BiPOm: a rule-based ontology to represent and infer molecule knowledge from a biological process-centered viewpoint

Vincent Henry,Fatiha Saïs,Juliette Dibie,Elodie Marchadier,Vincent Fromion,Olivier Inizan,Anne Goelzer

doi:10.1186/s12859-020-03637-9

Abstract

BackgroundManaging and organizing biological knowledge remains a major challenge, due to the complexity of living systems. Recently, systemic representations have been promising in tackling such a challenge at the whole-cell scale. In such representations, the cell is considered as a system composed of interlocked subsystems. The need is now to define a relevant formalization of the systemic description of cellular processes.ResultsWe introduce BiPOm (Biological interlocked Process Ontology for metabolism) an ontology to represent metabolic processes as interlocked subsystems using a limited number 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. We further showed that the information of molecules such as molecular types or molecular properties can be deduced by automatic reasoning using logical rules. The information necessary to populate BiPOm can be extracted from existing databases or existing bio-ontologies.ConclusionBiPOm provides a formal rule-based knowledge representation to relate all cellular components together by considering the cellular system as a whole. It relies on a paradigm shift where the anchorage of knowledge is rerouted from the molecule to the biological process.AvailabilityBiPOm can be downloaded at https://github.com/SysBioInra/SysOnto

Highlights

Managing and organizing biological knowledge remains a major challenge, due to the complexity of living systems
The question remains if information anchored on processes could really be used to formally describe process’ participants. Based on this previous work, we present in this article BiPOm (Biological interlocked Process Ontology for metabolism), a concise and expressive OWL-DL (Web Ontology Language) [21] ontology dedicated to the representation of metabolic processes
BiPOm overview This work seeks to show the substantial benefits of using a concise and highly expressive ontological model to describe metabolic processes using only few knowledge of molecules

Summary

Introduction

Managing and organizing biological knowledge remains a major challenge, due to the complexity of living systems. Systemic representations have been promising in tackling such a challenge at the whole-cell scale. In such representations, the cell is considered as a system composed of interlocked subsystems. Managing and organizing biological data and knowledge have remained a major challenge for decades, mainly due to the high complexity of living systems. The data associated to these experiments is growing in many application domains (e.g., plant biology, molecular biology, e-health) yielding to a bottleneck from data generation to their efficient management and the extraction of new valuable knowledge. Recent developments in single-cell technologies should further accentuate this general dynamic [4]

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