[HTML][HTML] Revolutionizing medicinal chemistry: the application of artificial intelligence (AI) in early drug discovery
Artificial intelligence (AI) has permeated various sectors, including the pharmaceutical
industry and research, where it has been utilized to efficiently identify new chemical entities …
industry and research, where it has been utilized to efficiently identify new chemical entities …
DRESIS: the first comprehensive landscape of drug resistance information
X Sun, Y Zhang, H Li, Y Zhou, S Shi… - Nucleic acids …, 2023 - academic.oup.com
Widespread drug resistance has become the key issue in global healthcare. Extensive
efforts have been made to reveal not only diverse diseases experiencing drug resistance …
efforts have been made to reveal not only diverse diseases experiencing drug resistance …
Predicting miRNA–disease associations via learning multimodal networks and fusing mixed neighborhood information
Z Lou, Z Cheng, H Li, Z Teng, Y Liu… - Briefings in …, 2022 - academic.oup.com
Motivation In recent years, a large number of biological experiments have strongly shown
that miRNAs play an important role in understanding disease pathogenesis. The discovery …
that miRNAs play an important role in understanding disease pathogenesis. The discovery …
[HTML][HTML] AttentionMGT-DTA: A multi-modal drug-target affinity prediction using graph transformer and attention mechanism
The accurate prediction of drug-target affinity (DTA) is a crucial step in drug discovery and
design. Traditional experiments are very expensive and time-consuming. Recently, deep …
design. Traditional experiments are very expensive and time-consuming. Recently, deep …
Identification of drug-side effect association via restricted Boltzmann machines with penalized term
In the entire life cycle of drug development, the side effect is one of the major failure factors.
Severe side effects of drugs that go undetected until the post-marketing stage leads to …
Severe side effects of drugs that go undetected until the post-marketing stage leads to …
[HTML][HTML] AMDGT: Attention aware multi-modal fusion using a dual graph transformer for drug–disease associations prediction
Identification of new indications for existing drugs is crucial through the various stages of
drug discovery. Computational methods are valuable in establishing meaningful …
drug discovery. Computational methods are valuable in establishing meaningful …
A comparative analytical review on machine learning methods in Drugtarget interactions prediction
Z Nikraftar, MR Keyvanpour - Current Computer-Aided Drug …, 2023 - ingentaconnect.com
Background: Predicting drug-target interactions (DTIs) is an important topic of study in the
field of drug discovery and development. Since DTI prediction in vitro studies is very …
field of drug discovery and development. Since DTI prediction in vitro studies is very …
Identification of drug-side effect association via multi-view semi-supervised sparse model
The association between drugs and side effects encompasses information about approved
medications and their documented adverse drug reactions. Traditional experimental …
medications and their documented adverse drug reactions. Traditional experimental …
Predicting microbe–drug associations with structure-enhanced contrastive learning and self-paced negative sampling strategy
Motivation Predicting the associations between human microbes and drugs (MDAs) is one
critical step in drug development and precision medicine areas. Since discovering these …
critical step in drug development and precision medicine areas. Since discovering these …
[HTML][HTML] Structured sparse regularization based random vector functional link networks for DNA N4-methylcytosine sites prediction
As an epigenetic modification that plays an important role in modifying gene function and
controlling gene expression during cell development, DNA N4-methylcytosine (4mC) is still …
controlling gene expression during cell development, DNA N4-methylcytosine (4mC) is still …