• The KIPS Transactions:PartA
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• v.16A no.3
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• pp.143-152
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• 2009

One of the main issues in comparative genomics is to study chromosomal gene order in one or more related species. For this purpose, the whole genome alignment is usually applied to find the horizontal gene transfer, gene duplication, and gene loss between two related genomes. Also it is well known that the novel visualization tool with whole genome alignment is greatly useful for us to understand genome organization and evolution process. There are a lot of algorithms and visualization tools already proposed to find the "gene clusters" on genome alignments. But due to the huge size of whole genome, the previous visualization tools are not convenient to discover the relationship between two genomes. In this paper, we propose AlignScope, a novel visualization system for whole genome alignment, especially useful to find gene clusters between two aligned genomes. This AlignScope not only provides the simplified structure of genome alignment at any simplified level, but also helps us to find gene clusters. In experiment, we show the performance of AlignScope with several microbial genomes such as B. subtilis, B.halodurans, E. coli K12, and M. tuberculosis H37Rv, which have more than 5000 alignment pairs (matched DNA subsequence).

• Proceedings of the Korean Society of Life Science Conference
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• 2003.10a
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• pp.14-27
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• 2003

The genomes of Arabidopsis and rice have been fully sequenced. Genomic sequencing provides global information about genome structure and organization. A comprehensive research account of our recent studies conducted on genome painting, comparative genomics and genome fusion is provided in order to project the prospects of plant cytogenetic research in post-genomics era. Genome analysis by GISH using genome painting is demonstrated as an excellent means suitable for visualization of a whole genome, since total genomic DNA representing the overall molecular composition of the genome is used as a probe. FISH on extended DNA fibers has been developed for high-resolution FISH and has contributed to determining the copy number and order of genes. We have also mapped a number of genes involving starch synthesis on wheat chromosomes by FISH and compared the position of these genes on linkage map of rice. Macro synteny between wheat and rice can be observed by comparing the location of these genes in spite of the fact that the size of DNA per chromosome differs by 20 fold in two. Moreover, to approach our goal towards making bread and udon noodles from rice flour in future by incorporating bread making and the noodle qualifies in rice, we have been successful in introducing large genomic DNA fragments containing agronomically important genes of wheat into a rice by successive introduction of large insert BAC clones, there by expanding genetic variability in rice. We call this method genome fusion.

• The KIPS Transactions:PartA
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• v.9A no.3
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• pp.387-398
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• 2002

As whole genome sequences of many organisms have been revealed by small-scale genome projects, the intensive research on individual genes and their functions has been performed. However on-memory algorithms are inefficient to analysis of whole genome sequences, since the size of individual whole genome is from several million base pairs to hundreds billion base pairs. In order to effectively manipulate the huge sequence data, it is necessary to use the indexed data structure for external memory. In this paper, we introduce a workbench system for analysis and visualization of whole genome sequence using string B-tree that is suitable for analysis of huge data. This system consists of two parts : analysis query part and visualization part. Query system supports various transactions such as sequence search, k-occurrence, and k-mer analysis. Visualization system helps biological scientist to easily understand whole structure and specificity by many kinds of visualization such as whole genome sequence, annotation, CGR (Chaos Game Representation), k-mer, and RWP (Random Walk Plot). One can find the relations among organisms, predict the genes in a genome, and research on the function of junk DNA using our workbench.

• Genomics & Informatics
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• v.5 no.4
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• pp.179-187
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• 2007

An increasing number of primate genomes are being sequenced. A direct comparison of repeat elements in human genes and their corresponding chimpanzee orthologs will not only give information on their evolution, but also shed light on the major evolutionary events that shaped our species. We have developed REPEATOME to enable visualization and subsequent comparisons of human and chimpanzee repeat elements. REPEATOME (http://www.repeatome.org/) provides easy access to a complete repeat element map of the human genome, as well as repeat element-associated information. It provides a convenient and effective way to access the repeat elements within or spanning the functional regions in human and chimpanzee genome sequences. REPEATOME includes information to compare repeat elements and gene structures of human genes and their counterparts in chimpanzee. This database can be accessed using comparative search options such as intersection, union, and difference to find lineage-specific or common repeat elements. REPEATOME allows researchers to perform visualization and comparative analysis of repeat elements in human and chimpanzee.

