The identification of the side-effects of chemicals is the serious and costly stage in the drug development. Most side-effects are caused by their toxicity and also their correlation with other diseases than target diseases. We present a novel measure that identifies disease-associated genes from the biomedical literature in terms of causing less side-effects. This enables the identification of specific disease-associated genes, the decreased expression of which would result in a lower probability of side-effects, thus contributing to efficient drug development. Our method evaluates the specificity of a gene to a particular disease based on the number of associated diseases with the gene. In addition, we consider transitive gene-disease associations, that is, indirect gene-disease associations via intermediate genes. Gene-disease associations are extracted from the PubMed abstracts based on term co-occurrences. Also, we discuss the ranking results for Alzheimer disease and various cancers to verify the effectiveness of our measure. Ranking results for other diseases are available at http://www.ps.noda.tus.ac.jp/ddss/.

BACKGROUND: There are a number of different methods for generation of trees and algorithms for phylogenetic analysis in the study of bacterial taxonomy. Genotypic information, such as SSU rRNA gene sequences, now plays a more prominent role in microbial systematics than does phenotypic information. However, the integration of genotypic and phenotypic information for polyphasic studies is necessary for the classification and identification of microbes. Thus, we devised an algorithm that objectively identifies discriminative characteristics for focused clusters on generated trees from a dataset composed of coded data, such as phenotypic information. Moreover, this algorithm has been integrated into the polyphasic analysis software, InforBIO. RESULTS: We developed a differential-character-finding algorithm based on information measures and used this algorithm to identify the characteristic that best discriminates operational taxonomic unit clusters. For all characteristics in a dataset, the algorithm estimates commonality in focused clusters and diversity among clusters by scoring based on Shannon's and relative entropies. All the characteristics selected for scoring are equally weighted. Thresholds for the scores are defined to identify discriminative characteristics for clusters efficiently from a database. The unique feature of the algorithm, which is implemented in the InforBIO software, is that it can identify the phenotypic characteristics that discriminate and are associated with the clusters of a phylogenetic tree. We successfully applied this algorithm to the study of phylogenetic clusters of Pseudomonas species. CONCLUSION: The algorithm in the InforBIO software is a novel and useful approach for microbial polyphasic studies. The algorithm can also be applied to diverse cluster analyses. The InforBIO software is available from the download site http://wdcm.nig.ac.jp/inforbio/. This software is free for personal but not commercial use.

BACKGROUND: Genome databases contain diverse kinds of information, including gene annotations and nucleotide and amino acid sequences. It is not easy to integrate such information for genomic study. There are few tools for integrated analyses of genomic data, therefore, we developed software that enables users to handle, manipulate, and analyze genome data with a variety of sequence analysis programs. RESULTS: The G-InforBIO system is a novel tool for genome data management and sequence analysis. The system can import genome data encoded as eXtensible Markup Language documents as formatted text documents, including annotations and sequences, from DNA Data Bank of Japan and GenBank encoded as flat files. The genome database is constructed automatically after importing, and the database can be exported as documents formatted with eXtensible Markup Language or tab-deliminated text. Users can retrieve data from the database by keyword searches, edit annotation data of genes, and process data with G-InforBIO. In addition, information in the G-InforBIO database can be analyzed seamlessly with nine different software programs, including programs for clustering and homology analyses. CONCLUSION: The G-InforBIO system simplifies genome analyses by integrating several available software programs to allow efficient handling and manipulation of genome data. G-InforBIO is freely available from the download site.

MOTIVATION: The DNA Data Bank of Japan (DDBJ) has developed a new DNA database system with a new schema design to accommodate rapid change and growth of requirements on the system. RESULTS: The new schema and systems were created using an object-oriented design approach. The design was accomplished in accordance with ANSI/SPARC three-level schema architecture. First, the conceptual schema was designed using a functional model named AIS (associative information structure) and was visualized in extended diagram format. The model is a natural extension of an ER (entity relationship) model and describes real-world objects in binary associations between entities with the concept of order. Second, the schema was mapped on a relational database as a physical schema. All details are concentrated in this schema and the layer lying above enjoys physical independence. Finally, as another layer, external modeling was introduced for the database applications interface. It provides set-at-a-time basis operations and was implemented as a C++ object-oriented library. On this common framework of a new schema, a new annotator's workbench named Yamato II and a World Wide Web (WWW) submission system named Sakura have been successfully developed to improve drastically daily transactions in the DDBJ. AVAILABILITY: Sakura is available at the following address: http://sakura.ddbj.nig.ac.jp. CONTACT: [email protected]

Culture collections are reservoirs of cultivable microbes, cell lines and gene libraries. Their role and duty are to supply biological resources to biomedical communities; nevertheless, their visibility from the public is low because most culture collections still have poor accesses via the Internet. Therefore the WFCC World Data Center on Micro-organisms (WDCM) developed a database that runs on IBM PCs and compatibles, which are the most popular computer and will be as powerful as workstations. The database includes various information: activities of 484 culture collections from 58 countries; an integrated list of their holdings of bacteria, fungi and yeast; and data entry system for culture collections.