Results 11 to 20 of about 8,194,450 (255)

Associative learning mechanism for drug‐target interaction prediction

CAAI Transactions on Intelligence Technology, 2023
As a necessary process of modern drug development, finding a drug compound that can selectively bind to a specific protein is highly challenging and costly.
Zhiqin Zhu, Zheng Yao, Guanqiu Qi, Neal Mazur, Pan Yang, Baisen Cong   +5 more
doaj   +2 more sources

Application of Machine Learning for Drug–Target Interaction Prediction [PDF]

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

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

Ligand Binding Prediction Using Protein Structure Graphs and Residual Graph Attention Networks

Molecules, 2022
Computational prediction of ligand–target interactions is a crucial part of modern drug discovery as it helps to bypass high costs and labor demands of in vitro and in vivo screening.
Mohit Pandey, Mariia Radaeva, Hazem Mslati, Olivia Garland, Michael Fernandez, Martin Ester, Artem Cherkasov   +6 more
doaj   +1 more source

Allo-network drugs: Extension of the allosteric drug concept to protein-protein interaction and signaling networks [PDF]

, 2013
Allosteric drugs are usually more specific and have fewer side effects than orthosteric drugs targeting the same protein. Here, we overview the current knowledge on allosteric signal transmission from the network point of view, and show that most ...
Csermely, Péter, Nussinov, Ruth, Szilágyi, András   +2 more
core   +2 more sources

DeepDrug: A general graph‐based deep learning framework for drug‐drug interactions and drug‐target interactions prediction

Quantitative Biology, 2023
Computational methods for DDIs and DTIs prediction are essential for accelerating the drug discovery process. We proposed a novel deep learning method DeepDrug, to tackle these two problems within a unified framework.
Qijin Yin, Rui Fan, Xusheng Cao, Qiao Liu, Rui Jiang, Wanwen Zeng   +5 more
doaj   +1 more source

DTiGEMS+: drug-target interaction prediction using graph embedding, graph mining, and similarity-based techniques. [PDF]

, 2019
In silico prediction of drug-target interactions is a critical phase in the sustainable drug development process, especially when the research focus is to capitalize on the repositioning of existing drugs.
Olayan, Rawan S, Gao, Xin, Ashoor, Haitham, Thafar, Maha A., Albaradei, Somayah, Bajic, Vladimir B, Bajic, Vladimir B., Thafar, Maha A, Olayan, Rawan S., Gojobori, Takashi, Essack, Magbubah   +10 more
core   +1 more source

Machine Learning for Drug-Target Interaction Prediction

Molecules, 2018
Identifying drug-target interactions will greatly narrow down the scope of search of candidate medications, and thus can serve as the vital first step in drug discovery.
Ruolan Chen, Xiangrong Liu, Shuting Jin, Jiawei Lin, Juan Liu   +4 more
doaj   +1 more source

Identification of drug-target interaction by a random walk with restart method on an interactome network

BMC Bioinformatics, 2018
Background Identification of drug-target interactions acts as a key role in drug discovery. However, identifying drug-target interactions via in-vitro, in-vivo experiments are very laborious, time-consuming.
Ingoo Lee, Hojung Nam
doaj   +1 more source

Drug-target interaction prediction using semi-bipartite graph model and deep learning

BMC Bioinformatics, 2020
Background Identifying drug-target interaction is a key element in drug discovery. In silico prediction of drug-target interaction can speed up the process of identifying unknown interactions between drugs and target proteins.
Hafez Eslami Manoochehri, Mehrdad Nourani   +1 more
doaj   +1 more source