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Comprehensive evaluation of CAZyme prediction tools in fungal and bacterial species

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P361_comprehensive_evaluation_cazyme_prediction_EH_v2.pdf (1.000Mb)
Date
26/04/2021
Author
Hobbs, Emma Elizabeth Mary
Gloster, Tracey
Chapman, Sean
Pritchard, Leighton
Keywords
CAZymes
dbCAN
CUPP
eCAMI
CAZyme prediction
CAZy
QR Microbiology
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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, 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.
Citation
Hobbs , E E M , Gloster , T , Chapman , S & Pritchard , L 2021 , ' Comprehensive evaluation of CAZyme prediction tools in fungal and bacterial species ' , Microbiology Society Annual Conference , 26/04/21 - 30/04/21 .
 
conference
 
Status
Non peer reviewed
Type
Conference poster
Rights
Copyright © 2021 The Authors.
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  • University of St Andrews Research
URL
https://doi.org/10.6084/m9.figshare.14370836.v3
URI
http://hdl.handle.net/10023/24612

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