Jessica D Tenenbaum | PubMed Health

PubMed2006

BioWarehouse: a bioinformatics database warehouse toolkit.

BACKGROUND: This article addresses the problem of interoperation of heterogeneous bioinformatics databases. RESULTS: We introduce BioWarehouse, an open source toolkit for constructing bioinformatics database warehouses using the MySQL and Oracle relational database managers. BioWarehouse integrates its component databases into a common representational framework within a single database management system, thus enabling multi-database queries using the Structured Query Language (SQL) but also facilitating a variety of database integration tasks such as comparative analysis and data mining. BioWarehouse currently supports the integration of a pathway-centric set of databases including ENZYME, KEGG, and BioCyc, and in addition the UniProt, GenBank, NCBI Taxonomy, and CMR databases, and the Gene Ontology. Loader tools, written in the C and JAVA languages, parse and load these databases into a relational database schema. The loaders also apply a degree of semantic normalization to their respective source data, decreasing semantic heterogeneity. The schema supports the following bioinformatics datatypes: chemical compounds, biochemical reactions, metabolic pathways, proteins, genes, nucleic acid sequences, features on protein and nucleic-acid sequences, organisms, organism taxonomies, and controlled vocabularies. As an application example, we applied BioWarehouse to determine the fraction of biochemically characterized enzyme activities for which no sequences exist in the public sequence databases. The answer is that no sequence exists for 36% of enzyme activities for which EC numbers have been assigned. These gaps in sequence data significantly limit the accuracy of genome annotation and metabolic pathway prediction, and are a barrier for metabolic engineering. Complex queries of this type provide examples of the value of the data warehousing approach to bioinformatics research. CONCLUSION: BioWarehouse embodies significant progress on the database integration problem for bioinformatics.

Computational Biology↗

PubMed2006

Multiplexed protein array platforms for analysis of autoimmune diseases.

Several proteomics platforms have emerged in the past decade that show great promise for filling in the many gaps that remain from earlier studies of the genome and from the sequencing of the human genome itself. This review describes applications of proteomics technologies to the study of autoimmune diseases. We focus largely on biased technology platforms that are capable of analyzing a large panel of known analytes, as opposed to techniques such as two-dimensional gel electrophoresis (2DIGE) or mass spectroscopy that represent unbiased approaches (as reviewed in 1). At present, the main analytes that can be systematically studied in autoimmunity include autoantibodies, cytokines and chemokines, components of signaling pathways, and cell-surface receptors. We review the most commonly used platforms for such studies, citing important discoveries and limitations that exist. We conclude by reviewing advances in biomedical informatics that will eventually allow the human proteome to be deciphered.

Autoantibodies↗