Ensemble prediction of synergistic drug combinations incorporating biological, chemical, pharmacological, and network knowledge
Combinatorial therapy may reduce drug side effects and improve drug efficacy, making
combination therapy a promising strategy to treat complex diseases. However, in the …
combination therapy a promising strategy to treat complex diseases. However, in the …
A drug combination prediction framework based on graph convolutional network and heterogeneous information
Combination therapy, which can improve therapeutic efficacy and reduce side effects, plays
an important role in the treatment of complex diseases. Yet, a large number of possible …
an important role in the treatment of complex diseases. Yet, a large number of possible …
MFSynDCP: multi-source feature collaborative interactive learning for drug combination synergy prediction
Y Dong, Y Chang, Y Wang, Q Han, X Wen, Z Yang… - BMC …, 2024 - Springer
Drug combination therapy is generally more effective than monotherapy in the field of cancer
treatment. However, screening for effective synergistic combinations from a wide range of …
treatment. However, screening for effective synergistic combinations from a wide range of …
Predicting synergistic anticancer drug combination based on low-rank global attention mechanism and bilinear predictor
Motivation Drug combination therapy has exhibited remarkable therapeutic efficacy and has
gradually become a promising clinical treatment strategy of complex diseases such as …
gradually become a promising clinical treatment strategy of complex diseases such as …
Biomolecular network‐based synergistic drug combination discovery
X Li, G Qin, Q Yang, L Chen… - BioMed research …, 2016 - Wiley Online Library
Drug combination is a powerful and promising approach for complex disease therapy such
as cancer and cardiovascular disease. However, the number of synergistic drug …
as cancer and cardiovascular disease. However, the number of synergistic drug …
AttenSyn: an attention-based deep graph neural network for anticancer synergistic drug combination prediction
Identifying synergistic drug combinations is fundamentally important to treat a variety of
complex diseases while avoiding severe adverse drug–drug interactions. Although several …
complex diseases while avoiding severe adverse drug–drug interactions. Although several …
Prediction of drug combinations by integrating molecular and pharmacological data
Combinatorial therapy is a promising strategy for combating complex disorders due to
improved efficacy and reduced side effects. However, screening new drug combinations …
improved efficacy and reduced side effects. However, screening new drug combinations …
EDST: a decision stump based ensemble algorithm for synergistic drug combination prediction
J Chen, L Wu, K Liu, Y Xu, S He, X Bo - BMC bioinformatics, 2023 - Springer
Introduction There are countless possibilities for drug combinations, which makes it
expensive and time-consuming to rely solely on clinical trials to determine the effects of each …
expensive and time-consuming to rely solely on clinical trials to determine the effects of each …
SNRMPACDC: computational model focused on Siamese network and random matrix projection for anticancer synergistic drug combination prediction
Synergistic drug combinations can improve the therapeutic effect and reduce the drug
dosage to avoid toxicity. In previous years, an in vitro approach was utilized to screen …
dosage to avoid toxicity. In previous years, an in vitro approach was utilized to screen …
Prediction of synergistic anti-cancer drug combinations based on drug target network and drug induced gene expression profiles
Objective Synergistic drug combinations are promising therapies for cancer treatment.
However, effective prediction of synergistic drug combinations is quite challenging as …
However, effective prediction of synergistic drug combinations is quite challenging as …