AntiCVP-Deep: Identify anti-coronavirus peptides between different negative datasets based on self-attention and deep learning
###AntiCVP-Deep uses the following dependencies:
Python 3.7 numpy scipy scikit-learn pandas TensorFlow keras ###Guiding principles:
**The dataset file contains four categories datasets, which contain training dataset and independent test dataset.
**Feature extraction：
AAC.py is the implementation of AAC.
Auto_Matine.m is the implementation of AD.
CTriad.py is the implementation of implement CT.
CTDC.py, CTDD.py and CTDT.py are the implementation of CTD.
DPC.py is the implementation of DPC.
PAAC.py is the implementation of PAAC.
**K-Means SMOTE:
K-Means SMOTE.py is the implementation of K-Means SMOTE.
**Classifier:
AdaBoost.py is the implementation of Adaboost.
BiLSTM_DNN.py is the implementation of BiLSTM_DNN.
BISEF.py is the implementation of BISEF.
CNN.py is the implementation of CNN.
DNN.py is the implementation of DNN.
LSTM.py is the implementation of LSTM.
LightGBM.py is the implementation of LightGBM.
XGBoost.py is the implementation of XGBoost.