We present BioSubroutine, an open depository server that automatically categorizes various subroutines frequently used in bioinformatics research. We processed a large bioinformatics subroutine library called Bio.pl that was the first Bioperl subroutine library built in 1995. Over 1000 subroutines were processed automatically and an HTML interface has been created. BioSubroutine can accept new subroutines and algorithms from any such subroutine library, as well as provide interactive user forms. The subroutines are stored in an SQL database for quick searching and accessing. BioSubroutine is an open access project under the BioLicense license scheme.
Computational Biology* ; Licensure

For the past several years, we have built various tools for automatic construction of biopathways to help biological experts, especially in the field of agriculture. We integrated several systems for constructing web applications for analyzing biological pathway information for agricultural species, constructing optimized pathway maps. In addition to building web applications for agricultural pathway information, we developed several stand-alone software tools, which are publicly downloadable under proper license agreements.
Agriculture ; Computational Biology ; Licensure

A few bioinformatics tools have been used to find out conserved regions as probes. We have developed a system based on a heuristic method with web interfaces to find out conserved regions against microbial genomes. The system runs in real time by using relative entropy in limited narrow regions and detecting similar regions between pair regions with local alignment. The system could be useful to find out conserved regions as genome-wide scale.
Computational Biology ; Entropy ; Genome

No abstract available.
Computational Biology ; Insulin Resistance

Computational Biology ; Medical Informatics

The basic graph layout technique, one of many visualization techniques, deals with the problem of positioning vertices in a way to maximize some measure of desirability in a graph. The technique is becoming critically important for further development of the field of systems biology. However, applying the appropriate automatic graph layout techniques to the genomic scale flow of metabolism requires an understanding of the characteristics and patterns of duplicate and shared vertices, which is crucial for bioinformatics software developers. In this paper, we provide the results of parsing KEGG XML files from a graph-theoretical perspective, for future research in the area of automatic layout techniques in biological pathway domains.
Computational Biology ; Metabolic Networks and Pathways ; Systems Biology

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.
Computational Biology ; Genome ; Korea ; Proteome

We developed an identifier mapping application for bioinformatics research in Java programming language. It is easy to use and provides many usability functionalities that are expected as essentials for a professional application. It supports three widely used mapping services and can convert many ids from one source database into many target databases at once. Id mapping across service providers is possible by remapping the resultant ids. Because it adheres to the NetBeans platform architecture, it can be incorporated into other NetBeans platform applications as an id mapping provider without adaption or modification.
Computational Biology ; Indonesia ; Programming Languages

OBJECTIVES: Nowadays, as the amounts of biological data are rapidly increasing, bioinformatics has become one of the important research issues. The bioinformatics data sources are, however, distributed and heterogeneous, and therefore, often poorly integrated and difficult to use together. As many bioinformatics analyses need to make use of multiple information sources, the problem of integration of bioinformatics data sources has become an important one. The purpose of this paper is to present an integration system for bioinformatics data sources. METHODS: To solve this problem, we present an integration system for bioinformatics data sources using a global MDR, which provides users with efficiency and convenience as if they use one system. We deal with the extraction of data elements for bioinformatics MDRs by using ISO 11179 mandatory attributes. RESULTS: A global bioinformatics MDR schema for given MDRs and the results of query processing are presented. CONCLUSIONS: The proposed system and concepts in this paper may be a good solution for the integration of diverse bioinformatics data sources.
Computational Biology ; Information Storage and Retrieval

Integrated genomics refers to the use of large-scale, systematically collected data from various sources to address biological and biomedical problems. A critical ingredient to a successful research program in integrated genomics is the establishment of an effective computational infrastructure. In this review, we suggest that the computational infrastructure challenges include developing tools for heterogeneous data organization and access, innovating techniques for combining the results of different analyses, and establishing a theoretical framework for integrating biological and quantitative models. For each of the three areas - data integration, analyses integration, and model integration - we review some of the current progress and suggest new topics of research. We argue that the primary computational challenges lie in developing sound theoretical foundations for understanding the genome rather than simply the development of algorithms and programs.
Computational Biology ; Foundations ; Genome ; Genomics*