Zobrazeno 1 - 10
of 56
pro vyhledávání: '"Xiongwen Quan"'
Publikováno v:
Frontiers in Physiology, Vol 14 (2023)
Recent studies on medical image fusion based on deep learning have made remarkable progress, but the common and exclusive features of different modalities, especially their subsequent feature enhancement, are ignored. Since medical images of differen
Externí odkaz:
https://doaj.org/article/d350fcf91e3a4322aec90ceddfbfd3da
Publikováno v:
BMC Bioinformatics, Vol 22, Iss 1, Pp 1-20 (2021)
Abstract Background Numerous studies have demonstrated that long non-coding RNAs are related to plenty of human diseases. Therefore, it is crucial to predict potential lncRNA-disease associations for disease prognosis, diagnosis and therapy. Dozens o
Externí odkaz:
https://doaj.org/article/72ad98df44fe4290a6cad979e2e7ef42
Publikováno v:
Frontiers in Genetics, Vol 13 (2022)
Background Classification and annotation of enzyme proteins are fundamental for enzyme research on biological metabolism. Enzyme Commission (EC) numbers provide a standard for hierarchical enzyme class prediction, on which several computational metho
Externí odkaz:
https://doaj.org/article/0b91ce8687954b83901975272cedc6d5
Publikováno v:
BMC Bioinformatics, Vol 20, Iss S16, Pp 1-11 (2019)
Abstract Background Predicting disease-related genes is helpful for understanding the disease pathology and the molecular mechanisms during the disease progression. However, traditional methods are not suitable for screening genes related to the dise
Externí odkaz:
https://doaj.org/article/21bdf38c35494691be22f286bc4ad6fb
Publikováno v:
BMC Bioinformatics, Vol 20, Iss 1, Pp 1-10 (2019)
Abstract Background Antibiotic resistance has become an increasingly serious problem in the past decades. As an alternative choice, antimicrobial peptides (AMPs) have attracted lots of attention. To identify new AMPs, machine learning methods have be
Externí odkaz:
https://doaj.org/article/37b5b697b7e641af9b62dac818147e08
Publikováno v:
International Journal of Molecular Sciences, Vol 23, Iss 9, p 4699 (2022)
Motif occupancy identification is a binary classification task predicting the binding of DNA motif instances to transcription factors, for which several sequence-based methods have been proposed. However, through direct training, these end-to-end met
Externí odkaz:
https://doaj.org/article/4bba3cc1c2ab49f1a74834d3544305da
Publikováno v:
Frontiers in Genetics, Vol 10 (2019)
Gene expression profiling has been widely used to characterize cell status to reflect the health of the body, to diagnose genetic diseases, etc. In recent years, although the cost of genome-wide expression profiling is gradually decreasing, the cost
Externí odkaz:
https://doaj.org/article/91ed7f17ad654b099dd0b8ee8f328935
Publikováno v:
BMC Bioinformatics, Vol 18, Iss 1, Pp 1-13 (2017)
Abstract Background Predicting disease-associated genes is helpful for understanding the molecular mechanisms during the disease progression. Since the pathological mechanisms of neurodegenerative diseases are very complex, traditional statistic-base
Externí odkaz:
https://doaj.org/article/458282cf3dc14b01bfacaf02ea769fa8
Publikováno v:
PLoS ONE, Vol 12, Iss 5, p e0178006 (2017)
Detecting disease-related gene modules by analyzing gene expression data is of great significance. It is helpful for exploratory analysis of the interaction mechanisms of genes under complex disease phenotypes. The multi-label propagation algorithm (
Externí odkaz:
https://doaj.org/article/4097a8b7edec437cbef5796a63ceb54b
Publikováno v:
IEEE Transactions on Instrumentation and Measurement. 71:1-17