Seamlessly integrating similarity queries in SQL

Modern database applications are increasingly employing database management systems (DBMS) to store multimedia and other complex data. To adequately support the queries required to retrieve these kinds of data, the DBMS need to answer similarity queries. However, the standard structured query language (SQL) does not provide effective support for such queries. This paper proposes an extension to SQL that seamlessly integrates syntactical constructions to express similarity predicates to the existing SQL syntax and describes the implementation of a similarity retrieval engine that allows posing similarity queries using the language extension in a relational DBM. The engine allows the evaluation of every aspect of the proposed extension, including the data definition language and data manipulation language statements, and employs metric access methods to accelerate the queries. Copyright (c) 2008 John Wiley & Sons, Ltd.

Critical applications of SW 846 US EPA methods to evaluation of marine samples quality

Technical evaluation of analytical data is of extreme relevance considering it can be used for comparisons with environmental quality standards and decision-making as related to the management of disposal of dredged sediments and the evaluation of salt and brackish water quality in accordance with CONAMA 357/05 Resolution. It is, therefore, essential that the project manager discusses the environmental agency's technical requirements with the laboratory contracted for the follow-up of the analysis underway and even with a view to possible re-analysis when anomalous data are identified. The main technical requirements are: (1) method quantitation limits (QLs) should fall below environmental standards; (2) analyses should be carried out in laboratories whose analytical scope is accredited by the National Institute of Metrology (INMETRO) or qualified or accepted by a licensing agency; (3) chain of custody should be provided in order to ensure sample traceability; (4) control charts should be provided to prove method performance; (5) certified reference material analysis or, if that is not available, matrix spike analysis, should be undertaken and (6) chromatograms should be included in the analytical report. Within this context and with a view to helping environmental managers in analytical report evaluation, this work has as objectives the discussion of the limitations of the application of SW 846 US EPA methods to marine samples, the consequences of having data based on method detection limits (MDL) and not sample quantitation limits (SQL), and present possible modifications of the principal method applied by laboratories in order to comply with environmental quality standards.

Integration and visualization of systems biology data in context of the genome

Background: High-density tiling arrays and new sequencing technologies are generating rapidly increasing volumes of transcriptome and protein-DNA interaction data. Visualization and exploration of this data is critical to understanding the regulatory logic encoded in the genome by which the cell dynamically affects its physiology and interacts with its environment. Results: The Gaggle Genome Browser is a cross-platform desktop program for interactively visualizing high-throughput data in the context of the genome. Important features include dynamic panning and zooming, keyword search and open interoperability through the Gaggle framework. Users may bookmark locations on the genome with descriptive annotations and share these bookmarks with other users. The program handles large sets of user-generated data using an in-process database and leverages the facilities of SQL and the R environment for importing and manipulating data. A key aspect of the Gaggle Genome Browser is interoperability. By connecting to the Gaggle framework, the genome browser joins a suite of interconnected bioinformatics tools for analysis and visualization with connectivity to major public repositories of sequences, interactions and pathways. To this flexible environment for exploring and combining data, the Gaggle Genome Browser adds the ability to visualize diverse types of data in relation to its coordinates on the genome. Conclusions: Genomic coordinates function as a common key by which disparate biological data types can be related to one another. In the Gaggle Genome Browser, heterogeneous data are joined by their location on the genome to create information-rich visualizations yielding insight into genome organization, transcription and its regulation and, ultimately, a better understanding of the mechanisms that enable the cell to dynamically respond to its environment.