Semantic systems biology: Formal knowledge representation in systems biology for model construction, retrieval, validation and discovery

With the publication of the human genome, scientists worldwide opened champagne and let out a collective cheer for progress in biology. After all, the untold number of interactions of tens of thousands of genes, a greater number of their products and product derivatives, and tens of thousands of chemicals came much closer to complete characterization. Paradoxically however, while individual efforts produced important biological results, an integrated view of biology from systems perspective seemed ever more distant due to the complexity of data integration from multiple knowledge representation forms, formalisms, modeling paradigms, and conflicting scientific statements. To address this, semantic technologies have risen over the past decade with the promise of truly unifying biological knowledge and allowing cross-domain queries and model integration. In this chapter, we shall examine Semantic Web technologies and their applications to build, publish, query, discover, compare, validate, reason about, and evaluate models and knowledge in Systems Biology. We shall specifically address biological ontologies, open data repositories, modeling and annotation tools, and selected promising applications of Semantic Systems Biology. We firmly believe that it shall soon be possible to completely close the gap between facts, models, and results, and to fully apply the accrued models and facts to evaluate biological hypotheses on a system level, discovering meaning within the vast collection of biological knowledge and taking Systems Biology research to a new, unprecedented level.