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[HTML][HTML] Application of artificial intelligence and machine learning in early detection of adverse drug reactions (ADRs) and drug-induced toxicity
S Yang, S Kar - Artificial Intelligence Chemistry, 2023 - Elsevier
Adverse drug reactions (ADRs) and drug-induced toxicity are major challenges in drug
discovery, threatening patient safety and dramatically increasing healthcare expenditures …
discovery, threatening patient safety and dramatically increasing healthcare expenditures …
[HTML][HTML] A review of transformers in drug discovery and beyond
Transformer models have emerged as pivotal tools within the realm of drug discovery,
distinguished by their unique architectural features and exceptional performance in …
distinguished by their unique architectural features and exceptional performance in …
MRNDR: multihead attention-based recommendation network for drug repurposing
X Feng, Z Ma, C Yu, R ** new drugs is extremely expensive, whereas
drug repurposing represents a promising approach to augment the efficiency of new drug …
drug repurposing represents a promising approach to augment the efficiency of new drug …
Multiscale topology in interactomic network: from transcriptome to antiaddiction drug repurposing
The escalating drug addiction crisis in the United States underscores the urgent need for
innovative therapeutic strategies. This study embarked on an innovative and rigorous …
innovative therapeutic strategies. This study embarked on an innovative and rigorous …
Machine learning study of the extended drug–target interaction network informed by pain related voltage-gated sodium channels
Pain is a significant global health issue, and the current treatment options for pain
management have limitations in terms of effectiveness, side effects, and potential for …
management have limitations in terms of effectiveness, side effects, and potential for …
Multiscale differential geometry learning of networks with applications to single-cell RNA sequencing data
Single-cell RNA sequencing (scRNA-seq) has emerged as a transformative technology,
offering unparalleled insights into the intricate landscape of cellular diversity and gene …
offering unparalleled insights into the intricate landscape of cellular diversity and gene …
[HTML][HTML] IUPHAR review–Data-driven computational drug repurposing approaches for opioid use disorder
Abstract Opioid Use Disorder (OUD) is a chronic and relapsing condition characterized by
the misuse of opioid drugs, causing significant morbidity and mortality in the United States …
the misuse of opioid drugs, causing significant morbidity and mortality in the United States …
Develo** a SARS-CoV-2 main protease binding prediction random forest model for drug repurposing for COVID-19 treatment
The coronavirus disease 2019 (COVID-19) global pandemic resulted in millions of people
becoming infected with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) …
becoming infected with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) …
A critical assessment of bioactive compounds databases
DQ de Azevedo, BM Campioni… - Future Medicinal …, 2024 - Taylor & Francis
Compound databases (DBs) are essential tools for drug discovery. The number of DBs in
public domain is increasing, so it is important to analyze these DBs. In this article, the main …
public domain is increasing, so it is important to analyze these DBs. In this article, the main …
Multiobjective molecular optimization for opioid use disorder treatment using generative network complex
Opioid use disorder (OUD) has emerged as a significant global public health issue,
necessitating the discovery of new medications. In this study, we propose a deep generative …
necessitating the discovery of new medications. In this study, we propose a deep generative …