PREGO

PREGO combines text mining and data integration techniques to mine what-where-who associations among microorganisms, biological processes, and environment types from scientific literature and public omics repositories.

Key Features:

• Entity identification and ontology mapping: Microorganisms, biological processes, and environment types are identified and mapped to ontology terms from established community resources.
• Association extraction via co-mention and co-occurrence analysis: Analyses of co-mentions in text and co-occurrences in metagenomics data and metadata are performed to extract associations.
• Confidence scoring: A level of confidence is assigned to each association through a scoring scheme.
• Knowledge base content: The database contains associations for 364,508 microbial taxa, 1090 environmental types, 15,091 biological processes, and 7971 molecular functions with a total of almost 58 million associations.
• Data access: Associations are available through a web portal, an Application Programming Interface (API), and bulk download.

Scientific Applications:

• Experimental design and interpretation: PREGO assists researchers in design and interpretation of experiments and their results by exploring environments and/or processes associated with each other or with microbes.
• Meta-analysis of environmental microbiology studies: PREGO enables meta-analysis of experimental results, as demonstrated with a lagoon-sediment study of sulfur-cycle related microbes.

Methodology:

PREGO combines text mining and data integration techniques to mine associations from data and metadata scattered in the scientific literature and in public omics repositories.