• Journal of the Korea Society of Computer and Information
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• v.10 no.5 s.37
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• pp.1-10
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• 2005

Multiple sequence alignment(MSA) is a fundamental technique of DNA and Protein sequence analysis. Biological sequences are aligned vertically in order to show the similarities and differences among them. In this Paper, we Propose an effcient group alignment method, which is based on clustering divergency, to Perform the alignment between two groups of sequences. The Proposed algorithm is a clustering divergence(CDMS)-based multiple sequence alignment and a top-down approach. The algorithm builds the tree topology for merging. It is so based on the concept that two sequences having the longest distance should be spilt into two clusters. We expect that our sequence alignment algorithm improves its qualify and speeds up better than traditional algorithm Clustal-W.

• The Journal of the Convergence on Culture Technology
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• v.5 no.3
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• pp.339-344
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• 2019

Global sequence alignment in search of similarity or homology favors larger size of the sequence because it keeps looking for more similar section between two sequences in the hope that it adds up scores for matched part in the rest of the sequence. If a substantial size of mismatched section exists in the middle of the sequence, it greatly reduces the total alignment score. In this case a whole sequence would be better to be divided into multiple sections. Overall alignment score over the multiple sections of the sequence would increase as compared to global alignment. This method is called multiple local alignment. In this paper, we implement a multiple local alignment algorithm, an extension of Smith-Waterman algorithm and show the experimental results for the algorithm that is able to search for sub-optimal sequence.

• Journal of KIISE:Software and Applications
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• v.30 no.9
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• pp.803-811
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• 2003

Multiple sequence alignment is a useful tool to identify the relationships among protein sequences. Dynamic programming is the most widely used algorithm to obtain multiple sequence alignment with optimal cost. However, dynamic programming cannot be applied to certain cost function due to its drawback and cannot be used to produce optimal multiple sequence alignment. We propose sub-alignment refinement algorithm to overcome the problem of dynamic programming. Also we show proposed algorithm can solve the problem of dynamic programming efficiently.

• Korean Journal of Microbiology
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• v.35 no.2
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• pp.115-120
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• 1999

Multiple Sequence Alignment of DNA and protem sequences is a imnport'mt tool in the study of molecular evolution, gene regulation. and prolein suucture-function relationships. Progressive pairwise alignment method generates multiple sequence alignment fast but not necessarily with optimal costs. Dynamic programming generates multiple sequence alig~~menl with optimal costs in most cases but long execution time. In this paper. we suggest genetlc algorithm lo improve the multiple sequence alignment generated from the cnlent methods, describe the design of the genetic algorithm, and compare the multiple sequence alignments from 0111 method and current methods.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.2
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• pp.467-472
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• 2024

Multiple sequence alignment (MSA) is a method of collecting and aligning multiple protein sequences or nucleic acid sequences that perform the same function in various organisms at once. clustalW, a representative multiple sequence alignment algorithm using BioPython, compares the degree of alignment by column position. In addition, a web logo and phylogenetic tree are created to visualize conserved sequences in order to improve understanding. An example was given to confirm the differences between humans and other species, and applications of BioPython are presented.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.5
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• pp.205-215
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• 2006

In this paper an optical power meter using Hadamard transform, which can be used in multiple channel optical elements alignment system, is proposed. A traditional optical power meter in multiple channel optical elements alignment system is able to judge how well the elements are aligned each other by measuring optical power of the first and the last two channels with at least two detectors. It has critical drawback that the alignment accuracy per channel is dependent on the number of detectors. The proposed optical power meter can get noise reduction by the Hadamard transform based multiplexing technique. The Hadamard transform based multiplexing technique using spatial light modulators is distinguished by the best enhancement of signal-to-noise ratio (SNR) for the reconstructed signals. Moreover, the noise reduction increases with increasing the order of multiplexing, namely the number of optical element channels. The proposed system is implemented by PDLC (Polymer Dispersed Liquid Crystal) mask which is operated by electric filed and generates optimal multiplexing patterns based on the Hadamard transform and single detector. It means that we obtain not only the each channel's optical power of multiple channel elements at once but also the best enhancement of SNR with single detector. Experimental results show that the proposed optical power meter is suitable for an active optical alignment system for multiple channel optical elements.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.264-267
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• 2003

Multiple sequence alignment is a useful tool to identify the relationships among protein sequences. Dynamic programming is the most widely used algorithm to obtain multiple sequence alignment with optimal cost. However dynamic programming cannot be applied to certain cost function due its drawback and to produce optimal multiple sequence alignment. We proposed sub-alignment refinement algorithm to overcome the problem of dynamic programming and impelmented this algorithm as a module of our MS Windows-based sequence alignment program.

• Current Optics and Photonics
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• v.8 no.1
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• pp.72-79
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• 2024

Recent flat-panel displays have become increasingly complicated to facilitate multiple display functions. In particular, the form of multilayered architectures for next-generation displays makes precise three-dimensional alignment of multiple panels a challenge. In this paper, a diffractive optical alignment marker is proposed to address the problem of three-dimensional alignment of distant dual panels beyond the depth-of-focus of a vision camera. The diffractive marker is effective to analyze the positional correlation of distant dual panels. The possibility of diffractive alignment in multilayer display fabrication is testified with numerical simulation and a proof-of-concept experiment.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.10
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• pp.1044-1049
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• 2006

Multiple sequence alignment is a method to compare two or more DNA or protein sequences. Most of multiple sequence alignment tools rely on pairwise alignment and Smith-Waterman algorithm to generate an alignment hierarchy. Therefore, in the existing multiple alignment method as the number of sequences increases, the runtime increases exponentially. In order to remedy this problem, we adopted a parallel processing suffix tree algorithm that is able to search for common subsequences at one time without pairwise alignment. Also, the cross-matching subsequences triggering inexact-matching among the searched common subsequences might be produced. So, the cross-matching masking process was suggested in this paper. To identify the function of the clusters generated by suffix tree clustering, BLAST and CDD (Conserved Domain Database)search were combined with a clustering tool. Our clustering and annotating tool consists of constructing suffix tree, overlapping common subsequences, clustering gene sequences and annotating gene clusters by BLAST and CDD search. The system was successfully evaluated with 36 gene sequences in the pentose phosphate pathway, clustering 10 clusters, finding out representative common subsequences, and finally identifying functional domains by searching CDD database.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.2859-2872
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• 2019

Interference alignment (IA) has been a powerful approach to achieve the maximum degree of freedom (DoF) for K users multiple-input-multiple-output (MIMO) interference channels. However, due to the feasibility constraint, aligning all the interference signals at each receiver is impractical for large K without symbol extension. In this paper, we propose two best-effort interference alignment (BEIA) schemes that the network selects the maximum number of interfering transmitters to align their signals given the feasibility conditions when each transmitter-receiver pair has a constant number of data streams. Besides, in case of not all interfering signals aligned at each receiver, an upper bound of the average throughput is derived. Simulation results show that the proposed schemes have superiority over the traditional methods, such as time division multiple access (TDMA) and cluster IA(CIA), in low and moderate signal-to-noise ratio (SNR) region in terms of average user throughput. In addition, the proposed max-min relative interference distance alignment scheme outperforms the proposed scheme of equal interfering transmitters number alignment in terms of both average user throughput and minimum user throughput.