Results 11 to 20 of about 2,729,950 (336)

Leveraging multimodal learning for enhanced drug-target interaction prediction [PDF]

Frontiers in Pharmacology
IntroductionThe evolving landscape of artificial intelligence in drug discovery necessitates increasingly sophisticated approaches to predict drug-target interactions (DTIs) with high precision and generalizability. In alignment with the current surge of
Guo Chen, Kaixin Sun
doaj   +2 more sources

Drug Target Interaction Prediction

International Journal of Advanced Research in Science, Communication and Technology
Drug–target interaction (DTI) prediction is vital to drug discovery, assisting in the identification of drug- target protein interactions more efficiently than usual methods of experimentation, which are frequently costly and time-consuming.
Ruby Sheikh, Dr. Soumyasri S M
semanticscholar   +2 more sources

A generative framework for enhancing drug target interaction prediction in drug discovery [PDF]

Scientific Reports
In silico drug-target interaction (DTI) prediction plays a key role in accelerating drug discovery and understanding molecular mechanisms. Traditional methods often struggle with the complexity and scale of biochemical data, thus limiting prediction ...
Roshan R. Kotkondawar, Sanjay R. Sutar, Arvind W. Kiwelekar, Vinod J. Kadam, Shivajirao M. Jadhav   +4 more
doaj   +2 more sources

Application of Machine Learning for Drug–Target Interaction Prediction

Frontiers in Genetics, 2021
Exploring drug–target interactions by biomedical experiments requires a lot of human, financial, and material resources. To save time and cost to meet the needs of the present generation, machine learning methods have been introduced into the prediction ...
Lei Xu, Xiaoqing Ru, Rong Song
doaj   +2 more sources

CCL-DTI: contributing the contrastive loss in drug–target interaction prediction

BMC Bioinformatics
Background The Drug–Target Interaction (DTI) prediction uses a drug molecule and a protein sequence as inputs to predict the binding affinity value. In recent years, deep learning-based models have gotten more attention.
Alireza Dehghan, Karim Abbasi, Parvin Razzaghi, Hossein Banadkuki, Sajjad Gharaghani   +4 more
doaj   +2 more sources

Neighborhood Regularized Logistic Matrix Factorization for Drug-Target Interaction Prediction. [PDF]

PLoS Computational Biology, 2016
In pharmaceutical sciences, a crucial step of the drug discovery process is the identification of drug-target interactions. However, only a small portion of the drug-target interactions have been experimentally validated, as the experimental validation ...
Yong Liu, Min Wu, Chunyan Miao, Peilin Zhao, Xiao-Li Li   +4 more
doaj   +2 more sources

DTI-LM: language model powered drug-target interaction prediction. [PDF]

Bioinformatics
Motivation The identification and understanding of drug–target interactions (DTIs) play a pivotal role in the drug discovery and development process. Sequence representations of drugs and proteins in computational model offer advantages such as their ...
Ahmed KT, Ansari MI, Zhang W.
europepmc   +2 more sources

Drug-target interaction prediction by integrating heterogeneous information with mutual attention network. [PDF]

BMC Bioinformatics
Identification of drug–target interactions is an indispensable part of drug discovery. While conventional shallow machine learning and recent deep learning methods based on chemogenomic properties of drugs and target proteins have pushed this prediction ...
Zhang Y, Wang Y, Wu C, Zhan L, Wang A, Cheng C, Zhao J, Zhang W, Chen J, Li P.   +9 more
europepmc   +2 more sources

Drug-Target Interaction Prediction Based on an Interactive Inference Network. [PDF]

Int J Mol Sci
Drug–target interactions underlie the actions of chemical substances in medicine. Moreover, drug repurposing can expand use profiles while reducing costs and development time by exploiting potential multi-functional pharmacological properties based upon additional target interactions.
Chen Y, Liang X, Du W, Liang Y, Wong G, Chen L.   +5 more
europepmc   +3 more sources

Mapping drug-target interaction networks [PDF]

2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2009
Molecular polypharmacological studies have gained more and more attention as they are important in predicting drug off-target properties and potential toxicity/side effect. The explosive growth of biomedical data provides us an opportunity to develop novel strategies to conduct such studies by analyzing molecular interaction networks. In this paper, we
Longzhang, Tian, Shuxing, Zhang
openaire   +2 more sources