Machine learning methods, databases and tools for drug combination prediction
L Wu, Y Wen, D Leng, Q Zhang, C Dai… - Briefings in …, 2022 - academic.oup.com
Combination therapy has shown an obvious efficacy on complex diseases and can greatly
reduce the development of drug resistance. However, even with high-throughput screens …
reduce the development of drug resistance. However, even with high-throughput screens …
A machine learning method for drug combination prediction
J Li, XY Tong, LD Zhu, HY Zhang - Frontiers in genetics, 2020 - frontiersin.org
Drug combination is now a hot research topic in the pharmaceutical industry, but experiment-
based methodologies are extremely costly in time and money. Many computational methods …
based methodologies are extremely costly in time and money. Many computational methods …
A network embedding framework based on integrating multiplex network for drug combination prediction
L Yu, M Xia, Q An - Briefings in bioinformatics, 2022 - academic.oup.com
Drug combination is a sensible strategy for disease treatment because it improves the
treatment efficacy and reduces concomitant side effects. Due to the large number of possible …
treatment efficacy and reduces concomitant side effects. Due to the large number of possible …
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 …
[HTML][HTML] Systematic review of computational methods for drug combination prediction
W Kong, G Midena, Y Chen, P Athanasiadis… - Computational and …, 2022 - Elsevier
Synergistic effects between drugs are rare and highly context-dependent and patient-
specific. Hence, there is a need to develop novel approaches to stratify patients for optimal …
specific. Hence, there is a need to develop novel approaches to stratify patients for optimal …
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 …
Predictive approaches for drug combination discovery in cancer
SA Madani Tonekaboni, L Soltan Ghoraie… - Briefings in …, 2018 - academic.oup.com
Drug combinations have been proposed as a promising therapeutic strategy to overcome
drug resistance and improve efficacy of monotherapy regimens in cancer. This strategy aims …
drug resistance and improve efficacy of monotherapy regimens in cancer. This strategy aims …
MatchMaker: a deep learning framework for drug synergy prediction
Drug combination therapies have been a viable strategy for the treatment of complex
diseases such as cancer due to increased efficacy and reduced side effects. However …
diseases such as cancer due to increased efficacy and reduced side effects. However …
Artificial intelligence and machine learning methods in predicting anti-cancer drug combination effects
Drug combinations have exhibited promising therapeutic effects in treating cancer patients
with less toxicity and adverse side effects. However, it is infeasible to experimentally screen …
with less toxicity and adverse side effects. However, it is infeasible to experimentally screen …
An enhanced cascade-based deep forest model for drug combination prediction
W Lin, L Wu, Y Zhang, Y Wen, B Yan… - Briefings in …, 2022 - academic.oup.com
Combination therapy has shown an obvious curative effect on complex diseases, whereas
the search space of drug combinations is too large to be validated experimentally even with …
the search space of drug combinations is too large to be validated experimentally even with …