Multi-class approach
收藏NIAID Data Ecosystem2026-05-02 收录
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https://figshare.com/articles/dataset/Multi-class_approach/26131864
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资源简介:
We tried different machine learning models (SVM, MLP, KNN, LR, RF), and features extracted by ESM2, to predict different types of nucleic acid binding proteins using multi-class approach. Files in the folder are the pre-trained models to predict non-NABPs, NABPs, SSBs and DSBs. The folder contains the README.txt file, indicating the user note for each model.
创建时间:
2024-08-29



