Results 1 to 10 of about 74,950 (296)

OFDR Distributed Demodulation Optimization Algorithm Using Discrete-Time Analytic Signal Backscattered Rayleigh Spectrum [PDF]

Sensors
We propose a novel distributed demodulation optimization algorithm for optical frequency domain reflectometry (OFDR). This algorithm applies discrete-time analytic (DTA) signals to the Rayleigh backscattered signal (RBS) reconstruction.
Shuaipeng Wang, Haomao Wang, Zhiguo Zhang, Yifan Wang, Haichao Huang   +4 more
doaj   +2 more sources

DrugForm-DTA: Towards real-world drug-target binding affinity model [PDF]

Computational and Structural Biotechnology Journal
Drug-target affinity (DTA) prediction is a fundamental challenge in drug discovery. Computational methods for predicting DTA can greatly assist drug design by narrowing the search space and reducing the number of protein-ligand complexes with low ...
Ivan Khokhlov, Anna Tashchilova, Nikolai Bugaev-Makarovskiy, Olga Glushkova, Vladimir Yudin, Anton Keskinov, Sergey Yudin, Dmitry Svetlichnyy, Veronika Skvortsova   +8 more
doaj   +2 more sources

Structure-free drug–target affinity prediction using protein and molecule language models [PDF]

Journal of Cheminformatics
Accurate prediction of drug-target affinity (DTA) is crucial for advancing drug discovery and optimizing experimental processes. Traditional DTA models often rely on handcrafted features or structural data, which can limit their generalizability and ...
Amir Hallaji Bidgoli, Morteza Mahdavi, Hamed Malek   +2 more
doaj   +2 more sources

A multimodal DTA prediction method based on triple-view contrastive learning

Complex & Intelligent Systems
Drug-target affinity (DTA) prediction is a crucial step in drug discovery, facilitating the acceleration of lead compound screening and drug repurposing, significantly reducing costs and shortening new drug development timelines.
Xiaoxing Pang, Zhixian Liu, Qingfeng Chen, Wei Lan, Shunhan Yao, Jiahai Liang   +5 more
doaj   +2 more sources

A deep learning method for drug-target affinity prediction based on sequence interaction information mining [PDF]

PeerJ, 2023
Background A critical aspect of in silico drug discovery involves the prediction of drug-target affinity (DTA). Conducting wet lab experiments to determine affinity is both expensive and time-consuming, making it necessary to find alternative approaches.
Mingjian Jiang, Yunchang Shao, Yuanyuan Zhang, Wei Zhou, Shunpeng Pang   +4 more
doaj   +2 more sources

The Effect of Manganese on the Crystallisation Process, Microstructure and Selected Properties of Compacted Graphite iron [PDF]

Archives of Metallurgy and Materials, 2019
The paper presents the effect of manganese on the crystallization process, microstructure and selected properties: cast iron hardness as well as ferrite and pearlite microhardness. The compacted graphite was obtained by Inmold technology.
G. Gumienny, B. Kurowska, P. Just
doaj   +1 more source

Compatibility assessment of a temperature-controlled radiofrequency catheter with a novel electroanatomical mapping system

Frontiers in Cardiovascular Medicine, 2023
BackgroundThe novel DiamondTemp ablation system (DTA) and EnSiteX mapping System (EAM) are both CE-Marked and FDA approved medical devices. The DTA has been validated by its manufacturer only in combination with previous version of EnSite System—EnSite ...
Luigi Pannone, Ivan Eltsov, Ivan Eltsov, Robbert Ramak, David Cabrita, Paul De Letter, Gian-Battista Chierchia, Carlo de Asmundis   +7 more
doaj   +1 more source

Case-based knowledge formalization and reasoning method for digital terrain analysis – application to extracting drainage networks [PDF]

Hydrology and Earth System Sciences, 2016
Application of digital terrain analysis (DTA), which is typically a modeling process involving workflow building, relies heavily on DTA domain knowledge of the match between the algorithm (and its parameter settings) and the application context ...
C.-Z. Qin, X.-W. Wu, J.-C. Jiang, A.-X. Zhu   +3 more
doaj   +1 more source

Drug-target binding affinity prediction using message passing neural network and self supervised learning

BMC Genomics, 2023
Background Drug-target binding affinity (DTA) prediction is important for the rapid development of drug discovery. Compared to traditional methods, deep learning methods provide a new way for DTA prediction to achieve good performance without much ...
Leiming Xia, Lei Xu, Shourun Pan, Dongjiang Niu, Beiyi Zhang, Zhen Li   +5 more
doaj   +1 more source

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   +1 more source