Zobrazeno 1 - 10
of 24
pro vyhledávání: '"Naifeng Wen"'
Autor:
Mengdie Xu, Xinwei Zhao, Jingyu Wang, Wei Feng, Naifeng Wen, Chunyu Wang, Junjie Wang, Yun Liu, Lingling Zhao
Publikováno v:
Journal of Cheminformatics, Vol 15, Iss 1, Pp 1-12 (2023)
Abstract Drug combination therapies are promising clinical treatments for curing patients. However, efficiently identifying valid drug combinations remains challenging because the number of available drugs has increased rapidly. In this study, we pro
Externí odkaz:
https://doaj.org/article/a9e513e8ffaa487dad14dde48a5f1407
Publikováno v:
Journal of Cheminformatics, Vol 14, Iss 1, Pp 1-13 (2022)
Abstract Molecular property prediction (MPP) is vital in drug discovery and drug reposition. Deep learning-based MPP models capture molecular property-related features from various molecule representations. In this paper, we propose a molecule sequen
Externí odkaz:
https://doaj.org/article/00d73938472b4809924a25932179a43f
Publikováno v:
Journal of Marine Science and Engineering, Vol 11, Iss 12, p 2334 (2023)
This research introduces a two-stage deep reinforcement learning approach for the cooperative path planning of unmanned surface vehicles (USVs). The method is designed to address cooperative collision-avoidance path planning while adhering to the Int
Externí odkaz:
https://doaj.org/article/1e20208442bc4e4782848c33c9ef1bba
Publikováno v:
Journal of Marine Science and Engineering, Vol 11, Iss 12, p 2346 (2023)
This study introduces a method for formation control and obstacle avoidance for multiple unmanned surface vehicles (USVs) by combining an artificial potential field with the virtual structure method. The approach involves a leader–follower formatio
Externí odkaz:
https://doaj.org/article/44f5598339b34574a1e23293f1bc28fa
Publikováno v:
Journal of Cheminformatics, Vol 14, Iss 1, Pp 1-14 (2022)
Abstract Motivation Drug-target binding affinity (DTA) reflects the strength of the drug-target interaction; therefore, predicting the DTA can considerably benefit drug discovery by narrowing the search space and pruning drug-target (DT) pairs with l
Externí odkaz:
https://doaj.org/article/50d59d86d6294f7fbcab36b373594a22
Publikováno v:
Computational and Structural Biotechnology Journal, Vol 20, Iss , Pp 2831-2838 (2022)
The task of identifying protein–ligand interactions (PLIs) plays a prominent role in the field of drug discovery. However, it is infeasible to identify potential PLIs via costly and laborious in vitro experiments. There is a need to develop PLI com
Externí odkaz:
https://doaj.org/article/6b8a77aad28841b691d14b61b4b4ec04
Publikováno v:
International Journal of Advanced Robotic Systems, Vol 19 (2022)
The unstructured, dynamic marine environmental information and the cooperative obstacle avoidance problem greatly challenge the online path planner for unmanned surface vehicles. Efficiency and optimization are crucial for online path planning scheme
Externí odkaz:
https://doaj.org/article/ba133eb10e3e42028180a41cf9f72276
Publikováno v:
International Journal of Molecular Sciences, Vol 23, Iss 19, p 11136 (2022)
The prediction of the strengths of drug–target interactions, also called drug–target binding affinities (DTA), plays a fundamental role in facilitating drug discovery, where the goal is to find prospective drug candidates. With the increase in th
Externí odkaz:
https://doaj.org/article/a305ed674a394f4eabda4d03e9e6d032
Publikováno v:
International Journal of Advanced Robotic Systems, Vol 17 (2020)
The study is concerned with the problem of online planning low-cost cooperative paths; those are energy-efficient, easy-to-execute, and low collision probability for unmanned surface vehicles (USVs) based on the artificial vector field and environmen
Externí odkaz:
https://doaj.org/article/f0e9870c0c864618a8c5b8704b6afeb9
Publikováno v:
Chemical Science; 8/28/2024, Vol. 15 Issue 32, p12879-12888, 10p