%0 Journal Article
%T Biomedical Semantics: the Hub for Biomedical Research 2.0
%A Dietrich Rebholz-Schuhmann
%A Goran Nenadic
%J Journal of Biomedical Semantics
%D 2010
%I BioMed Central
%R 10.1186/2041-1480-1-1
%X New discoveries in biology and medicine over the last two decades have been facilitated by large-scale data generation exercises as part of high-throughput experiments [1]. The observed data is maintained in ever growing scientific public databases as structured data, while novel scientific findings are reported in a semi- or un-structured form in the literature. Many of the past and present developments in biomedicine, in particular in computational biology and medical informatics, have focused on structured data management. At the same time, there has been a remarkable increase in the number and coverage of semantics resources and semantically annotated repositories to leverage biomedical knowledge from their structured and unstructured origins alike [2].As part of the new developments, biomedical research is not relying only on local data and findings generated within individual laboratories, but is increasingly integrating shared, publicly available biomedical repositories. Furthermore, researchers exploit data resources from miscellaneous domains: for example, molecular biologists using toxicological data and medical scientists exploring data resources from molecular biology or environmental sciences. Altogether, biomedical research is moving beyond approaches utilizing "hand-crafted" hypotheses and inference techniques towards approaches that are trained on large-scale, semantically integrated biomedical data. For example, research in systems biology and systems medicine requires semantic integration of data across the biomedical domain to feed it into comprehensive and formalised models of living beings, utilising techniques from computer science, mathematics and engineering to analyse and predict biological and medical outcomes based on experimental and formal semantics descriptions.Indeed, in recent years, we have been witnessing an evolution towards formalising biomedical knowledge in explicit domain models such as curated and annotated datasets, ontologie
%U http://www.jbiomedsem.com/content/1/1/1