UNASSIGNED: This paper outlines the work for which Roland Grafstr  m and Pekka Kohonen were awarded the 2014 Lush Science Prize. The research activities of the Grafstr  m laboratory have, for many years, @entity5 biology studies, as well as the development and application of @entity137 -predictive in vitro models to determine chemical safety. Through the integration of in silico analyses of diverse types of genomics data (transcriptomic and proteomic), their efforts have proved to fit well into the recently-developed Adverse Outcome Pathway paradigm. Genomics analysis within state-of-the-art @entity5 biology research and Toxicology in the 21st Century concepts share many technological tools. A key category within the Three Rs paradigm is the Replacement of animals in @entity137 testing with alternative methods, such as bioinformatics-driven analyses of data obtained from @entity1 cell cultures exposed to diverse toxicants. This work was recently expanded within the pan-European SEURAT-1 project (Safety Evaluation Ultimately Replacing Animal Testing), to replace repeat-dose @entity137 testing with data-rich analyses of sophisticated cell culture models. The aims and objectives of the SEURAT project have been to guide the application, analysis, interpretation and storage of 'omics' technology-derived data within the service-oriented sub-project, ToxBank. Particularly addressing the Lush Science Prize focus on the relevance of @entity137 pathways, a 'data warehouse' that is under continuous expansion, coupled with the development of novel data storage and management methods for toxicology, serve to address data integration across multiple 'omics' technologies. The prize winners' guiding principles and concepts for modern knowledge management of toxicological data are summarised. The translation of basic discovery results ranged from chemical-testing and material-testing data, to information relevant to @entity1 health and environmental safety.

Toward the Replacement of Animal Experiments through the Bioinformatics-driven Analysis of 'Omics' Data from XXXX Cell Cultures.

@entity5 :: ('MESH:D009369', 'Disease') :: ['cancer', 'covered cancer'] @entity1 :: ('9606', 'Species') :: ['human'] @entity137 :: ('MESH:D064420', 'Disease') :: ['toxicity']
@entity1 :: (9606,Species) :: ['Human']
