Current strategies to address data scarcity in artificial intelligence-based drug discovery: A comprehensive review
Artificial intelligence (AI) has played a vital role in computer-aided drug design (CADD). This
development has been further accelerated with the increasing use of machine learning (ML) …
development has been further accelerated with the increasing use of machine learning (ML) …
Application of artificial intelligence in drug design: A review
Artificial intelligence (AI) is a field of computer science that involves acquiring information,
developing rule bases, and mimicking human behaviour. The fundamental concept behind …
developing rule bases, and mimicking human behaviour. The fundamental concept behind …
A graph neural network approach for predicting drug susceptibility in the human microbiome
Recent studies have illuminated the critical role of the human microbiome in maintaining
health and influencing the pharmacological responses of drugs. Clinical trials …
health and influencing the pharmacological responses of drugs. Clinical trials …
Large Language Model-Based Natural Language Encoding Could Be All You Need for Drug Biomedical Association Prediction
Analyzing drug-related interactions in the field of biomedicine has been a critical aspect of
drug discovery and development. While various artificial intelligence (AI)-based tools have …
drug discovery and development. While various artificial intelligence (AI)-based tools have …
RLSynC: Offline–Online Reinforcement Learning for Synthon Completion
Retrosynthesis is the process of determining the set of reactant molecules that can react to
form a desired product. Semitemplate-based retrosynthesis methods, which imitate the …
form a desired product. Semitemplate-based retrosynthesis methods, which imitate the …
Bioactive compounds from Ocimum tenuiflorum and Poria cocos: A novel natural Compound for insomnia treatment based on A computational approach
Insomnia, a widespread public health issue, is associated with substantial distress and
daytime functionality impairments and can predispose to depression and cardiovascular …
daytime functionality impairments and can predispose to depression and cardiovascular …
[HTML][HTML] DeLA-DrugSelf: Empowering multi-objective de novo design through SELFIES molecular representation
In this paper, we introduce DeLA-DrugSelf, an upgraded version of DeLA-Drug [J. Chem. Inf.
Model. 62 (2022) 1411–1424], which incorporates essential advancements for automated …
Model. 62 (2022) 1411–1424], which incorporates essential advancements for automated …
ERT-GFAN: A multimodal drug–target interaction prediction model based on molecular biology and knowledge-enhanced attention mechanism
X Cheng, X Yang, Y Guan, Y Feng - Computers in Biology and Medicine, 2024 - Elsevier
In drug discovery, precisely identifying drug–target interactions is crucial for finding new
drugs and understanding drug mechanisms. Evolving drug/target heterogeneous data …
drugs and understanding drug mechanisms. Evolving drug/target heterogeneous data …
Predicting Clinical Anticancer Drug Response of Patients by using Domain Alignment and Prototypical Learning
W Peng, C Chen, W Dai, N Yu… - IEEE Journal of …, 2024 - ieeexplore.ieee.org
Anticancer drug response prediction is crucial in developing personalized treatment plans
for cancer patients. However, High-quality patient anticancer drug response data are scarce …
for cancer patients. However, High-quality patient anticancer drug response data are scarce …
A graph neural network approach for predicting drug susceptibility in the human microbiome
Recent studies have illuminated the critical role of the human microbiome in maintaining
health and influencing the pharmacological responses of drugs. Clinical trials …
health and influencing the pharmacological responses of drugs. Clinical trials …