Unsupervised encoding selection through ensemble pruning for biomedical classification

Unsupervised encoding selection through ensemble pruning for biomedical classification

Abstract Background Owing to the rising levels of multi-resistant pathogens, antimicrobial peptides, an alternative strategy to classic antibiotics, got more attention. A crucial part is thereby the costly identification and validation. With the ever-growing amount of annotated peptides, researchers...

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Bibliographic Details
Main Authors: Sebastian Spänig, Alexander Michel, Dominik Heider
Format: Article
Language:English
Published: BMC 2023-03-01
Series:BioData Mining
Subjects:
Biomedical classification
Antimicrobial peptides
Encodings
Machine learning
Ensemble learning
Online Access:https://doi.org/10.1186/s13040-022-00317-7

Internet

https://doi.org/10.1186/s13040-022-00317-7

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