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The increasing availability of omics data poses new challenges to bioinformatics applications regarding the efficient storage and integration of experimental data, their efficient and high-throughput preprocessing and analysis, the building of reproducible "in silico" experiments, the integration of analysis results with pre-existing knowledge repositories stored into ontologies, like Gene Ontology, or into specialised databases, as those available in pharmacogenomics. This paper presents an overview of how parallelism, service orientation, and knowledge management techniques can be used to face those challenges presenting some recent bioinformatics tools and projects that employ such technologies in different stages of the bioinformatics analysis’s pipeline.

The role of parallelism, web services and ontologies in bioinformatics and omics data management and analysis