Evidence map›Paper›PMID 32703160›Full record

ArticleBMC bioinformatics2020

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

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

Abstract read
In one paragraph

Article in BMC bioinformatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. The Immunopeptidomics Ontology (ImPO).Database : the journal of biological databases and curation · 2024
    Article
  2. Article
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

7 authors.

Vincent HenryUniversité Paris-Saclay, INRAE, MaIAGE, Jouy-en-Josas, France.
Fatiha SaïsLRI, UMR 8623, CNRS, Université Paris-Sud, Université Paris Saclay, Orsay, France.
Olivier InizanUniversité Paris-Saclay, INRAE, MaIAGE, Jouy-en-Josas, France.
Elodie MarchadierUniversité Paris-Saclay, INRAE, CNRS, AgroParisTech, GQE-Le Moulon, Gif-sur-Yvette, 91190, France.
Juliette DibieUMR MIA-Paris, AgroParisTech, INRAE, Université Paris Saclay, Paris, France.
Anne GoelzerUniversité Paris-Saclay, INRAE, MaIAGE, Jouy-en-Josas, France. anne.goelzer@inrae.fr.ORCID http://orcid.org/0000-0003-2222-6142
Vincent FromionUniversité Paris-Saclay, INRAE, MaIAGE, Jouy-en-Josas, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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. AVAILABILITY: BiPOm can be downloaded at https://github.com/SysBioInra/SysOnto.

Indexed as

Biological OntologiesMetabolismDatabases, FactualEnzymesKnowledge BasesEnzymesLogical rulesMetabolic processesOntology

Identifiers

PMID32703160
PMCPMC7376860

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.