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Updated Protocol for the Assembly and Use of the Minibioreactor Array (MBRA)
Published on: September 5, 2025
Modeling a microbial community and biodiversity assay with OBO Foundry ontologies: the interoperability gains of a
Philippe Rocca-Serra1, Ramona Walls2, Jacob Parnell2
1Oxford e-Research Centre, University of Oxford, OX1 3QG, Oxford, UK, The iPlant Collaborative, University of Arizona, Thomas J. Keating Bioresearch Building, 1657 East Helen St., Tucson, AZ 85721, USA, NEON, Inc. 1685 38th St., Ste. 100, Boulder, CO 80301, USA, University of Arizona, 1311 E. 4th St. Tucson, AZ 85721, USA and Department of Genetics and Institute of Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA philippe.rocca-serra@oerc.ox.ac.uk.
Abstract:
The advent of affordable sequencing technology provides for a new generation of explorers who probe the world's microbial diversity. Projects such as Tara Oceans, Moorea Biocode Project and Gut Microbiome rely on sequencing technologies to probe community diversity. Either targeted gene surveys (also known as community surveys) or complete metagenomes are evaluated. The former, being the less costly of the two methods, relies on the identification of specific genomic regions, which can be used as a proxy to estimate genetic distance between related species in a Phylum. For instance, 16 S ribosomal RNA gene surveys are used to probe bacterial communities while internal transcribed spacer surveys, for example, can be used for probing fungal communities. With the explosion of projects and frenzy to explore new domains of life, scientists in the field have issued guidelines to report minimal information (following a checklist), ensuring that information is contextualized in a meaningful way. Yet the semantics of a checklist are not explicit. We demonstrate here how a tabular template can be used to collect information on microbial diversity using an explicit representation in the Resource Description Framework that is consistent with community agreed-upon knowledge representation patterns found in the Ontology for Biomedical Investigations.
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