Profiling the baseline performance and limits of machine learning models for adaptive immune receptor repertoire classification

BACKGROUND: Machine learning (ML) methodology development for the classification of immune states in adaptive immune receptor repertoires (AIRRs) has seen a recent surge of interest. However, so far, there does not exist a systematic evaluation of scenarios where classical ML methods (such as penali...

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Detalles Bibliográficos
Autores principales: Kanduri, Chakravarthi, Pavlović, Milena, Scheffer, Lonneke, Motwani, Keshav, Chernigovskaya, Maria, Greiff, Victor, Sandve, Geir K
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9154052/
https://www.ncbi.nlm.nih.gov/pubmed/35639633
http://dx.doi.org/10.1093/gigascience/giac046

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9154052/
https://www.ncbi.nlm.nih.gov/pubmed/35639633
http://dx.doi.org/10.1093/gigascience/giac046

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