The PIR-International databases.

PIR-International is an association of macromolecular sequence data collection centers dedicated to fostering international cooperation as an essential element in the development of scientific databases. PIR-International is most noted for the Protein Sequence Database. This database originated in the early 1960's with the pioneering work of the late Margaret Dayhoff as a research tool for the study of protein evolution and intersequence relationships; it is maintained as a scientific resource, organized by biological concepts, using sequence homology as a guiding principle. PIR-International also maintains a number of other genomic, protein sequence, and sequence-related databases. The databases of PIR-International are made widely available. This paper briefly describes the architecture of the Protein Sequence Database, a number of other PIR-International databases, and mechanisms for providing access to and for distribution of these databases.     

The KEGG databases at GenomeNet

The Kyoto Encyclopedia of Genes and Genomes (KEGG) is the primary database resource of the Japanese GenomeNet service (http://www.genome.ad.jp/) for understanding higher order functional meanings and utilities of the cell or the organism from its genome information. KEGG consists of the PATHWAY database for the computerized knowledge on molecular interaction networks such as pathways and complexes, the GENES database for the information about genes and proteins generated by genome sequencing projects, and the LIGAND database for the information about chemical compounds and chemical reactions that are relevant to cellular processes. In addition to these three main databases, limited amounts of experimental data for microarray gene expression profiles and yeast two-hybrid systems are stored in the EXPRESSION and BRITE databases, respectively. Furthermore, a new database, named SSDB, is available for exploring the universe of all protein coding genes in the complete genomes and for identifying functional links and ortholog groups. The data objects in the KEGG databases are all represented as graphs and various computational methods are developed to detect graph features that can be related to biological functions. For example, the correlated clusters are graph similarities which can be used to predict a set of genes coding for a pathway or a complex, as summarized in the ortholog group tables, and the cliques in the SSDB graph are used to annotate genes. The KEGG databases are updated daily and made freely available (http://www.genome.ad.jp/kegg/).     

The evolution of structural databases

Starting with the Protein Data Bank (PDB) as a common ancestor, the evolution of structural databases has been driven by the rapprochement of the structural world and the practical applications. The result is an impressive number of secondary structural databases that is welcomed by structural biologists and bioinformaticians but runs the risk of producing an embarrassment of riches among non-specialist users. Given that any profit depends on the number of customers, efficient interfaces between many structural data banks must be available to make their contents easily accessible. Increasing the information content of central structural repositories might be the best way to guide users through the many, sometimes overlapping databases.     

The EcoCyc and MetaCyc databases

EcoCyc is an organism-specific Pathway/Genome Database that describes the metabolic and signal-transduction pathways of Escherichia coli, its enzymes, and-a new addition-its transport proteins. MetaCyc is a new metabolic-pathway database that describes pathways and enzymes of many different organisms, with a microbial focus. Both databases are queried using the Pathway Tools graphical user interface, which provides a wide variety of query operations and visualization tools. EcoCyc and MetaCyc are available at http://ecocyc.PangeaSystems.com/ecocyc/     

Strategies for searching sequence databases

We provide a detailed overview of the choices inherent in performing a sequence database search, including the choice of algorithm, substitution matrix and gap model. Each of these choices has implications that can be described as restrictions on the underlying model of sequence evolution, the expected degree of divergence between the query sequence and the database sequences (if one uses an evolutionary based matrix), as well as the sensitivity and selectivity of the search. We conclude with a series of recommendations for researchers performing these searches based on our experience and literature studies.     

The ARKdb: genome databases for farmed and other animals

The ARKdb genome databases provide comprehensive public repositories for genome mapping data from farmed species and other animals (http://www.thearkdb.org) providing a resource similar in function to that offered by GDB or MGD for human or mouse genome mapping data, respectively. Because we have attempted to build a generic mapping database, the system has wide utility, particularly for those species for which development of a specific resource would be prohibitive. The ARKdb genome database model has been implemented for 10 species to date. These are pig, chicken, sheep, cattle, horse, deer, tilapia, cat, turkey and salmon. Access to the ARKdb databases is effected via the World Wide Web using the ARKdb browser and Anubis map viewer. The information stored includes details of loci, maps, experimental methods and the source references. Links to other information sources such as PubMed and EMBL/GenBank are provided. Responsibility for data entry and curation is shared amongst scientists active in genome research in the species of interest. Mirror sites in the United States are maintained in addition to the central genome server at Roslin.     

KNApSAcK family databases: integrated metabolite-plant species databases for multifaceted plant research

A database (DB) describing the relationships between species and their metabolites would be useful for metabolomics research, because it targets systematic analysis of enormous numbers of organic compounds with known or unknown structures in metabolomics. We constructed an extensive species-metabolite DB for plants, the KNApSAcK Core DB, which contains 101,500 species-metabolite relationships encompassing 20,741 species and 50,048 metabolites. We also developed a search engine within the KNApSAcK Core DB for use in metabolomics research, making it possible to search for metabolites based on an accurate mass, molecular formula, metabolite name or mass spectra in several ionization modes. We also have developed databases for retrieving metabolites related to plants used for a range of purposes. In our multifaceted plant usage DB, medicinal/edible plants are related to the geographic zones (GZs) where the plants are used, their biological activities, and formulae of Japanese and Indonesian traditional medicines (Kampo and Jamu, respectively). These data are connected to the species-metabolites relationship DB within the KNApSAcK Core DB, keyed via the species names. All databases can be accessed via the website http://kanaya.naist.jp/KNApSAcK_Family/. KNApSAcK WorldMap DB comprises 41,548 GZ-plant pair entries, including 222 GZs and 15,240 medicinal/edible plants. The KAMPO DB consists of 336 formulae encompassing 278 medicinal plants; the JAMU DB consists of 5,310 formulae encompassing 550 medicinal plants. The Biological Activity DB consists of 2,418 biological activities and 33,706 pairwise relationships between medicinal plants and their biological activities. Current statistics of the binary relationships between individual databases were characterized by the degree distribution analysis, leading to a prediction of at least 1,060,000 metabolites within all plants. In the future, the study of metabolomics will need to take this huge number of metabolites into consideration.     

