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POI-3DGCN: Predicting odor intensity of monomer flavors based on three-dimensionally embedded graph convolutional network

  • Published:2022-08 Issue: Volume:199 Page:116997
  • ISSN:0957-4174
  • Container-title:Expert Systems with Applications
  • language:en
  • Short-container-title:Expert Systems with Applications

Author:

Liu QiORCID,Luo Dehan,Wen TengtengORCID,GholamHosseini Hamid,Qiu Xiaofang,Li Jingshan

Funder

National Natural Science Foundation of China

Guangdong Science and Technology Department

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference42 articles.

1. Random forests;Breiman;Machine Learning,2001

2. Deep learning with Python: Develop deep learning models on theano and tensorflow using Keras;Brownlee,2016

3. Humans as sensors to evaluate drinking water taste and odor: a review;Burlingame;Journal-American Water Works Association,2017

4. Data based predictive models for odor perception;Chacko;Scientific Reports,2020

5. Three-dimensionally embedded graph convolutional network (3dgcn) for molecule interpretation;Cho,2018

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