Final Report Summary - EMI-CD (European modelling initiative combating complex diseases)
Genome research has seen fundamental technical breakthroughs in recent years such as the sequencing of the human genome and the genome of other species serving as experimental model systems. The main sociological and economical impact of genome research is the molecular understanding of major human diseases and the development of new therapies and medicals for the combat of these diseases.
While bioinformatics methods are well incorporated in the drug target discovery stage, this is not the case for the later stages. In particular, the simulation and modelling of biological processes such as disease-relevant signalling pathways and metabolic processes are under-developed in drug target validation. Nevertheless, computational methods are needed here.
With the EMI-CD project we attempted to develop software and methods that are able to meet some of the above requirements. In the first stage information was gathered on the biological objects under analysis and experimental measurements on these objects were integrated. An analysis layer translated this knowledge into biological networks. Using probabilistic learning methods, these networks were expanded in light of all available data on the objects. In the simulation and modelling layer these network hypotheses were evaluated and predictions of experiments were produced which had a direct feedback to the forthcoming experimental design and experimental verifications.
EMI-CD provided software, tools and additional methodology that is complex enough in order to cope with various experimental techniques for the discovery of gene function and the understanding of disease processes. The methodology ranges from kinetic modelling using continuous models such as Ordinary differential equations (ODEs), discrete probabilistic modelling to Boolean approaches. By incorporating expert knowledge from various databases, experimental data and computer modelling approaches it is useful for practical research.
EMI-CD has a high impact to systems biology research. The methodology developed is in use in several important disease applications on the national and European Union level. Several initiatives have been started that ensure durability and usability of the developed results.
The methodology developed in EMI-CD has contributed several unique elements that will ultimately strengthen systems biology approaches in general and disease-oriented research in particular. All developments provide user interfaces for practical applications:
- the modelling and simulation platform PyBioS capable of integrating multiple databases and experimental data with computational models;
- model analysis methodology for kinetic models that support bottom-up and top-down approaches;
- SRS system extended to multiple pathway resources supporting computational modeling;
- integrative database for transcriptome and proteomics primary data supporting computational modeling;
- model analysis methodology for discrete probabilistic models integrated in the Metareg software system;
- Reactome pathway database annotation of nine important disease-relevant pathways.
While bioinformatics methods are well incorporated in the drug target discovery stage, this is not the case for the later stages. In particular, the simulation and modelling of biological processes such as disease-relevant signalling pathways and metabolic processes are under-developed in drug target validation. Nevertheless, computational methods are needed here.
With the EMI-CD project we attempted to develop software and methods that are able to meet some of the above requirements. In the first stage information was gathered on the biological objects under analysis and experimental measurements on these objects were integrated. An analysis layer translated this knowledge into biological networks. Using probabilistic learning methods, these networks were expanded in light of all available data on the objects. In the simulation and modelling layer these network hypotheses were evaluated and predictions of experiments were produced which had a direct feedback to the forthcoming experimental design and experimental verifications.
EMI-CD provided software, tools and additional methodology that is complex enough in order to cope with various experimental techniques for the discovery of gene function and the understanding of disease processes. The methodology ranges from kinetic modelling using continuous models such as Ordinary differential equations (ODEs), discrete probabilistic modelling to Boolean approaches. By incorporating expert knowledge from various databases, experimental data and computer modelling approaches it is useful for practical research.
EMI-CD has a high impact to systems biology research. The methodology developed is in use in several important disease applications on the national and European Union level. Several initiatives have been started that ensure durability and usability of the developed results.
The methodology developed in EMI-CD has contributed several unique elements that will ultimately strengthen systems biology approaches in general and disease-oriented research in particular. All developments provide user interfaces for practical applications:
- the modelling and simulation platform PyBioS capable of integrating multiple databases and experimental data with computational models;
- model analysis methodology for kinetic models that support bottom-up and top-down approaches;
- SRS system extended to multiple pathway resources supporting computational modeling;
- integrative database for transcriptome and proteomics primary data supporting computational modeling;
- model analysis methodology for discrete probabilistic models integrated in the Metareg software system;
- Reactome pathway database annotation of nine important disease-relevant pathways.