Towards Gene Function Prediction via Multi-Networks Representation Learning Article Swipe
Hansheng Xue
,
Jiajie Peng
,
Xuequn Shang
·
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1609/aaai.v33i01.330110069
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1609/aaai.v33i01.330110069
Multi-networks integration methods have achieved prominent performance on many network-based tasks, but these approaches often incur information loss problem. In this paper, we propose a novel multi-networks representation learning method based on semi-supervised autoencoder, termed as DeepMNE, which captures complex topological structures of each network and takes the correlation among multinetworks into account. The experimental results on two realworld datasets indicate that DeepMNE outperforms the existing state-of-the-art algorithms.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1609/aaai.v33i01.330110069
- https://ojs.aaai.org/index.php/AAAI/article/download/5171/5044
- OA Status
- diamond
- Cited By
- 4
- References
- 2
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2965725058
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2965725058Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1609/aaai.v33i01.330110069Digital Object Identifier
- Title
-
Towards Gene Function Prediction via Multi-Networks Representation LearningWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2019Year of publication
- Publication date
-
2019-07-17Full publication date if available
- Authors
-
Hansheng Xue, Jiajie Peng, Xuequn ShangList of authors in order
- Landing page
-
https://doi.org/10.1609/aaai.v33i01.330110069Publisher landing page
- PDF URL
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https://ojs.aaai.org/index.php/AAAI/article/download/5171/5044Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
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https://ojs.aaai.org/index.php/AAAI/article/download/5171/5044Direct OA link when available
- Concepts
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Autoencoder, Representation (politics), Computer science, Artificial intelligence, Machine learning, Feature learning, Function (biology), Data mining, Artificial neural network, Theoretical computer science, Political science, Biology, Politics, Law, Evolutionary biologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
4Total citation count in OpenAlex
- Citations by year (recent)
-
2024: 1, 2022: 1, 2021: 1, 2020: 1Per-year citation counts (last 5 years)
- References (count)
-
2Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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