Award details

BioModels Database, the comprehensive resource for computational models in biology

Reference	BB/J019305/1
Principal Investigator / Supervisor	Mr Henning Hermjakob
Co-Investigators / Co-Supervisors	Mr Camille Laibe, Dr Nicolas Le Novere
Institution	EMBL - European Bioinformatics Institute
Department	Computational Neurobiology Group
Funding type	Research
Value (£)	534,432
Status	Completed
Type	Research Grant
Start date	01/08/2012
End date	31/07/2015
Duration	36 months

Abstract

Modelling and simulations are becoming important pieces of the biologist toolkit. to understand life, normal or pathological, but also as complement and partially replacements to animal models. Because models are most often complex and sometimes very large, one needs to exchange and reuse rather than rebuild them. The construction, sometimes automated, of large models from elementary pieces, also requires free availability of those pieces. An open central repository is thus necessary to obtain up-to-date, state of the art models to the scientific community. BioModels Database is the reference resource to share quantitative models of biological interest. Models submitted by authors, publishers, or encoded from literature, are verified, extensively annotated and linked to external data resources. Access to the database is available via a website or programmatically using web services. Users can search for models of interest, explore and simulate them, and download a model, part of a model or the entire database in several formats. Currently largely focussed on models using process descriptions and in particular chemical kinetics, the coverage of the resource will be expanded to different modelling approaches, such as logical models, multicellular models, PKPD models. We will distribute more than the models, but also of the simulations to perform and the required datasets. We will improve the software infrastructure (full model versioning, support for more standard formats, improved search engine, ...). Moreover, we will build-up an extensive documentation and training program, based on multimedia and e-learning technologies. The availability for all of computer-readable versions of quantitative models covering all scales and all aspects of the living, normal or pathological, will have over the forthcoming years a tremendous effect on basic, applied, and translational research, in particular for drug discovery, bioengineering and synthetic biology.

Summary

Even the simplest living organisms perform a huge number of different processes, which are interconnected in complex ways to ensure that the organism responds appropriately to its environment. One of the ways of ensuring that we really understand how these processes fit together is to build quantitative models of them, that can be simulated using computers. If a computer simulation behaves differently than the real organism, we know that we've neglected an important component of the system. Quantitative models can also reveal previously unappreciated properties of complex systems, for instance paving the way toward new drug treatments. This approach, known as "Computational Systems Biology", is becoming increasingly popular now that scientists are accumulating detailed parts lists for many organisms, thanks to the "omics" efforts to comprehensively document the components of living entities. BioModels Database provides access to quantitative models of biochemical and cell biological systems that have been published in the scientific literature, and verified to be accurate. Some of these models are very simple, containing just a few processes or reactions; others contain hundreds or even thousands. The models are checked to verify that they behave as described in the reference publication. Human curators add annotations and cross link components of the models to relevant external data resources. This allows users to identify precisely the components of models, and helps them to retrieve appropriate models, which they can then visualise, simulate (online or by using appropriate dedicated software) and download (in various formats). For instance, in order to develop a quantitative model of cell tumorigenesis, one may choose a suitable model of cell-cycle, and attempt to merge it with models of relevant cell signalling pathways such as the MAP kinase cascade. Only a database of trusted, peer-reviewed, annotated up-to-date state of the art models will provide the adequate choice of "building bricks". Users can search models based on many different criteria, visualise and download them in various standard formats for further use. Since its creation in 2005 - and supported by the BBSRC since 2008 - BioModels Database has undergone an exponential growth to become the worldwide reference forquantitative models of biological processes. Deposition of models upon publication is advised by several hundreds scientific journals and the resource receives around a million page requests a year. Having developed in a mature resource serving the need of a growing UK Systems Biology community, BioModels Database must now provides for the entire biosciences. This will be achieved by expanding the coverage of BioModels Database to more types of models: using different approaches and representing biological processes at different scales. W e will also improvee the software support to make access, analysis and re-use of the models easier. We will provide access to more information than just the models themselves (simulation recipes, associated dataset, ...) as well as more historical data (to allow users to explore how a model evolved to its current form). Finally, one core aspect of the resource: the retrieval of models of interest, will be greatly facilitated. We will provide users with ranked search results and more flexible search strategies, making full use of the plethora of ontological annotations contained in the models. This development will have a significant effect on basic, applied, and translational research. In particular drug discovery, bioengineering and synthetic biology, disciplines in which computational modelling is central, will benefit from a better BioModels Database, ultimately resulting on better ageing, development of biofuels, improved and more sustainable food supplies.

Impact Summary

Further developments of BioModels Database will primarily impact the direct users of computational models in the biosciences. A large corpus of carefully annotated models available in standard formats is an invaluable resource for researchers in life science using models to understand life and for pharmaceutical and biotechnological industry using models to characterise drugs or predict the behaviour of modified living matter. We expect that the database will contribute to speed up the development, use and application of computational models, whether to understand systems, or as part of the toolkit necessary to implement the 3Rs of animal testing. A third community of users directly impacted is made of the professors, using BioModels Database as a source of trustful material to teach computational modelling, and their students. The basic and applied research conducted by the primary impacted class of users above will itself have a major effect on the society at large. It is clear that computational models are increasingly used to understand and modify life. Having an extensive, accurate and up to date corpus of such models, covering all aspects of biology will have a tremendous effect on the quality of life, maintenance of health and improved ageing. Quantitative computational models of plant metabolisms, growth, reproduction and local ecosystems can help optimising useful biomass production. This can be done by designing specific growth environments or acting directly on the living systems by cell reprogramming and synthetic biology. In turn, the benefits for sustainable food provision, but also production of energy sources such as biofuels are potentially huge.

Committee	Research Committee C (Genes, development and STEM approaches to biology)
Research Topics	X – not assigned to a current Research Topic
Research Priority	X – Research Priority information not available
Research Initiative	Bioinformatics and Biological Resources Fund (BBR) [2007-2015]
Funding Scheme	X – not Funded via a specific Funding Scheme

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