Machine learning framework for cost effective deep mutational scanning through targeted substitution profiling

Abstract Background Deep mutational scanning (DMS) provides comprehensive maps of protein variant effects but remains experimentally intensive. Machine learning (ML) approaches have the potential to reduce experimental burden of DMS by predicting the functional impact of substitutions from limited d...

Szczegółowa specyfikacja

Opis bibliograficzny

Główni autorzy:	Emily Morgan, Shaylyn Govender, Prashant Singh, Ian Goodfellow, Stephen C. Graham, Nigel T. Bishop, Özlem Tastan Bishop
Format:	Artigo
Język:	Inglês
Wydane:	BMC 2026-05-01
Seria:	BMC Bioinformatics
Hasła przedmiotowe:	Brute-force approach Deep mutational scanning Random Forest Support vector machine Zero-shot prediction
Dostęp online:	https://doi.org/10.1186/s12859-026-06473-5
Etykiety:	Dodaj etykietę Nie ma etykietki, Dołącz pierwszą etykiete!