DeepB3Pred - code

DeepB3Pred uses the following dependencies:MATLAB2018a python 3.10 numpy scipy pandas scikit-learn catboost= 1.1.1 gc_forset xgboost-1.5.0 tensorflow=1.15.0 Keras=2.1.6Guiding principles:The data contains a training dataset and a testing dataset. The training dataset TR_BB.fasta includes BBB_pos and BBB_neg training samples. Testing dataset TS_BB includes BBB_pos and BBB_neg testing samplesFeature_Extraction: CPSR is the implementation of component protein sequence representation. MCTD is the implementation of composition-transition and distribution, and GSFE is the implementation of graphical and statistical-based feature engineering.Classifier: DeepB3Pred.py is the implementation of the proposed method to predict B3PPs and non-B3PPs.