• Genomics & Informatics
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• v.3 no.2
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• pp.52-54
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• 2005

Visualization of the homology information is an important method to analyze the evolutionary and functional meanings of genes. With a database containing model genomes of Homo sapiens, Mus muculus, and Rattus norvegicus, we constructed a web­based comparative analysis tool, BioCovi, to visualize the homology information of mammalian sequences on a very large scale. The user interface has several features: it marks regions whose identity is greater than that specified, it shows or hides gaps from the result of global sequence alignment, and it inverts the graph when total identity is higher than the threshold specified.

• Genomics & Informatics
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• v.17 no.1
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• pp.4.1-4.7
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• 2019

In this paper, we propose a window-based mechanism visualization approach as an alternative way to measure the seriousness of the difference among data-insights extracted from a composite biodata point. The approach is based on two components: undirected graph and Mosaab-metric space. The significant application of this approach is to visualize the segmented genome of a virus. We use Influenza and Ebola viruses as examples to demonstrate the robustness of this approach and to conduct comparisons. This approach can provide researchers with deep insights about information structures extracted from a segmented genome as a composite biodata point, and consequently, to capture the segmented genetic variations and diversity (variants) in composite data points.

• Genomics & Informatics
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• v.3 no.3
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• pp.68-73
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• 2005

Pharmacogenomics research requires an intelligent integration of large-scale genomic and clinical data with public and private knowledge resources. We developed a web-based knowledge base for KPRN (Korea Pharmacogenomics Research Network, http://kprn.snubi. org/). Four major types of information is integrated; genetic variation, drug information, disease information, and literature annotation. Eighteen Korean pharmacogenomics research groups in collaboration have submitted 859 genotype data sets for 91 disease-related genes. Integrative analysis and visualization of the large collection of data supported by integrated biomedical path­ways and ontology resources are provided with a user-friendly interface and visualization engine empowered by Generic Genome Browser.

• Journal of Convergence for Information Technology
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• v.8 no.6
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• pp.201-207
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• 2018

A genome contains all genetic information of an organism. Within a specific species, unique traits appear for each individual, which can be identified by analyzing nucleotide sequences. Many Genome-Wide Associations Studies have been carried out to find genetic associations and cause of diseases from slightly different base among the individuals. It is important to identify occurrence of slight variations for polymorphisms of individuals. In this paper, we introduce an analysis and visualization tool for specific variation pattern identification of polymorphisms in nucleotide sequences and show the validity of the tool by applying it to analyzing nucleotide sequences of subcultured pOka strain of varicella-zoster virus. The tool is expected to help efficiently explore allele frequency variations and genetic factors within a species.

• Genomics & Informatics
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• v.18 no.4
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• pp.46.1-46.4
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• 2020

We developed the BaSDAS (Barcode-Seq Data Analysis System), a GUI-based pooled knockout screening data analysis system, to facilitate the analysis of pooled knockout screen data easily and effectively by researchers with limited bioinformatics skills. The BaSDAS supports the analysis of various pooled screening libraries, including yeast, human, and mouse libraries, and provides many useful statistical and visualization functions with a user-friendly web interface for convenience. We expect that BaSDAS will be a useful tool for the analysis of genome-wide screening data and will support the development of novel drugs based on functional genomics information.

• Journal of KIISE:Software and Applications
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• v.31 no.12
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• pp.1602-1610
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• 2004

As various genome projects have produced enormous amount of biosequence data, functional sequence analysis in terms of tile nucleic acid and protein becomes very significant. In functional genomics and proteomics, the functional analysis of each individual gene and protein remains a big challenge. Contrary to traditional studies, which regard proteins as not components of a whole protein interaction network but individual entities, recent studies have focused on examining functions and roles of each individual gene and protein in view of a whole life system. In this regard, it has been recognized as an appropriate method to analyze protein function on the basis of synthetic information of its interaction and domain modularity. In this context, this paper introduces the PIVS (Protein-protein interaction Inference & Visualization System), which predicts the interaction relationship of input proteins by taking advantage of information on homology degree, domain modules which input sequences contain, and protein interaction relationship. The information on domain modules can increase the accuracy of the function and interaction relationship analysis in terms of the specificity and sensitivity.