BiPOm: Biological interlocked Process Ontology for metabolism. How to infer molecule knowledge from biological process?

Vincent J. Henry (1) , Fatiha Saïs (2, 3) , Elodie Marchadier (4) , Juliette Dibie-Barthelemy (5) , Anne Goelzer (1) , Vincent Fromion (1)

1 MaIAGE - Mathématiques et Informatique Appliquées du Génome à l'Environnement [Jouy-En-Josas]
2 LRI - Laboratoire de Recherche en Informatique
3 LaHDAK - LRI - Données et Connaissances Massives et Hétérogènes (LRI)
4 GQE-Le Moulon - Génétique Quantitative et Evolution - Le Moulon (Génétique Végétale)
5 MIA-Paris - Mathématiques et Informatique Appliquées

In this paper, we introduce a new ontology BiPOm1. describing metabolic processes as interlocked subsystems while explicitly formalizing the active states of the involved molecules. We further showed that the annotation 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.

Keywords: Ontology; metabolic process

Domains: Computer Science [cs]; Computation and Language [cs.CL]; Computer Science [cs]; Machine Learning [cs.LG]

Vincent J. Henry, Fatiha Saïs, Elodie Marchadier, Juliette Dibie-Barthelemy, Anne Goelzer, et al.. BiPOm: Biological interlocked Process Ontology for metabolism. How to infer molecule knowledge from biological process?. International Conference on Biomedical Ontology, ICBO 2017, Sep 2017, Newcastle upon Tyne, United Kingdom. ⟨hal-01652924⟩