• Interdisciplinary Bio Central
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• v.3 no.3
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• pp.12.1-12.3
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• 2011

Bioinformatics tools and databases are useful for understanding and processing various biological data. Numerous resources are being published each year. It is not a trivial task to find up-to-date relevant tools and databases. Moreover, no server is available to provide comprehensive coverage on bioinformatics resources in all biological fields. Here, we present a directory server called IntoPub that provides information on web resources. First, we downloaded XML-formatted abstracts containing web URLs from the NCBI PubMed database by using 'ESearch-EFetch' function in the NCBI E-utilities. The information is obtained from abstracts in the PubMed by extracting 'www' or 'http' prefixes. Then, we cu-rate the downloaded abstracts both in automatic and manual fashion. As of July 2011, the IntoPub database has 12,118 abstracts containing web URLs from 174 journals. Our anal-ysis shows that the number of abstracts containing web resources has increased signifi-cantly every year. The server has been tested by many biologists from several countries to get opinion on user satisfaction, usefulness, practicability, and ease of use since January 2010. In the IntoPub web server, users can easily find relevant bioinformatics resources, as compared to searching in PubMed. IntoPub will continue to update and incorporate new web resources from PubMed and other literature databases. IntoPub, available at http://into.kobic.re.kr/, is updated every day.

• IMMUNE NETWORK
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• v.2 no.3
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• pp.125-132
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• 2002

In the past, bioinformatics was often regarded as a difficult and rather remote field, practiced only by computer scientists and not a practical tool available to biologists. However, the various on-going genome projects have had a serious impact on biological sciences in various ways and now there is little doubt that bioinformatics is an essential part of the research environment, with a wealth of biological information to analyze and predict. Fully sequenced genomes made us to have additional insights into the functional properties of the encoded proteins and made it possible to develop new tools and schemes for functional biology on a proteomic scale. Among those are the yeast two-hybrid system, mass spectrometry and microarray: the technology of choice to detect protein-protein interactions. These functional insights emerge as networks of interacting proteins, also known as "pathway informatics" or "interactomics". Without exception it is no longer possible to make advances in the signaling/regulatory pathway studies without integrating information technologies with experimental technologies. In this paper, we will introduce the databases of protein interaction worldwide and discuss several challenging issues regarding the actual implementation of databases.

• Journal of Computing Science and Engineering
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• v.1 no.1
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• pp.1-30
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• 2007

In this paper we have provided an extensive survey of the databases and other resources related to the current research in bioinformatics and the issues that confront the database researcher in helping the biologists. Initially we give an overview of the concepts and principles that are fundamental in understanding the basis of the data that has been captured in these databases. We briefly trace the evolution of biological advances and point out the importance of capturing data about genes, the fundamental building blocks that encode the characteristics of life and proteins that are the essential ingredients for sustaining life. The study of genes and proteins is becoming extremely important and is being known as genomics and proteomics, respectively. Whereas there are numerous databases related to various subfields of biology, we have maintained a focus on genomic and proteomic databases which are the crucial stepping stones for other fields and are expected to play an important role in the future applications of biology and medicine. A detailed listing of these databases with information about their sizes, formats and current status is presented. Related databases like molecular pathways and interconnection network databases are mentioned, but their full coverage would be beyond the scope of a single paper. We comment on the peculiar nature of the data in biology that presents special problems in organizing and accessing these databases. We also discuss the capabilities needed for database development and information management in the bioinformatics arena with particular attention to ontology development. Two research case studies based on our own research are summarized dealing with the development of a new genome database called Mitomap and the creation of a framework for discovery of relationships among genes from the biomedical literature. The paper concludes with an overview of the applications that will be driven from these databases in medicine and healthcare. A glossary of important terms is provided at the end of the paper.

