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Systemic ontologies

 

Bacterial interlocked Process ONtology (BiPON)

Background

High-throughput technologies produce huge amounts of heterogeneous data at all cellular levels. In parallel, dramatic progresses on the understanding of molecular mechanisms involved in the adaptation of the cell to environmental changes have been achieved. Structuring these data and biological knowledge requires the development of integrative tools and methods to share and extract valuable information. Bio-ontologies are usually highly suitable to tackle this two interlaced integration problem since they can intrinsically formalize and organize different levels and sources of knowledge, information and data. The challenge is then to have an ontology that could embrace all cellular levels from a single molecule to a high-level cellular process and connect these entities to omics data, sequence information and finally parameters (reaction rate, association constant, etc.). Such an ontology does not currently exist.

In collaboration with the LRI (https://www.lri.fr/), we developed the Bacterial interlocked Process ONtology (BiPON), an ontology permitting a multi-scale systemic representation of bacterial cellular processes and the coupling to their mathematical models. BiPON is further composed of two sub-ontologies, bioBiPON and modelBiPON. bioBiPON aims at organizing the systemic description of biological information while modelBiPON aims at describing the mathematical models (including parameters) associated to each biological process. As a proof of concept, we deploy BiPON on the description on the whole translation process. Automatic reasoning using bridge rules on specific classes then relates these two sub-ontologies. By doing so, biological processes are then automatically related to their mathematical models integrating specific parameters. 41% of BiPON classes have been imported from different well-established bio-ontologies while the others have been manually defined and curated. Currently, BiPON integrates the main bacterial gene expression processes. These processes are representative enough to regroup most of the difficulties in the formal knowledge description.

The knowledge formalization included in BiPON is highly flexible and generic. Most of the known cellular processes, new participants or other knowledge resources could be inserted in BiPON, and then linked to mathematical models if any. Altogether, BiPON opens up promising perspectives for knowledge integration and sharing, and could be used by various communities such as biologists, and system and computational biologists, and the emerging community of whole-cell modeling.

 

Download

BiPON is distributed under the license Creative Commons Attribution 4.0 (CC-by; https://creativecommons.org/licenses/by/4.0/) and can be downloaded here.

In addition, a toy ontology that is representative of BIPON and that permits to investigate automatic reasoning and SWRL rules can be downloaded here.

 

Bacterial interlocked Process Ontology for metabolism (BiPOm)

Background

Managing and organizing biological knowledge remains a major challenge due to the complexity and the level of sophisticity of living systems. Recently, systemic representations were shown to be promising to tackle such challenge at the whole-cell scale. In such representations, the cell is considered as a system composed of interlocked subsystems. The question is now to develop relevant tools to formalize the systemic description of cells.


In collaboration with the LRI, AgroParistech and GQE, we introduce BiPOm, an ontology  describing metabolic processes as interlocked subsystems using a minimal set of classes and properties. We explicitly formalized the relations between the enzyme, its activity, the substrates and the products of the reaction, as well as the active state of all involved molecules, using Description Logics language. We further showed that the information of molecules such as molecular types or molecular properties can be deduced using SWRL rules and automatic reasoning on instances of BiPOm. The information necessary to instantiate BiPOm can be extracted from existing databases or existing bio-ontologies. Altogether, this results in a paradigm shift where the anchorage of knowledge is rerouted from the molecule to the biological process.

Download

BiPOm is distributed under the license Creative Commons Attribution 4.0 (CC-by; https://creativecommons.org/licenses/by/4.0/) and can be downloaded here.

 



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