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Artikel 1 Chemical toxicity prediction based on semi-supervised learning and graph convolutional neural network
Enthalten in Journal of cheminformatics Bd. 13, 27.11.2021, Nr. 1, date:12.2021: 1-16
Online Ressource
Artikel 2 Correction to: Diagnosis of schizophrenia with functional connectome data: a graph-based convolutional neural network approach
Enthalten in BMC neuroscience Bd. 23, 14.3.2022, Nr. 1, date:12.2022: 1
Online Ressource
Artikel 3 DeepPN: a deep parallel neural network based on convolutional neural network and graph convolutional network for predicting RNA-protein binding sites
Enthalten in BMC bioinformatics Bd. 23, 29.6.2022, Nr. 1, date:12.2022: 1-16
Online Ressource
Artikel 4 Detecting large-scale underwater cracks based on remote operated vehicle and graph convolutional neural network
Enthalten in Frontiers of structural and civil engineering Bd. 16, 5.12.2022, Nr. 11, date:11.2022: 1378-1396
Online Ressource
Artikel 5 Diagnosis of schizophrenia with functional connectome data: a graph-based convolutional neural network approach
Enthalten in BMC neuroscience Bd. 23, 17.1.2022, Nr. 1, date:12.2022: 1-11
Online Ressource
Artikel 6 Essential genes identification model based on sequence feature map and graph convolutional neural network
Enthalten in BMC genomics Bd. 25, 10.1.2024, Nr. 1, date:12.2024: 1-14
Online Ressource
Artikel 7 PCP-GC-LM: single-sequence-based protein contact prediction using dual graph convolutional neural network and convolutional neural network
Enthalten in BMC bioinformatics Bd. 25, 2.9.2024, Nr. 1, date:12.2024: 1-21
Online Ressource
Artikel 8 Prediction of the water solubility by a graph convolutional-based neural network on a highly curated dataset
Enthalten in Journal of cheminformatics Bd. 17, 21.4.2025, Nr. 1, date:12.2025: 1-13
Online Ressource
Artikel 9 Schizophrenia recognition based on three-dimensional adaptive graph convolutional neural network
Enthalten in Scientific reports Bd. 15, 3.2.2025, Nr. 1, date:12.2025: 1-11
Online Ressource
Artikel 10 Vulnerability detection in Java source code using a quantum convolutional neural network with self-attentive pooling, deep sequence, and graph-based hybrid feature extraction
Enthalten in Scientific reports Bd. 14, 28.3.2024, Nr. 1, date:12.2024: 1-17
Online Ressource


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