MANE: Organizational Network Embedding with Multiplex Attentive Neural Networks

Author(s):  
Yuyang Ye ◽  
Zheng Dong ◽  
Hengshu Zhu ◽  
Tong Xu ◽  
Xin Song ◽  
...  
2018 ◽  
Author(s):  
Cen Wan ◽  
Domenico Cozzetto ◽  
Rui Fa ◽  
David T. Jones

Protein-protein interaction network data provides valuable information that infers direct links between genes and their biological roles. This information brings a fundamental hypothesis for protein function prediction that interacting proteins tend to have similar functions. With the help of recently-developed network embedding feature generation methods and deep maxout neural networks, it is possible to extract functional representations that encode direct links between protein-protein interactions information and protein function. Our novel method, STRING2GO, successfully adopts deep maxout neural networks to learn functional representations simultaneously encoding both protein-protein interactions and functional predictive information. The experimental results show that STRING2GO outperforms other network embedding-based prediction methods and one benchmark method adopted in a recent large scale protein function prediction competition.


2020 ◽  
Vol 388 ◽  
pp. 1-11
Author(s):  
Chen Zhang ◽  
Zhouhua Tang ◽  
Bin Yu ◽  
Yu Xie ◽  
Ke Pan

Author(s):  
Dario Garcia-Gasulla ◽  
Armand Vilalta ◽  
Ferran Pares ◽  
Eduard Ayguade ◽  
Jesus Labarta ◽  
...  

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