• Genomics & Informatics
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• v.8 no.4
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• pp.165-169
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• 2010

The Korean Bioinformation Center (KOBIC) is a national bioinformatics research center in Korea. We developed many bioinformatics algorithms and applications to facilitate the biological interpretation of OMICS data. Here we present an introduction to major bioinformatics resources of databases and tools developed at KOBIC. These resources are classified into three main fields: genome, proteome, and literature. In the genomic resources, we constructed several pipelines for next generation sequencing (NGS) data processing and developed analysis algorithms and web-based database servers including miRGator, ESTpass, and CleanEST. We also built integrated databases and servers for microarray expression data such as MDCDP. As for the proteome data, VnD database, WDAC, Localizome, and CHARMM_HM web servers are available for various purposes. We constructed IntoPub server and Patome database in the literature field. We continue constructing and maintaining the bioinformatics infrastructure and developing algorithms.

• International Journal of Contents
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• v.5 no.2
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• pp.6-15
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• 2009

Recently many different programming languages have emerged for the development of bioinformatics applications. In addition to the traditional languages, languages from open source projects such as BioPerl, BioPython, and BioJava have become popular because they provide special tools for biological data processing and are easy to use. However, it is not well-studied which of these programming languages will be most suitable for a given bioinformatics task and which factors should be considered in choosing a language for a project. Like many other application projects, bioinformatics projects also require various types of tasks. Accordingly, it will be a challenge to characterize all the aspects of a project in order to choose a language. However, most projects require some common and primitive tasks such as file I/O, text processing, and basic computation for counting, translation, statistics, etc. This paper presents the benchmarking results of six popular languages, Perl, BioPerl, Python, BioPython, Java, and BioJava, for several common and simple bioinformatics tasks. The experimental results of each language are compared through quantitative evaluation metrics such as execution time, memory usage, and size of the source code. Other qualitative factors, including writeability, readability, portability, scalability, and maintainability, that affect the success of a project are also discussed. The results of this research can be useful for developers in choosing an appropriate language for the development of bioinformatics applications.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.1
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• pp.1-5
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• 2008

Generally the analytical tools of data mining have two learning types which are supervised and unsupervised learning algorithms. Classification and prediction are main analysis tools for supervised learning. In this paper, we perform a comparison study of classification algorithms in data mining. We make comparative studies between popular classification algorithms which are LDA, QDA, kernel method, K-nearest neighbor, naive Bayesian, SVM, and CART. Also, we use almost all classification data sets of UCI machine learning repository for our experiments. According to our results, we are able to select proper algorithms for given classification data sets.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.383-387
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• 2005

One of the most important issues in post-genome era is identifying functions of genes and understanding the interaction among them. Such interactions from complex biochemical pathways, which are very useful to understand the organism system. We present an integrated biochemical pathway database system with a set of software tools for reconstruction, visualization, and simulation of the pathways from the database. The novel features of the presented system include: (a) automatic integration of the heterogeneous biochemical pathway databases, (b) gene ontology for high quality of database in the integration and query (c) various biochemical simulations on the pathway database, (d) dynamic pathway reconstruction for the gene list or sequence data, (e) graphical tools which enable users to view the reconstructed pathways in a dynamic form, (f) importing/exporting SBML documents, a data exchange standard for systems biology.

• Bioinformatics and Biosystems
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• v.1 no.1
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• pp.17-27
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• 2006

Recent progress in the development of non-invasive imaging technologies continues to strengthen the role of molecular imaging biological research. These tools have been validated recently in variety of research models, and have been shown to provide continuous quantitative monitoring of the location(s), magnitude, and time-variation of gene delivery and/or expression. This article reviews the use of radionuclide, magnetic resonance, and optical imaging technologies as they have been used in imaging gene delivery and gene expression for molecular imaging applications. The studies published to date demonstrate that noninvasive imaging tools will help to accelerate pre-clinical model validation as well as allow for clinical monitoring of human diseases.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2001.10a
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• pp.97-115
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• 2001

cDNA microarray technology allows the monitoring of expression levels for thousands of genes simultaneously. Many statistical analysis tools become widely applicable to the analysis of cDNA microarray data. In this talk, we consider a two-way ANOVA model to differentiate genes that have high variability and ones that do not. Using this model, we detect genes that have different gene expression profiles among experimental groups. The two-way ANOVA model is illustrated using cDNA microarrays of 3,800 genes obtained in an experiment to search for changes in gene expression profiles during neuronal differentiation of cortical stem cells.

• Genomics & Informatics
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• v.13 no.4
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• pp.119-125
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• 2015

RNA is a polymeric molecule implicated in various biological processes, such as the coding, decoding, regulation, and expression of genes. Numerous studies have examined RNA features using whole transcriptome sequencing (RNA-seq) approaches. RNA-seq is a powerful technique for characterizing and quantifying the transcriptome and accelerates the development of bioinformatics software. In this review, we introduce routine RNA-seq workflow together with related software, focusing particularly on transcriptome reconstruction and expression quantification.

• Genomics & Informatics
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• v.14 no.4
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• pp.241-254
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• 2016

Environmental microbes like Bordetella petrii has been established as a causative agent for various infectious diseases in human. Again, development of drug resistance in B. petrii challenged to combat against the infection. Identification of potential drug target and proposing a novel lead compound against the pathogen has a great aid and value. In this study, bioinformatics tools and technology have been applied to suggest a potential drug target by screening the proteome information of B. petrii DSM 12804 (accession No. PRJNA28135) from genome database of National Centre for Biotechnology information. In this regards, the inhibitory effect of nine natural compounds like ajoene (Allium sativum), allicin (A. sativum), cinnamaldehyde (Cinnamomum cassia), curcumin (Curcuma longa), gallotannin (active component of green tea and red wine), isoorientin (Anthopterus wardii), isovitexin (A. wardii), neral (Melissa officinalis), and vitexin (A. wardii) have been acknowledged with anti-bacterial properties and hence tested against identified drug target of B. petrii by implicating computational approach. The in silico studies revealed the hypothesis that lpxD could be a potential drug target and with recommendation of a strong inhibitory effect of selected natural compounds against infection caused due to B. petrii, would be further validated through in vitro experiments.

• Journal of Computing Science and Engineering
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• v.11 no.4
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• pp.111-120
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• 2017

Post-translational modifications (PTMs) of proteins play substantial roles in the gene regulation of cell physiological functions and in the generation of major diseases. However, the majority of existing studies only explored a certain PTM of proteins, while very few have investigated the PTMs of two or more domains and the effects of their interactions. In this study, after collecting data regarding a large number of breast cancer-related and validated PTMs, a sequence and domain analysis of breast cancer proteins was carried out using bioinformatics methods. Then, protein-protein interaction network-related tools were applied in order to determine the crosstalks between the PTMs of the proteins. Finally, statistical and functional analyses were conducted to identify more modification sites of domains and proteins that may interact with at least two or more PTMs. In addition to exploring the associations between the interactive effects of PTMs, the present study also provides important information that would allow biologists to further explore the regulatory pathways of biological functions and related diseases.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.2
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• pp.29-36
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• 2009

Due to the progress of Bioinformatics field, We are making use of analyzing tools for effective analyzing enormous data of DNA sequence. But there was inconvenience in existing tools when searching and applying data for analyzing. Our treatise proposes a tool developed by a form based on RIA(Rich Internet Application) that you can solve the problems came from weak points. The analyzing tool for RIA indexing data of DNA sequence shows the results by real time in basis of Web 2.0 which supplemented basis on a form of Web. The web application was developed in Flex2 on Windows workstation.