CAFA-evaluator: a Python tool for benchmarking ontological classification methods.
Journal
Bioinformatics advances
ISSN: 2635-0041
Titre abrégé: Bioinform Adv
Pays: England
ID NLM: 9918282081306676
Informations de publication
Date de publication:
2024
2024
Historique:
received:
20
11
2023
revised:
02
02
2024
accepted:
12
03
2024
medline:
28
3
2024
pubmed:
28
3
2024
entrez:
28
3
2024
Statut:
epublish
Résumé
We present CAFA-evaluator, a powerful Python program designed to evaluate the performance of prediction methods on targets with hierarchical concept dependencies. It generalizes multi-label evaluation to modern ontologies where the prediction targets are drawn from a directed acyclic graph and achieves high efficiency by leveraging matrix computation and topological sorting. The program requirements include a small number of standard Python libraries, making CAFA-evaluator easy to maintain. The code replicates the Critical Assessment of protein Function Annotation (CAFA) benchmarking, which evaluates predictions of the consistent subgraphs in Gene Ontology. Owing to its reliability and accuracy, the organizers have selected CAFA-evaluator as the official CAFA evaluation software. https://pypi.org/project/cafaeval.
Identifiants
pubmed: 38545087
doi: 10.1093/bioadv/vbae043
pii: vbae043
pmc: PMC10965419
doi:
Types de publication
Journal Article
Langues
eng
Pagination
vbae043Informations de copyright
© The Author(s) 2024. Published by Oxford University Press.
Déclaration de conflit d'intérêts
None declared.