction performance.

• International Journal of Control, Automation, and Systems
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• v.6 no.6
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• pp.904-914
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• 2008

An action-selection-mechanism(ASM) has been proposed to work as a fully connected finite state machine to deal with sequential behaviors as well as to allow a state in the task program to migrate to any state in the task, in which a primitive node in association with a state and its transitional conditions can be easily inserted/deleted. Also, such a primitive node can be learned by a shortest path-finding-based reinforcement learning technique. Specifically, we define a behavioral motivation as having state-dependent value as a primitive node for action selection, and then sequentially construct a network of behavioral motivations in such a way that the value of a parent node is allowed to flow into a child node by a releasing mechanism. A vertical path in a network represents a behavioral sequence. Here, such a tree for our proposed ASM can be newly generated and/or updated whenever a new behavior sequence is learned. To show the validity of our proposed ASM, experimental results of a mobile robot performing the task of pushing- a- box-in to- a-goal(PBIG) will be illustrated.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.5
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• pp.551-556
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• 2004

According to revealing the DNA sequence of human and living things, it increases that a demand on a new computational processing method which utilizes DNA sequence information. In this paper we propose a classification algorithm based on negative selection of the immune system to classify DNA patterns. Negative selection is the process to determine an antigenic receptor that recognize antigens, nonself cells. The immune cells use this antigen receptor to judge whether a self or not. If one composes n group of antigenic receptor for n different patterns, they can classify into n patterns. In this paper we propose a pattern classification algorithm based on negative selection in nucleotide base level and amino acid level.

• Journal of Crop Science and Biotechnology
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• v.11 no.4
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• pp.263-268
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• 2008

Bacterial leaf pustule (BLP) caused by Xanthomonas axonopodis pv. glycines is a serious disease to make pustule and chlorotic haloes in soybean [Glycine max (L). Merr.]. While inheritance mode and map positions of the BLP resistance gene, rxp are known, no sequence information of the gene was reported. In this study, we made five near isogenic lines (NILs) from separate backcrosses (BCs) of BLP-susceptible Hwangkeumkong $\times$ BLP-resistant SS2-2 (HS) and BLP-susceptible Taekwangkong$\times$ SS2-2 (TS) through foreground and background selection based on the four-stage selection strategy. First, 15 BC individuals were selected through foreground selection using the simple sequence repeat (SSR) markers Satt486 and Satt372 flanking the rxp gene. Among them, 11 BC plants showed the BLP-resistant response. The HS and TS lines chosen in foreground selection were again screened by background selection using 118 and 90 SSR markers across all chromosomes, respectively. Eventually, five individuals showing greater than 90% recurrent parent genome content were selected in both HS and TS lines. These NILs will be a unique biological material to characterize the rxp gene.

• Management Science and Financial Engineering
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• v.1 no.1
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• pp.67-90
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• 1995

In planning an assembly system, choosing the proper assembly sequence is one of the most important decisions because it significantly affects the costs associated with the assembly process. This paper deals with the selection of assembly sequences in flexible assembly systems. The selection criterion is the minimization of makespan to complete all assembly products. This problem is formulated as a "modified FAS scheduling problem" (MFASSP) and its scheduling procedure is described. The experimental results show that the procedure is very efficient for both quality of solution and computation time.

• Journal of the Korea Safety Management & Science
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• v.5 no.1
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• pp.69-82
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• 2003

The sequence which minimizes overall utility work in car assembly lines reduces the cycle time, the number of utility workers, and the risk of conveyor stopping. This study suggests mathematical formulation of the sequencing problem to minimize overall utility work, and present a genetic algorithm which can provide a near optimal solution in real time. To apply a genetic algorithm to the sequencing problem in car assembly lines, the representation, selection methods, and genetic parameters are studied. Experiments are carried out to compare selection methods such as roullette wheel selection, tournament selection and ranking selection. Experimental results show that ranking selection method outperforms the others in solution quality, whereas tournament selection provides the best performance in computation time.

• Molecules and Cells
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• v.25 no.1
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• pp.20-29
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• 2008

Cytoplasmic male sterility (CMS), one of the most important traits in crop breeding, has been used for commercial seed production by $F_1$ hybrid cultivars of pepper (Capsicum annuum L.). To develop reliable molecular markers for allelic selection of the Restorer-of-fertility (Rf) gene, which is known to be a major determinant of pollen fertility restoration in peppers, a sequence of approximately 10 kb flanking an RAPD fragment closely linked to the Rf locus was obtained by genome walking. A homology search revealed that this sequence contained an LTR retrotransposon and a non-LTR LINE-like retrotransposon. Sequencing of this Rf-linked region to search for polymorphisms between a dominant and recessive allele revealed 98% nucleotide sequence identity between them. A third polymorphic haplotype of the Rf-linked sequence, which has 94-96% nucleotide sequence identity with the two previously isolated haplotypes, was identified among a large number of breeding lines. Utilizing polymorphic sequences in the haplotypes, PCR markers were developed for selection of particular haplotypes and used to examine the distribution of the haplotypes in diverse breeding lines, cultivars, and C. annuum germplasms. Surprisingly, the third haplotype was the predominant type in C. annuum germplasms, while its frequency in $F_1$ hybrid cultivars was relatively low. Meanwhile, analysis of breeding lines whose Rf allele genotypes and male-sterility phenotypes were already known revealed that the third haplotype was mainly present in exotic breeding lines that cause unstable male-sterility when combined with sterile cytoplasms.

• Journal of Microbiology and Biotechnology
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• v.30 no.10
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• pp.1583-1591
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• 2020

CRISPR/Cpf1 has emerged as a new CRISPR-based genome editing tool because, in comparison with CRIPSR/Cas9, it has a different T-rich PAM sequence to expand the target DNA sequence. Single-base editing in the microbial genome can be facilitated by oligonucleotide-directed mutagenesis (ODM) followed by negative selection with the CRISPR/Cpf1 system. However, single point mutations aided by Cpf1 negative selection have been rarely reported in Corynebacterium glutamicum. This study aimed to introduce an amber stop codon in crtEb encoding lycopene hydratase, through ODM and Cpf1-mediated negative selection; deficiency of this enzyme causes pink coloration due to lycopene accumulation in C. glutamicum. Consequently, on using double-, triple-, and quadruple-base-mutagenic oligonucleotides, 91.5-95.3% pink cells were obtained among the total live C. glutamicum cells. However, among the negatively selected live cells, 0.6% pink cells were obtained using single-base-mutagenic oligonucleotides, indicating that very few single-base mutations were introduced, possibly owing to mismatch tolerance. This led to the consideration of various target-mismatched crRNAs to prevent the death of single-base-edited cells. Consequently, we obtained 99.7% pink colonies after CRISPR/Cpf1-mediated negative selection using an appropriate single-mismatched crRNA. Furthermore, Sanger sequencing revealed that single-base mutations were successfully edited in the 99.7% of pink cells, while only two of nine among 0.6% of pink cells were correctly edited. The results indicate that the target-mismatched Cpf1 negative selection can assist in efficient and accurate single-base genome editing methods in C. glutamicum.