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PREGO: A Literature and Data-Mining Resource to Associate Microorganisms, Biological Processes, and Environment Types
Haris Zafeiropoulos1,2, Savvas Paragkamian1,2, Stelios Ninidakis2
1Department of Biology, University of Crete, Voutes University Campus, P.O. Box 2208, 70013 Heraklion, Crete, Greece.
Microorganisms
|February 25, 2022
Summary
PREGO is a new knowledge base linking microbes to their environments and biological processes. It uses text mining and data integration to map microbial functions for ecosystem research.
Area of Science:
- Microbiology
- Ecology
- Bioinformatics
Background:
- Understanding ecosystem functioning requires identifying microbial roles in specific environments.
- Current knowledge is fragmented across literature and public omics data.
Purpose of the Study:
- To develop PREGO, a comprehensive knowledge base of microbe-environment-process associations.
- To facilitate research by providing accessible and integrated data on microbial functions.
Main Methods:
- Combined text mining and data integration of scientific literature and public omics repositories.
- Utilized ontology mapping for microorganisms, processes, and environments.
- Employed comention and co-occurrence analyses with a scoring scheme for association confidence.
Main Results:
- PREGO contains 58 million associations linking 364,508 microbial taxa, 1090 environments, and 15,091 processes.
- Data is accessible via a web portal, API, and bulk download.
- Demonstrated utility through a meta-analysis of lagoon sediment microbial communities.
Conclusions:
- PREGO serves as a valuable resource for exploring and understanding microbial roles in ecosystems.
- The knowledge base aids researchers in experimental design and result interpretation.
- Facilitates a deeper understanding of microbial ecology and biogeochemical cycles.
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