Identifying anti-tumor heat shock proteins based on evolutionary information using deep learning method-Reference-Cited by-同舟云学术

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Identifying anti-tumor heat shock proteins based on evolutionary information using deep learning method

Published:2022-10 Issue: Volume: Page:
ISSN:
Container-title:2022 21st International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES)
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Author:

Fu Yi¹,Zhao Ji¹,Mei Juan¹,Ding Yi¹

Affiliation:

1. School of Internet of Things Engineering, Wuxi City College of Vocational Technology,Wuxi,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10036587/10036588/10036623.pdf?arnumber=10036623

Reference10 articles.

1. Identifying Heat Shock Protein Families from Imbalanced Data by Using Combined Features

2. Identification of Heat Shock Protein families and J-protein types by incorporating Dipeptide Composition into Chou's general PseAAC

3. Protein transfer learning improves identification of heat shock protein families

4. Dendritic cells pulsed with placental gp96 promote tumor-reactive immune responses

5. Heat Shock Proteins and Cancer

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