Elimination of locus-specific inter-individual variation in quantitative PCR

Robust dosage PCR (RD-PCR), a duplex and quantitative PCR, detects large heterozygous deletions and duplications in genomic DNA samples. RD-PCR amplifies an endogenous internal control and a target locus. Two of six RD-PCR assays behaved anomalously due to lower yields specific to the targets. The variability was eliminated by heat treatment of the genomic DNA samples in 2x TE solution at 90 degrees C for 10 min. Heat treatment improves the utility of RD-PCR and may be generally helpful in multiplex PCR quantitation. The mechanism by which heat treatment eliminates inter-individual variation is unclear. The variability is not associated with DNA extraction methods, RNA contamination, or solution protein contamination, but may reflect inhibition from tightly bound chromatin proteins.     

A comprehensive datamodel for karyological databases

A project-independent data model for the entire range of karyological information provides a comprehensive picture of all data items presently used in karyological research and characterizes their logical inter-relation. It is presented in the form of a hierarchical decomposition of the subject matter down to attribute-level data items. The applied analytical methods are relevant for the structuring of information in other branches of biology. Only sporadic and inconsistent efforts have previously been made to make the huge amount of available karyological information accessible in electronic form. In the view of growing demand for the availability of scientific data on computer networks, further attempts are to be expected presently. The present data model provides a framework for the design of individual databases and ensures compatibility of the resulting datasets.     

Web-accessible proteome databases for microbial research

The analysis of proteomes of biological organisms represents a major challenge of the post-genome era. Classical proteomics combines two-dimensional electrophoresis (2-DE) and mass spectrometry (MS) for the identification of proteins. Novel technologies such as isotope coded affinity tag (ICAT)-liquid chromatography/mass spectrometry (LC/MS) open new insights into protein alterations. The vast amount and diverse types of proteomic data require adequate web-accessible computational and database technologies for storage, integration, dissemination, analysis and visualization. A proteome database system (http://www.mpiib-berlin.mpg.de/2D-PAGE) for microbial research has been constructed which integrates 2-DE/MS, ICAT-LC/MS and functional classification data of proteins with genomic, metabolic and other biological knowledge sources. The two-dimensional polyacrylamide gel electrophoresis database delivers experimental data on microbial proteins including mass spectra for the validation of protein identification. The ICAT-LC/MS database comprises experimental data for protein alterations of mycobacterial strains BCG vs. H37Rv. By formulating complex queries within a functional protein classification database "FUNC_CLASS" for Mycobacterium tuberculosis and Helicobacter pylori the researcher can gather precise information on genes, proteins, protein classes and metabolic pathways. The use of the R language in the database architecture allows high-level data analysis and visualization to be performed "on-the-fly". The database system is centrally administrated, and investigators without specific bioinformatic competence in database construction can submit their data. The database system also serves as a template for a prototype of a European Proteome Database of Pathogenic Bacteria. Currently, the database system includes proteome information for six strains of microorganisms.     

The past and future of structure databases

For many years the primary source of information about biological macromolecules was the Protein Data Bank, which is a repository of files containing coordinates of biological macromolecules. Now a variety of databases has been developed in which structures are organized in different ways. Currently available are databases that classify molecules according to their overall structural characteristics or particular features of structures, as well as databases that focus on particular protein families in depth.     

Aminoaciduria databases

Electronic encyclopaedia of human hereditary disorders of amino acid metabolism (aminoacidurias) has been created. The disease inheritance, gene location, gene mutations, biochemistry, and gene therapy of aminoacidurias are described in most detail. The database (DB) is integrated with international DBs available in Internet. The electronic encyclopaedia may serve as an educational system connecting medicine with modern molecular genetics.     

Quantitative trait locus-specific genotype x alcoholism interaction on linkage for evoked electroencephalogram oscillations

We explored the evidence for a quantitative trait locus (QTL)-specific genotype x alcoholism interaction for an evoked electroencephalogram theta band oscillation (ERP) phenotype on a region of chromosome 7 in participants of the US Collaborative Study on the Genetics of Alcoholism. Among 901 participants with both genotype and phenotype data available, we performed variance component linkage analysis (SOLAR version 2.1.2) in the full sample and stratified by DSM-III-R and Feighner-definite alcoholism categories. The heritability of the ERP phenotype after adjusting for age and sex effects in the combined sample and in the alcoholism classification sub-groups ranged from 40% to 66%. Linkage on chromosome 7 was identified at 158 cM (LOD = 3.8) in the full sample and at 108 in the non-alcoholic subgroup (LOD = 3.1). Further, we detected QTL-specific genotype x alcoholism interaction at these loci. This work demonstrates the importance of considering the complexity of common complex traits in our search for genes that predispose to alcoholism.