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 …

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 …

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 …

Prediction of drug combinations by integrating molecular and pharmacological data

XM Zhao, M Iskar, G Zeller, M Kuhn… - PLoS computational …, 2011 - journals.plos.org
Combinatorial therapy is a promising strategy for combating complex disorders due to
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 …

Ensemble prediction of synergistic drug combinations incorporating biological, chemical, pharmacological, and network knowledge

P Ding, R Yin, J Luo, CK Kwoh - IEEE journal of biomedical and …, 2018 - ieeexplore.ieee.org
Combinatorial therapy may reduce drug side effects and improve drug efficacy, making
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 …

MatchMaker: a deep learning framework for drug synergy prediction

HI Kuru, O Tastan, AE Cicek - IEEE/ACM transactions on …, 2021 - ieeexplore.ieee.org
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 …

Artificial intelligence and machine learning methods in predicting anti-cancer drug combination effects

K Fan, L Cheng, L Li - Briefings in bioinformatics, 2021 - academic.oup.com
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 …

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 …