Malsite-Deep：Malsite-Deep：基于NearMiss-2策略的深度学习和多信息融合预测蛋白的丙二酸化位点

[{"title":"（ 31 个子文件 1.48MB ） Malsite-Deep：Malsite-Deep：基于NearMiss-2策略的深度学习和多信息融合预测蛋白的丙二酸化位点","children":[{"title":"Malsite-Deep-master","children":[{"title":"classifier","children":[{"title":"SVM.py <span style='color:#111;'> 4.40KB </span>","children":null,"spread":false},{"title":"GTB.py <span style='color:#111;'> 4.39KB </span>","children":null,"spread":false},{"title":"NB.py <span style='color:#111;'> 4.37KB </span>","children":null,"spread":false},{"title":"DNN.py <span style='color:#111;'> 4.63KB </span>","children":null,"spread":false},{"title":"GRUD.py <span style='color:#111;'> 2.93KB </span>","children":null,"spread":false},{"title":"LightGBM.py <span style='color:#111;'> 4.40KB </span>","children":null,"spread":false},{"title":"RF.py <span style='color:#111;'> 4.38KB </span>","children":null,"spread":false},{"title":"LSTM.py <span style='color:#111;'> 3.86KB </span>","children":null,"spread":false},{"title":"XGBoost.py <span style='color:#111;'> 4.37KB </span>","children":null,"spread":false},{"title":"GRU.py <span style='color:#111;'> 2.61KB </span>","children":null,"spread":false},{"title":"AdaBoost.py <span style='color:#111;'> 4.41KB </span>","children":null,"spread":false},{"title":"CNN.py <span style='color:#111;'> 3.86KB </span>","children":null,"spread":false}],"spread":false},{"title":"Readme.md <span style='color:#111;'> 1.40KB </span>","children":null,"spread":false},{"title":"feature_extraction","children":[{"title":"BE","children":[{"title":"be_extract_feature.m <span style='color:#111;'> 788B </span>","children":null,"spread":false},{"title":"exchange_matrix.m <span style='color:#111;'> 1.42KB </span>","children":null,"spread":false}],"spread":true},{"title":"EAAC","children":[{"title":"EAAC.py <span style='color:#111;'> 1.92KB </span>","children":null,"spread":false}],"spread":true},{"title":"PWAA","children":[{"title":"PWAA_CC.m <span style='color:#111;'> 2.15KB </span>","children":null,"spread":false},{"title":"PWAA_Y1.m <span style='color:#111;'> 256B </span>","children":null,"spread":false},{"title":"PWAA_demo.m <span style='color:#111;'> 1.99KB </span>","children":null,"spread":false}],"spread":true},{"title":"BLOUSUM62","children":[{"title":"BLOSUM62.py <span style='color:#111;'> 3.21KB </span>","children":null,"spread":false}],"spread":true},{"title":"EBGW","children":[{"title":"EBGW.m <span style='color:#111;'> 1.07KB </span>","children":null,"spread":false},{"title":"EBGW_DATA.m <span style='color:#111;'> 192B </span>","children":null,"spread":false}],"spread":true},{"title":"DC","children":[{"title":"DPC.py <span style='color:#111;'> 933B </span>","children":null,"spread":false}],"spread":true},{"title":"BPB","children":[{"title":"AAC.m <span style='color:#111;'> 375B </span>","children":null,"spread":false},{"title":"Bi_profile_bayes.m <span style='color:#111;'> 964B </span>","children":null,"spread":false}],"spread":true}],"spread":true},{"title":"NearMiss_2","children":[{"title":"NearMiss_2.py <span style='color:#111;'> 2.20KB </span>","children":null,"spread":false}],"spread":true},{"title":"datasets","children":[{"title":"Independent test Set4.txt <span style='color:#111;'> 74.18KB </span>","children":null,"spread":false},{"title":"Training data.txt <span style='color:#111;'> 3.25MB </span>","children":null,"spread":false},{"title":"Independent test Set3.txt <span style='color:#111;'> 278.03KB </span>","children":null,"spread":false},{"title":"Independent test Set1.txt <span style='color:#111;'> 774.58KB </span>","children":null,"spread":false},{"title":"Independent test Set2.txt <span style='color:#111;'> 178.24KB </span>","children":null,"spread":false}],"spread":true}],"spread":true}],"spread":true}]