Graph representation learning in biomedicine and healthcare
Networks—or graphs—are universal descriptors of systems of interacting elements. In
biomedicine and healthcare, they can represent, for example, molecular interactions …
biomedicine and healthcare, they can represent, for example, molecular interactions …
[HTML][HTML] PD-L1 distribution and perspective for cancer immunotherapy—blockade, knockdown, or inhibition
Cancer immunotherapy involves blocking the interactions between the PD-1/PD-L1 immune
checkpoints with antibodies. This has shown unprecedented positive outcomes in clinics …
checkpoints with antibodies. This has shown unprecedented positive outcomes in clinics …
[HTML][HTML] NLLSS: predicting synergistic drug combinations based on semi-supervised learning
Fungal infection has become one of the leading causes of hospital-acquired infections with
high mortality rates. Furthermore, drug resistance is common for fungus-causing diseases …
high mortality rates. Furthermore, drug resistance is common for fungus-causing diseases …
Computational multitarget drug design
Designing drugs that can simultaneously interact with multiple targets is a promising
approach for treating complicated diseases. Compared to using combinations of single …
approach for treating complicated diseases. Compared to using combinations of single …
[HTML][HTML] Combinations of Plant Essential Oil Based Terpene Compounds as Larvicidal and Adulticidal Agent against Aedes aegypti (Diptera: Culicidae)
R Sarma, K Adhikari, S Mahanta, B Khanikor - Scientific reports, 2019 - nature.com
Insecticidal plant-based compound (s) in combinations may show synergistic or antagonistic
interactions against insect pest. Considering the rapid spread of the Aedes borne diseases …
interactions against insect pest. Considering the rapid spread of the Aedes borne diseases …
[HTML][HTML] Harnessing machine learning to find synergistic combinations for FDA-approved cancer drugs
Combination therapy is a fundamental strategy in cancer chemotherapy. It involves
administering two or more anti-cancer agents to increase efficacy and overcome multidrug …
administering two or more anti-cancer agents to increase efficacy and overcome multidrug …
Predicting cell line-specific synergistic drug combinations through a relational graph convolutional network with attention mechanism
Identifying synergistic drug combinations (SDCs) is a great challenge due to the
combinatorial complexity and the fact that SDC is cell line specific. The existing …
combinatorial complexity and the fact that SDC is cell line specific. The existing …
Potentiating antibiotics in drug-resistant clinical isolates via stimuli-activated superoxide generation
The rise of multidrug-resistant (MDR) bacteria is a growing concern to global health and is
exacerbated by the lack of new antibiotics. To treat already pervasive MDR infections, new …
exacerbated by the lack of new antibiotics. To treat already pervasive MDR infections, new …
[HTML][HTML] Systems biology approaches for advancing the discovery of effective drug combinations
KA Ryall, AC Tan - Journal of cheminformatics, 2015 - Springer
Complex diseases like cancer are regulated by large, interconnected networks with many
pathways affecting cell proliferation, invasion, and drug resistance. However, current cancer …
pathways affecting cell proliferation, invasion, and drug resistance. However, current cancer …
[HTML][HTML] A geometrical approach to control and controllability of nonlinear dynamical networks
In spite of the recent interest and advances in linear controllability of complex networks,
controlling nonlinear network dynamics remains an outstanding problem. Here we develop …
controlling nonlinear network dynamics remains an outstanding problem. Here we develop …