Final Report Summary - DIAMONDS (Dedicated integration and modelling of novel data and prior knowledge to enable systems biology)
The ultimate aim of the DIAMONDS project was to demonstrate the power of a systems biology approach to study fundamental biological processes. The project was designed to link data integration and modelling with wet lab experimentation and it focused on the cell cycle control in four model organisms: human, Arabidopsis, Baker's and Fission yeast. The main objective was to develop a software platform with a variety of tools and applications to facilitate the analysis and integration of data allowing the development of qualitative and quantitative dynamical models to simulate the behaviour of the cell cycle system under different conditions.
The main target of the project consisted of two parts: a cell cycle knowledge base and an integrated platform of data mining, modelling and simulation tools that would allow the integrated analysis of that data in a systems biology approach: the development of a basic model, the use of this model to design new experiments, the production and analysis of novel data and the integration of these into a refined model. The knowledge base and tools would be made available and introduced to the European research community.
The particular challenge in building a systems biology consortium was twofold: on the one side there was the need to identify a biological topic with broad relevance to life science and health while, on the other side there was a need to bring together a critical mass in analysis, mining and modelling partners. The project focused on cell cycle control as an example of a fundamental process conserved throughout all the kingdoms of biology with clear relevance both for a sustainable world economy (food, biomass and renewable energy, plant-derived medicine) and for health (cancer-related dysfunctional cell cycle control). By including four different model organisms into the project cross-species comparisons and comparative genomics were included as an additional source of pathway information. In addition, implementation of the platform in all four areas would also demonstrate its broad applicability and ensure its versatility.
A basic model of the cell cycle was established in four different eukaryotic species: S. cerevisae, S. pombe, A. thaliania and H. sapiens. Initially, the project involved the de novo generation of data concerning transcript profiling and proteomics data. Progressively, the plan was to lay more focus on iterations between modelling data, designing experiments based on model predictions, subsequent experimentation, data analysis and updating of the model. The project also implemented a simulation tool which enabled users to access to the knowledge base Cell cycle ontology (CCO).
The main target of the project consisted of two parts: a cell cycle knowledge base and an integrated platform of data mining, modelling and simulation tools that would allow the integrated analysis of that data in a systems biology approach: the development of a basic model, the use of this model to design new experiments, the production and analysis of novel data and the integration of these into a refined model. The knowledge base and tools would be made available and introduced to the European research community.
The particular challenge in building a systems biology consortium was twofold: on the one side there was the need to identify a biological topic with broad relevance to life science and health while, on the other side there was a need to bring together a critical mass in analysis, mining and modelling partners. The project focused on cell cycle control as an example of a fundamental process conserved throughout all the kingdoms of biology with clear relevance both for a sustainable world economy (food, biomass and renewable energy, plant-derived medicine) and for health (cancer-related dysfunctional cell cycle control). By including four different model organisms into the project cross-species comparisons and comparative genomics were included as an additional source of pathway information. In addition, implementation of the platform in all four areas would also demonstrate its broad applicability and ensure its versatility.
A basic model of the cell cycle was established in four different eukaryotic species: S. cerevisae, S. pombe, A. thaliania and H. sapiens. Initially, the project involved the de novo generation of data concerning transcript profiling and proteomics data. Progressively, the plan was to lay more focus on iterations between modelling data, designing experiments based on model predictions, subsequent experimentation, data analysis and updating of the model. The project also implemented a simulation tool which enabled users to access to the knowledge base Cell cycle ontology (CCO).