Author

Rebecca E. Colman

FINDORCID 0000-0002-6854-2100Unclaimed ORCID profile · follow to get notified of new preprints

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Organism:bacteria (other)· 1 Research Focus:benchmarking· 1 Research Focus:database / resource· 1 Approach:machine learning (classical)· 1 Research Focus:software / tool· 1 Approach:statistical model· 1

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Anita SureshiD· 1 shared Miguel Moreno-MolinaiD· 1 shared Timothy C. RodwelliD· 1 shared

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BioinformaticsbioRxivPreprintApr 25, 2025

Facilitating User Interaction with the Tuberculosis Mutation Catalogue using AI Tools

Miguel Moreno-Molina, Anita Suresh, Rebecca E. Colman, Timothy C. Rodwell

This paper evaluates AI models for interacting with a tuberculosis mutation catalogue, finding Google Gemini 2.5 Pro performs best in accuracy and reliability.

2 citations

bacteria (other)statistical model

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