The present and future of the Cancer Dependency Map
Despite tremendous progress in the past decade, the complex and heterogeneous nature of
cancer complicates efforts to identify new therapies and therapeutic combinations that …
cancer complicates efforts to identify new therapies and therapeutic combinations that …
The recent progress of deep-learning-based in silico prediction of drug combination
Highlights•In silico prediction of drug combination has become indispensable due to the
expensive cost of experiments.•Deep learning architectures used for drug combination …
expensive cost of experiments.•Deep learning architectures used for drug combination …
MGAE-DC: Predicting the synergistic effects of drug combinations through multi-channel graph autoencoders
P Zhang, S Tu - PLoS computational biology, 2023 - journals.plos.org
Accurate prediction of synergistic effects of drug combinations can reduce the experimental
costs for drug development and facilitate the discovery of novel efficacious combination …
costs for drug development and facilitate the discovery of novel efficacious combination …
Network-based drug repurposing identifies small molecule drugs as immune checkpoint inhibitors for endometrial cancer
F Ahmed, A Samantasinghar, W Ali, KH Choi - Molecular Diversity, 2024 - Springer
Endometrial cancer (EC) is the 6th most common cancer in women around the world. Alone
in the United States (US), 66,200 new cases and 13,030 deaths are expected to occur in …
in the United States (US), 66,200 new cases and 13,030 deaths are expected to occur in …
Prediction of cancer drug combinations based on multidrug learning and cancer expression information injection
S Ren, L Chen, H Hao, L Yu - Future Generation Computer Systems, 2024 - Elsevier
Compared with patients with common diseases, cancer patients usually have a more fragile
cellular microenvironment and more complex or varied complications. Therefore, to meet …
cellular microenvironment and more complex or varied complications. Therefore, to meet …
DDSBC: A Stacking Ensemble Classifier-Based Approach for Breast Cancer Drug-Pair Cell Synergy Prediction
Breast cancer (BC) ranks as a leading cause of mortality among women worldwide, with
incidence rates continuing to rise. The quest for effective treatments has led to the adoption …
incidence rates continuing to rise. The quest for effective treatments has led to the adoption …
piscesCSM: prediction of anticancer synergistic drug combinations
While drug combination therapies are of great importance, particularly in cancer treatment,
identifying novel synergistic drug combinations has been a challenging venture …
identifying novel synergistic drug combinations has been a challenging venture …
PermuteDDS: a permutable feature fusion network for drug-drug synergy prediction
X Zhao, J Xu, Y Shui, M Xu, J Hu, X Liu, K Che… - Journal of …, 2024 - Springer
Motivation Drug combination therapies have shown promise in clinical cancer treatments.
However, it is hard to experimentally identify all drug combinations for synergistic interaction …
However, it is hard to experimentally identify all drug combinations for synergistic interaction …
DELFOS—drug efficacy leveraging forked and specialized networks—benchmarking scRNA-seq data in multi-omics-based prediction of cancer sensitivity
Motivation Cancer is currently one of the most notorious diseases, with over 1 million deaths
in the European Union alone in 2022. As each tumor can be composed of diverse cell types …
in the European Union alone in 2022. As each tumor can be composed of diverse cell types …
[PDF][PDF] Sentiment Analysis of ChatGPT Tweets Using Transformer Algorithms
This study explores the application of the Transformer model in sentiment analysis of tweets
generated by ChatGPT. We used a Kaggle dataset consisting of 217,623 instances labeled …
generated by ChatGPT. We used a Kaggle dataset consisting of 217,623 instances labeled …