An automated framework for evaluation of deep learning models for splice site predictions

Abstract A novel framework for the automated evaluation of various deep learning-based splice site detectors is presented. The framework eliminates time-consuming development and experimenting activities for different codebases, architectures, and configurations to obtain the best models for a given...

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Bibliographic Details
Main Authors: Amin Zabardast, Elif Güney Tamer, Yeşim Aydın Son, Arif Yılmaz
Format: Article
Language:English
Published: Nature Portfolio 2023-06-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-023-34795-4