Hierarchical approach
收藏DataCite Commons2024-08-29 更新2024-09-03 收录
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https://figshare.com/articles/dataset/Hierarchical_approach/26131852
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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 hierarchical approach, including the non-NABP/NABP classification, DBP/RBP classification and SSB/DSB classification. Files in the folder 1-non-NABP-NABP are the pre-trained models to predict non-NABPs and NABPs, and files in the folder 2-DBP-RBP are the pre-trained models to predict DBPs and RBPs. Each folder contains the README.txt file, indicating the user note for each model. For the SSBs and DSBs prediction, see https://figshare.com/articles/software/Prediction_of_SSB_DSB/25927360.<br>
提供机构：
figshare
创建时间：
2024-08-29
