Zobrazeno 1 - 10
of 326
pro vyhledávání: '"Maozu Guo"'
Publikováno v:
Fundamental Research, Vol 4, Iss 4, Pp 761-769 (2024)
The genome-wide association study (GWAS) aims to detect associations between individual single nucleotide polymorphisms (SNPs) or SNP interactions and phenotypes to decipher the genetic mechanism. Existing GWAS analysis tools have different focuses a
Externí odkaz:
https://doaj.org/article/895bc0908a4542acbc0391ba653168e7
Publikováno v:
BMC Bioinformatics, Vol 25, Iss 1, Pp 1-19 (2024)
Abstract Background Molecular biology is crucial for drug discovery, protein design, and human health. Due to the vastness of the drug-like chemical space, depending on biomedical experts to manually design molecules is exceedingly expensive. Utilizi
Externí odkaz:
https://doaj.org/article/bae72ea5a1a5458ca683b6e2fa0e2b8c
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-16 (2024)
Abstract Predicting the interaction affinity between drugs and target proteins is crucial for rapid and accurate drug discovery and repositioning. Therefore, more accurate prediction of DTA has become a key area of research in the field of drug disco
Externí odkaz:
https://doaj.org/article/427ec61495714493b57a19cd887d29df
Publikováno v:
IEEE Access, Vol 12, Pp 113463-113473 (2024)
Discovering potential drug-target interactions is crucial for advancing pharmacology. In recent years, the development of large-scale DTI datasets has propelled advancements in DTI prediction computational methods. Various deep learning approaches fo
Externí odkaz:
https://doaj.org/article/ca4339004f034271bedb1229b6f06c2a
Publikováno v:
IEEE Access, Vol 12, Pp 33792-33802 (2024)
This paper proposes a Bayesian neural network method for predicting equipment operational trends based on a channel attention mechanism. Traditional time series prediction methods have limitations in handling complex data and nonlinear relationships.
Externí odkaz:
https://doaj.org/article/997c7fc91e814fe0aae8794ed2d81b6c
Publikováno v:
Sensors, Vol 24, Iss 11, p 3268 (2024)
Structural health monitoring for roads is an important task that supports inspection of transportation infrastructure. This paper explores deep learning techniques for crack detection in road images and proposes an automatic pixel-level semantic road
Externí odkaz:
https://doaj.org/article/f6f519915569421f96d53f6f943cdfa4
Publikováno v:
BMC Bioinformatics, Vol 24, Iss 1, Pp 1-18 (2023)
Abstract Motivation Gene regulatory networks (GRNs) arise from the intricate interactions between transcription factors (TFs) and their target genes during the growth and development of organisms. The inference of GRNs can unveil the underlying gene
Externí odkaz:
https://doaj.org/article/f99314718a134d58bd0be0d3aa22f792
Publikováno v:
IEEE Access, Vol 11, Pp 127422-127430 (2023)
Joint biomedical entity and relation extraction is essential in biomedical text mining. It automatically identifies entities and uncovers the relation between them from biomedical texts. However, due to the relatively complex semantics of biomedical
Externí odkaz:
https://doaj.org/article/2ce0e5c51e2b41d9be76a2f8ffb70bb8
Publikováno v:
Applied Sciences, Vol 13, Iss 18, p 10055 (2023)
Biomedical texts are relatively obscure in describing relations between specialized entities, and the automatic extraction of drug–drug or drug–disease relations from massive biomedical texts presents a challenge faced by many researchers. To thi
Externí odkaz:
https://doaj.org/article/5ece988949f44ac28f8a177a74610021
Publikováno v:
Sensors, Vol 23, Iss 13, p 5819 (2023)
Accurate equipment operation trend prediction plays an important role in ensuring the safe operation of equipment and reducing maintenance costs. Therefore, monitoring the equipment vibration and predicting the time series of the vibration trend is o
Externí odkaz:
https://doaj.org/article/1861fc7cedee4c82b3966ddf9110b6db