• Journal of Information Processing Systems
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• v.6 no.2
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• pp.163-176
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• 2010

Nowadays due to the rapid advances in the field of information systems, transactional databases are being updated regularly and/or periodically. The knowledge discovered from these databases has to be maintained, and an incremental updating technique needs to be developed for maintaining the discovered association rules from these databases. The concept of Temporal Association Rules has been introduced to solve the problem of handling time series by including time expressions into association rules. In this paper we introduce a novel algorithm for Incremental Mining of General Temporal Association Rules (IMTAR) using an extended TFP-tree. The main benefits introduced by our algorithm are that it offers significant advantages in terms of storage and running time and it can handle the problem of mining general temporal association rules in incremental databases by building TFP-trees incrementally. It can be utilized and applied to real life application domains. We demonstrate our algorithm and its advantages in this paper.

• Journal of Preventive Medicine and Public Health
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• v.35 no.2
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• pp.83-91
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• 2002

Bioinformatics is a rapidly emerging field of biomedical research. A flood of large-scale genomic and postgenomic data means that many of the challenges in biomedical research are now challenges in computational sciences. Clinical informatics has long developed methodologies to improve biomedical research and clinical care by integrating experimental and clinical information systems. The informatics revolutions both in bioinformatics and clinical informatics will eventually change the current practice of medicine, including diagnostics, therapeutics, and prognostics. Postgenome informatics, powered by high throughput technologies and genomic-scale databases, is likely to transform our biomedical understanding forever much the same way that biochemistry did a generation ago. The paper describes how these technologies will impact biomedical research and clinical care, emphasizing recent advances in biochip-based functional genomics and proteomics. Basic data preprocessing with normalization, primary pattern analysis, and machine learning algorithms will be presented. Use of integrated biochip informatics technologies, text mining of factual and literature databases, and integrated management of biomolecular databases will be discussed. Each step will be given with real examples in the context of clinical relevance. Issues of linking molecular genotype and clinical phenotype information will be discussed.

• 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.

• Genomics & Informatics
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• v.11 no.3
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• pp.102-113
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• 2013

Metagenomics has become one of the indispensable tools in microbial ecology for the last few decades, and a new revolution in metagenomic studies is now about to begin, with the help of recent advances of sequencing techniques. The massive data production and substantial cost reduction in next-generation sequencing have led to the rapid growth of metagenomic research both quantitatively and qualitatively. It is evident that metagenomics will be a standard tool for studying the diversity and function of microbes in the near future, as fingerprinting methods did previously. As the speed of data accumulation is accelerating, bioinformatic tools and associated databases for handling those datasets have become more urgent and necessary. To facilitate the bioinformatics analysis of metagenomic data, we review some recent tools and databases that are used widely in this field and give insights into the current challenges and future of metagenomics from a bioinformatics perspective.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.301-305
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• 2002

Bioinformatics can beexplained as the science of developing algorithms, applicatiou tools, and computer databases and so on, for the purpose of supporting and enhancing biological research. Bioinformatic information systems (BIS) typically handle large data sets and the amount of the data goes up exponentially. Another impediment to easy extraction and retrieval of genomic data in BIS is the need to access different sites for similar information. Recently. there has been some attempts to integrate bioinformatics data in the World Wide Web (WWW) among the bioinformatics community by the internet computing technology. However, the work to integrate bioinformatics data on a universal platform has some problems because of the lack of standard, terminologies, semantics, and ontologies about bioinformatics. In this paper, an XML-based BIS architecture is proposed as an integrated BIS framework. The XML and related technologies allow the creation of meaningful information tags to exchange data between various databases as a standard format, and to create more simple interfaces. This integrated BIS framework has bioinformatic architectural components which is used in the Corporate Information Factory (CIF) method.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.9-9
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• 2005

• Proceedings of the Korea Contents Association Conference
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• 2007.11a
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• pp.3-6
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• 2007

KISTI(Korea Institute of Science & Technology Information) CCBB(Center for Computational Biology and Bioinformatics) Website has been providing bioinformatics contents(databases and analysis tools) services to construct IT-based bioinformatics infrastructure. It also carries out the services to support domestic bioinformatics R&D activity and to construct the infrastructure. But, these services are not actively available because this CCBB website is not wellknown to users. Therefore, we performed the user survey for the researchers who are studying in the field of biological science. The items of this survey consist of subjects on bioinformatics databases, analysis tools and BioInfoNet. After the user survey is rearranged and analyzed, the result of survey will be used to provide the good service to the users who are need of bioinformatics infrastructure such as databases and analysis tools etc.