Zobrazeno 1 - 10
of 83
pro vyhledávání: '"Tiangang Zhang"'
Publikováno v:
iScience, Vol 27, Iss 6, Pp 109571- (2024)
Summary: Identifying the side effects related to drugs is beneficial for reducing the risk of drug development failure and saving the drug development cost. We proposed a graph reasoning method, RKDSP, to fuse the semantics of multiple connection rel
Externí odkaz:
https://doaj.org/article/a4befb54bac147dbbca6596fbd7dcc1b
Publikováno v:
Frontiers in Energy Research, Vol 12 (2024)
The deployment of energy storage systems can play a role in peak and frequency regulation, solve the issue of limited flexibility in cleaner power systems in China, and ensure the stability and safety of the power grid. This paper presents a comprehe
Externí odkaz:
https://doaj.org/article/9332e243fa554f7b91e2046d0aa87359
Publikováno v:
iScience, Vol 27, Iss 2, Pp 108639- (2024)
Summary: Inferring the latent disease-related miRNAs is helpful for providing a deep insight into observing the disease pathogenesis. We propose a method, CMMDA, to encode and integrate the context relationship among multiple heterogeneous networks,
Externí odkaz:
https://doaj.org/article/7092e623f1c54018a46f206e82898a22
Publikováno v:
Journal of Materials Research and Technology, Vol 24, Iss , Pp 6923-6941 (2023)
A novel cold metal transfer and pulse (CMT-P) hybrid arc technology was introduced for additive manufacturing of high-strength aluminum alloy 2024 (AA2024). The effects of process parameters, namely the wire-feed speed, travel speed, and CMT/P ratio
Externí odkaz:
https://doaj.org/article/b961e3ebe37f48458d8e8d2bceb1618c
Publikováno v:
Actuators, Vol 13, Iss 1, p 23 (2024)
A thin-walled structure of high-strength aluminum alloy 2024 (AA2024) was fabricated using novel laser and cold metal transfer and pulse (CMT-P) arc hybrid additive manufacturing (LCAHAM) technology. The influence of the wire feeding speed, scanning
Externí odkaz:
https://doaj.org/article/9d9d69026f5447b8b44b1b761d2208d4
Publikováno v:
Frontiers in Pharmacology, Vol 14 (2023)
Background: Inferring drug-related side effects is beneficial for reducing drug development cost and time. Current computational prediction methods have concentrated on graph reasoning over heterogeneous graphs comprising the drug and side effect nod
Externí odkaz:
https://doaj.org/article/f314529ae8b54209b8807b6de17cc72b
Publikováno v:
Molecules, Vol 28, Iss 18, p 6544 (2023)
Since side-effects of drugs are one of the primary reasons for their failure in clinical trials, predicting their side-effects can help reduce drug development costs. We proposed a method based on heterogeneous graph transformer and capsule networks
Externí odkaz:
https://doaj.org/article/51f1e1a47eb9431cbd7fd644d416b5e1
Publikováno v:
BMC Bioinformatics, Vol 21, Iss 1, Pp 1-16 (2020)
Abstract Background Inferring diseases related to the patient’s electronic medical records (EMRs) is of great significance for assisting doctor diagnosis. Several recent prediction methods have shown that deep learning-based methods can learn the d
Externí odkaz:
https://doaj.org/article/2fd8f9ef37c94a9f9e0383e52ed7e2b3
Publikováno v:
International Journal of Molecular Sciences, Vol 23, Iss 7, p 3870 (2022)
Identifying new disease indications for existing drugs can help facilitate drug development and reduce development cost. The previous drug–disease association prediction methods focused on data about drugs and diseases from multiple sources. Howeve
Externí odkaz:
https://doaj.org/article/cb4d0bf2624742939f94788178309b24
Publikováno v:
Frontiers in Pharmacology, Vol 10 (2019)
Identifying new treatments for existing drugs can help reduce drug development costs and explore novel indications of drugs. The prediction of associations between drugs and diseases is challenging because their similarities and relations are complic
Externí odkaz:
https://doaj.org/article/80a573a8c1a649a7b9ce5d5f3da3978d