DTI-HeNE: a novel method for drug-target interaction prediction based on heterogeneous network embedding
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
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1471-2105
- Extent
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Online-Ressource
- Language
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Englisch
- Notes
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online resource.
- Bibliographic citation
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DTI-HeNE: a novel method for drug-target interaction prediction based on heterogeneous network embedding ; volume:22 ; number:1 ; day:3 ; month:9 ; year:2021 ; pages:1-20 ; date:12.2021
BMC bioinformatics ; 22, Heft 1 (3.9.2021), 1-20, 12.2021
- Creator
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Yue, Yang
He, Shan
- Contributor
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SpringerLink (Online service)
- DOI
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10.1186/s12859-021-04327-w
- URN
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urn:nbn:de:101:1-2021111619514667610396
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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15.08.2025, 7:34 AM CEST
Data provider
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Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Yue, Yang
- He, Shan
- SpringerLink (Online service)
Other Objects (12)
MSH-DTI: multi-graph convolution with self-supervised embedding and heterogeneous aggregation for drug-target interaction prediction
DTiGEMS+: drug–target interaction prediction using graph embedding, graph mining, and similarity-based techniques
GraphDTI: A robust deep learning predictor of drug-target interactions from multiple heterogeneous data
CCL-DTI: contributing the contrastive loss in drug–target interaction prediction
Novel drug-target interactions via link prediction and network embedding
A comparison of embedding aggregation strategies in drug–target interaction prediction
DTi2Vec: Drug–target interaction prediction using network embedding and ensemble learning
GSRF-DTI: a framework for drug-target interaction prediction based on a drug-target pair network and representation learning on a large graph
CAT-DTI: cross-attention and Transformer network with domain adaptation for drug-target interaction prediction
MOKPE: drug–target interaction prediction via manifold optimization based kernel preserving embedding
Accurate prediction of drug-target interactions in Chinese and western medicine by the CWI-DTI model
DLM-DTI: a dual language model for the prediction of drug-target interaction with hint-based learning
MSH-DTI: multi-graph convolution with self-supervised embedding and heterogeneous aggregation for drug-target interaction prediction
DTiGEMS+: drug–target interaction prediction using graph embedding, graph mining, and similarity-based techniques
GraphDTI: A robust deep learning predictor of drug-target interactions from multiple heterogeneous data
CCL-DTI: contributing the contrastive loss in drug–target interaction prediction
Novel drug-target interactions via link prediction and network embedding
A comparison of embedding aggregation strategies in drug–target interaction prediction
DTi2Vec: Drug–target interaction prediction using network embedding and ensemble learning
GSRF-DTI: a framework for drug-target interaction prediction based on a drug-target pair network and representation learning on a large graph
CAT-DTI: cross-attention and Transformer network with domain adaptation for drug-target interaction prediction
MOKPE: drug–target interaction prediction via manifold optimization based kernel preserving embedding
Accurate prediction of drug-target interactions in Chinese and western medicine by the CWI-DTI model
DLM-DTI: a dual language model for the prediction of drug-target interaction with hint-based learning
MSH-DTI: multi-graph convolution with self-supervised embedding and heterogeneous aggregation for drug-target interaction prediction
DTiGEMS+: drug–target interaction prediction using graph embedding, graph mining, and similarity-based techniques
GraphDTI: A robust deep learning predictor of drug-target interactions from multiple heterogeneous data
CCL-DTI: contributing the contrastive loss in drug–target interaction prediction
Novel drug-target interactions via link prediction and network embedding
A comparison of embedding aggregation strategies in drug–target interaction prediction
DTi2Vec: Drug–target interaction prediction using network embedding and ensemble learning
GSRF-DTI: a framework for drug-target interaction prediction based on a drug-target pair network and representation learning on a large graph
CAT-DTI: cross-attention and Transformer network with domain adaptation for drug-target interaction prediction
MOKPE: drug–target interaction prediction via manifold optimization based kernel preserving embedding
Accurate prediction of drug-target interactions in Chinese and western medicine by the CWI-DTI model