Graph pooling in graph neural networks: methods and their applications in omics studies.

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Title: Graph pooling in graph neural networks: methods and their applications in omics studies.
Authors: Wang, Yan1, Hou, Wenju1, Sheng, Nan1, Zhao, Ziqi2, Liu, Jialin1, Huang, Lan1, huanglan@jlu.edu.cn, Wang, Juexin3, wangjuex@iu.edu
Source: Artificial Intelligence Review; Nov2024, Vol. 57 Issue 11, p1-55, 55p
Database: Applied Science & Technology Source
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DbLabel: Applied Science & Technology Source
An: 179668087
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  Data: Graph pooling in graph neural networks: methods and their applications in omics studies.
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  Data: <searchLink fieldCode="AU" term="%22Wang%2C+Yan%22">Wang, Yan</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AU" term="%22Hou%2C+Wenju%22">Hou, Wenju</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AU" term="%22Sheng%2C+Nan%22">Sheng, Nan</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AU" term="%22Zhao%2C+Ziqi%22">Zhao, Ziqi</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AU" term="%22Liu%2C+Jialin%22">Liu, Jialin</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AU" term="%22Huang%2C+Lan%22">Huang, Lan</searchLink><relatesTo>1</relatesTo>, <i>huanglan@jlu.edu.cn</i><br /><searchLink fieldCode="AU" term="%22Wang%2C+Juexin%22">Wang, Juexin</searchLink><relatesTo>3</relatesTo>, <i>wangjuex@iu.edu</i>
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  Data: <searchLink fieldCode="JN" term="%22Artificial+Intelligence+Review%22">Artificial Intelligence Review</searchLink>; Nov2024, Vol. 57 Issue 11, p1-55, 55p
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1007/s10462-024-10918-9
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      – Code: eng
        Text: English
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        PageCount: 55
        StartPage: 1
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      – TitleFull: Graph pooling in graph neural networks: methods and their applications in omics studies.
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            NameFull: Wang, Yan
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            NameFull: Hou, Wenju
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            NameFull: Sheng, Nan
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            NameFull: Zhao, Ziqi
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            NameFull: Liu, Jialin
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            NameFull: Huang, Lan
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            – D: 01
              M: 11
              Text: Nov2024
              Type: published
              Y: 2024
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              Value: 57
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