1.A simple protocol of DNA sequencing with 10% formamide for dissolving G/C compression.
Kee Ryeon KANG ; Yeon Woong KIM
Experimental & Molecular Medicine 1997;29(4):235-237
Formamide has been widely used in urea/polyacrylamide gel to solve the compression problems that are occasionally found during the DNA sequencing of G/C rich regions. In this study, however, 10% formamide was added in annealing solution in stead of adding to the gel. The compressions were unfolded efficiently with a more rapid annealing reaction on ice in the presence of 10% formamide.
DNA*
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Ice
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Sequence Analysis, DNA*
2.DNA Sequence Analysis on Internet.
Korean Journal of Clinical Microbiology 2000;3(1):5-15
No abstract available.
Base Sequence*
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DNA*
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Internet*
;
Sequence Analysis, DNA*
3.A Pattern Summary System Using BLAST for Sequence Analysis.
Han Suk CHOI ; Dong Wook KIM ; Tae W RYU
Genomics & Informatics 2006;4(4):173-181
Pattern finding is one of the important tasks in a protein or DNA sequence analysis. Alignment is the widely used technique for finding patterns in sequence analysis. BLAST (Basic Local Alignment Search Tool) is one of the most popularly used tools in bio-informatics to explore available DNA or protein sequence databases. BLAST may generate a huge output for a large sequence data that contains various sequence patterns. However, BLAST does not provide a tool to summarize and analyze the patterns or matched alignments in the BLAST output file. BLAST lacks of general and robust parsing tools to extract the essential information out from its output. This paper presents a pattern summary system which is a powerful and comprehensive tool for discovering pattern structures in huge amount of sequence data in the BLAST. The pattern summary system can identify clusters of patterns, extract the cluster pattern sequences from the subject database of BLAST, and display the clusters graphically to show the distribution of clusters in the subject database.
Computational Biology
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Databases, Protein
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DNA
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Sequence Analysis*
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Sequence Analysis, DNA
4.DNA Chip.
Journal of Korean Society of Endocrinology 2000;15(4-5):463-467
No Abstract Available.
DNA*
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Oligonucleotide Array Sequence Analysis*
5.A Clustering Tool Using Particle Swarm Optimization for DNA Chip Data.
Genomics & Informatics 2011;9(2):89-91
DNA chips are becoming increasingly popular as a convenient way to perform vast amounts of experiments related to genes on a single chip. And the importance of analyzing the data that is provided by such DNA chips is becoming significant. A very important analysis on DNA chip data would be clustering genes to identify gene groups which have similar properties such as cancer. Clustering data for DNA chips usually deal with a large search space and has a very fuzzy characteristic. The Particle Swarm Optimization algorithm which was recently proposed is a very good candidate to solve such problems. In this paper, we propose a clustering mechanism that is based on the Particle Swarm Optimization algorithm. Our experiments show that the PSO-based clustering algorithm developed is efficient in terms of execution time for clustering DNA chip data, and thus be used to extract valuable information such as cancer related genes from DNA chip data with high cluster accuracy and in a timely manner.
Cluster Analysis
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DNA
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Oligonucleotide Array Sequence Analysis
6.Unusual mtDNA sequencing results from ancient DNA.
Seung Bum SEO ; Chong Min CHOUNG ; Aihua ZHANG ; Byoung Su JANG ; Seong Ho YOO ; Soong Deok LEE
Korean Journal of Legal Medicine 2007;31(1):36-40
Sequence analysis of human mitochondrial DNA(mtDNA) is being used widely to characterize individual identification, particularly when there is insufficient nuclear DNA in samples for typing. Hair shafts, bones, teeth and other samples that are severely decomposed may be subjected to mtDNA analysis. As sample decomposes, however, the possibility of mtDNA to be degraded becomes high and the possibility of spurious results becomes high. In this case mtDNA sequencing results must be carefully analyzed. We got unusual results while typing two human bone samples, which were not compatible with human mtDNA sequence. Bones were about 50 and 35 years old. We report the results with discussions about ancient DNA sequencing.
Adult
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DNA*
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DNA, Mitochondrial*
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Hair
;
Humans
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Sequence Analysis
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Sequence Analysis, DNA
;
Tooth
7.DNA Microarrays for Comparative Genomics: Identification of Conserved and Variable Sequences in Prokaryotic Genomes.
Genomics & Informatics 2004;2(1):53-56
No abstract available.
DNA*
;
Genome*
;
Genomics*
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Oligonucleotide Array Sequence Analysis*
8.Implementation of a Particle Swarm Optimization-based Classification Algorithm for Analyzing DNA Chip Data.
Genomics & Informatics 2011;9(3):134-135
DNA chips are used for experiments on genes and provide useful information that could be further analyzed. Using the data extracted from the DNA chips to find useful patterns or information has become a very important issue. In this paper, we explain the application developed for classifying DNA chip data using a classification method based on the Particle Swarm Optimization (PSO) algorithm. Considering that DNA chip data is extremely large and has a fuzzy characteristic, an algorithm that imitates the ecosystem such as the PSO algorithm is suitable to be used for analyzing such data. The application enables researchers to customize the PSO algorithm parameters and see detail results of the classification rules.
DNA
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Ecosystem
;
Oligonucleotide Array Sequence Analysis
9.Microbial Genome Analysis and Application to Clinical Bateriology.
Yeungnam University Journal of Medicine 2002;19(1):1-10
With the establishment of rapid sequence analysis of 16S rRNA and the recognition of its patential to determine the phylogenetic position of any prokaryotic organism, the role of 16S rRNA similarities in the present species definition in bacteriology need to be clarified. Comparative studies clearly reveal the limitations of the sequence analysis of this conserved gene and gene product in the determination of relationship at the pathogenic strain level for which DNA-DNA reassociation exprements still constitute the superior method. Since today the primary structure of 16S rRNA is easier to determine than hybridization between DNA strands, the strength of the sequence analysis is to recognize the level at which DNA pairing studies need to be performed, which certainly applies to similarities of 97% and higher.
Bacteriology
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DNA
;
Genome, Microbial*
;
Sequence Analysis
10.Microbial Genome Analysis and Application to Clinical Bateriology.
Yeungnam University Journal of Medicine 2002;19(1):1-10
With the establishment of rapid sequence analysis of 16S rRNA and the recognition of its patential to determine the phylogenetic position of any prokaryotic organism, the role of 16S rRNA similarities in the present species definition in bacteriology need to be clarified. Comparative studies clearly reveal the limitations of the sequence analysis of this conserved gene and gene product in the determination of relationship at the pathogenic strain level for which DNA-DNA reassociation exprements still constitute the superior method. Since today the primary structure of 16S rRNA is easier to determine than hybridization between DNA strands, the strength of the sequence analysis is to recognize the level at which DNA pairing studies need to be performed, which certainly applies to similarities of 97% and higher.
Bacteriology
;
DNA
;
Genome, Microbial*
;
Sequence Analysis