Table 2.

ML and DL methods with source code applied in the drug study at the bulk level.

Method	Platform	Functions	Source code
HNMDRP [45]	M,R	Drug response	https://github.com/USTC-HIlab/HNMDRP
Dr.VAE [52]	P	Drug response	https://github.com/rampasek/DrVAE
BMTMKL [44]	M,R	Drug response	https://github.com/mehmetgonen/bmtmkl
RefDNN [48]	P	Drug response	https://github.com/mathcom/RefDNN
DCell [47]	J,P	Drug response	https://github.com/idekerlab/DCell
tCNNs [49]	P	Drug response	https://github.com/Lowpassfilter/tCNNS-Project
MOLI [46]	P	Drug response	https://github.com/hosseinshn/MOLI
DeepCDR [51]	P	Drug response	https://github.com/kimmo1019/DeepCDR
GraphDRP [50]	P	Drug response	https://github.com/hauldhut/GraphDRP/
scDEAL [127]	P	Drug response	https://github.com/OSU-BMBL/scDEAL
DeepChem [42]	P	Drug discovery	https://github.com/deepchem/deepchem
DeepDRK [38]	R	Drug discovery	https://github.com/wangyc82/DeepDRK
deepDR [40]	P,M	Drug discovery	https://github.com/ChengF-Lab/deepDR
DeepDTIs [53]	P	DTI	https://github.com/Bjoux2/DeepDTIs_DBN
DeepCPI [54]	P	DTI	https://github.com/FangpingWan/DeepCPI
DeepDTnet [62]	P	DTI	https://github.com/ChengF-Lab/deepDTnet
DeepConv-DTI [56]	P	DTI	https://github.com/GIST-CSBL/DeepConv-DTI
DeepPurpose [55]	P	DTI	https://github.com/kexinhuang12345/DeepPurpose
DEEPScreen [57]	P	DTI	https://github.com/cansyl/DEEPScreen
DeepAffinity [59]	P	DTI	https://github.com/Shen-Lab/DeepAffinity
Deep-AmPEP30 [60]	P	DTI	https://cbbio.cis.um.edu.mo/AxPEP/
DeepSynergy [61]	P	DDI	https://github.com/KristinaPreuer/DeepSynergy
Decagon [63]	P	DDI	https://github.com/mims-harvard/decagon
KRL [39]	P	Other	https://github.com/BorgwardtLab/Kernelized-Rank-Learning
DeepMACT [37]	P	Other	http://discotechnologies.org/DeepMACT/
RACS [36]	R	Other	https://github.com/DrugCombination/RACS
Yu [41]	P	Other	https://github.com/tzuhuiyuatntu/cnsstudy2019

M, Matlab; P, Python; J, Java; DTI, drug–target interactions; DDI, drug–drug interactions.