Abstract
BackgroundHigh-throughput technologies produce huge amounts of heterogeneous biological data at all cellular levels. Structuring these data together with biological knowledge is a critical issue in biology and requires integrative tools and methods such as bio-ontologies to extract and share valuable information. In parallel, the development of recent whole-cell models using a systemic cell description opened alternatives for data integration. Integrating a systemic cell description within a bio-ontology would help to progress in whole-cell data integration and modeling synergistically.ResultsWe present BiPON, an ontology integrating a multi-scale systemic representation of bacterial cellular processes. BiPON consists in of two sub-ontologies, bioBiPON and modelBiPON. bioBiPON organizes the systemic description of biological information while modelBiPON describes the mathematical models (including parameters) associated with biological processes. bioBiPON and modelBiPON are related using bridge rules on classes during automatic reasoning. Biological processes are thus automatically related to mathematical models. 37% of BiPON classes stem from different well-established bio-ontologies, while the others have been manually defined and curated. Currently, BiPON integrates the main processes involved in bacterial gene expression processes.ConclusionsBiPON is a proof of concept of the way to combine formally systems biology and bio-ontology. The knowledge formalization is highly flexible and generic. Most of the known cellular processes, new participants or new mathematical models could be inserted in BiPON. Altogether, BiPON opens up promising perspectives for knowledge integration and sharing and can be used by biologists, systems and computational biologists, and the emerging community of whole-cell modeling.
Highlights
High-throughput technologies produce huge amounts of heterogeneous biological data at all cellular levels
We demonstrates that a systemic multiscale representation of biological processes, the typical perspective of systems biology, can be formally described as an ontology, and how this ontology can be built based on existing sparse bio-ontologies
As a proof of concept, we developed the Bacterial interlocked Process ONtology (BiPON) and showed that a) heterogeneous biological processes can be described with the systemic representation and b) be linked automatically to mathematical models, and that c) information about these processes can be enriched by automatic reasoning
Summary
High-throughput technologies produce huge amounts of heterogeneous biological data at all cellular levels. Systems biology has its roots in engineering science and conceptualizes the cell as a system composed of interacting sub-systems [1, 6,7,8,9,10,11] In this context, cellular processes are typically described as biological subsystems whose inputs (e.g. metabolites, proteins, or sequences, etc.) are converted into outputs by dedicated molecular machines. The molecular machines are usually composed of proteins, consume energy and chemical building blocks, and display a characteristic of operation This operation can be static or dynamic, deterministic or/and stochastic and is generally described by a formal mathematical model having inputs, outputs and model parameters. Existing standardized formats for file exchange are adequate to exchange mathematical models for specific cell processes [12, 13], but remain limited to describe a whole-cell model, i.e. a systemic multi-scale representation of interacting complex subsystems
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