CRAVE: a database, middleware and visualization system for phenotype ontologies

MOTIVATION: A major challenge in modern biology is to link genome sequence information to organismal function. In many organisms this is being done by characterizing phenotypes resulting from mutations. Efficiently expressing phenotypic information requires combinatorial use of ontologies. However tools are not currently available to visualize combinations of ontologies. Here we describe CRAVE (Concept Relation Assay Value Explorer), a package allowing storage, active updating and visualization of multiple ontologies. RESULTS: CRAVE is a web-accessible JAVA application that accesses an underlying MySQL database of ontologies via a JAVA persistent middleware layer (Chameleon). This maps the database tables into discrete JAVA classes and creates memory resident, interlinked objects corresponding to the ontology data. These JAVA objects are accessed via calls through the middleware's application programming interface. CRAVE allows simultaneous display and linking of multiple ontologies and searching using Boolean and advanced searches.     

A standardized format for handling data on plasmids,viruses and transposons: The PVT database format

The PVT format described here has been designed to store and retrieve genetic data on plasmids, viruses or transposons with special focus on their applications. Both naturally-occurring and engineered elements can be included in it. A variety of data can be accommodated in fields that are grouped in blocks: name and type of element, database administration, element administration, history, propagation, selection and host, biological properties, cloned insert and applications. The number of fields, now 157, can be expanded as required. Most properties can be described in simple logical fields. The format is organized to permit rapid searches and to facilitate communication between database and user; connection with culture and/or DNA collections is also envisaged and adequate fields for these tasks have been provided. The format allows cross-reference with that originated by the Microbial Information Network Europe (MINE) for computer storage and handling of bacterial or fungal strain data.     

Protecs,a comprehensive and powerful storage and analysis system for OMICS data,applied for profiling the anaerobiosis response of Staphylococcus aureus COL

Broad functional genomic studies call for comprehensive and powerful data repositories for storage of genome sequences, experimental information, protein identification data, protein properties and expression values. The better such data repositories can integrate and display complex data in a clear and structured way the more biologically meaningful conclusions or novel hypotheses can be derived from extensive omics data sets. This work presents the web accessible database system Protecs and how it was used to support analysis of 50 samples drawn from four Staphylococcus aureus cultivations under anaerobiosis. Protecs incorporates findings from visualization science, e.g. micro charts and heat maps in the user interface. Its integrated tools for expression data analysis in combination with TIGR Multi Experiment Viewer were used to highlight similar gene expression profiles in single or multiple experiments based on the continuously updated S. aureus master gel. Raw data analysis results are available online at www.protecs.uni‐greifswald.de . Our meta‐study revealed that S. aureus responds in different anaerobiotic experimental setups (growth without oxygen; growth without oxygen but with supplemental pyruvate and uracil; growth without oxygen but with NO; growth without oxygen but with NO and without functional nreABC genes) with a general anaerobiosis response. Among others, this response is characterized by an induction of fermentation enzymes (PflB, Ldh1, SACOL0135, SACOL0660) as well as the response regulator SrrA. Interestingly, especially genes with a high codon adaptation index highly overlap with anaerobically induced genes.