Comprehensive evaluation of CAZyme prediction tools in fungal and bacterial species

Hobbs, Emma and Gloster, Tracey and Chapman, Sean and Pritchard, Leighton (2021) Comprehensive evaluation of CAZyme prediction tools in fungal and bacterial species. In: Microbiology Society Annual Conference 2021, 2021-04-26 - 2021-04-30, Online. (https://doi.org/10.6084/m9.figshare.14370836.v1)

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Abstract

Carbohydrate Active enZymes (CAZymes) are pivotal in pathogen recognition, signalling, structure and energy metabolism. CAZy is the most comprehensive CAZyme database, cataloguing CAZymes into sequence-based CAZy families. The CAZyme prediction tools dbCAN [2], CUPP and eCAMI annotate CAZymes with CAZy families. However, these tools have not been independently evaluated on a common high-quality dataset. Additionally, previous evaluations did not evaluate the binary classification of CAZymes/non-CAZymes, and the multilabel classification of CAZymes to multiple CAZy families.

ORCID iDs

Hobbs, Emma, Gloster, Tracey, Chapman, Sean and Pritchard, Leighton ORCID logoORCID: https://orcid.org/0000-0002-8392-2822;