In silico prediction of chemical-induced hematotoxicity with machine learning and deep learning methods

Author(s):  
Yuqing Hua ◽  
Yinping Shi ◽  
Xueyan Cui ◽  
Xiao Li
2020 ◽  
Vol 39 (8) ◽  
pp. 1900178
Author(s):  
Jiajing Hu ◽  
Yingchun Cai ◽  
Weihua Li ◽  
Guixia Liu ◽  
Yun Tang

Author(s):  
Xiaoxiao Zhang ◽  
Piaopiao Zhao ◽  
Zhiyuan Wang ◽  
Xuan Xu ◽  
Guixia Liu ◽  
...  

2016 ◽  
Vol 5 (2) ◽  
pp. 570-582 ◽  
Author(s):  
Chen Zhang ◽  
Yuan Zhou ◽  
Shikai Gu ◽  
Zengrui Wu ◽  
Wenjie Wu ◽  
...  

A series of models of hERG blockage were built using five machine learning methods based on 13 molecular descriptors, five types of fingerprints and molecular descriptors combining fingerprints at four blockage thresholds.


RSC Advances ◽  
2017 ◽  
Vol 7 (11) ◽  
pp. 6697-6703 ◽  
Author(s):  
Qin Wang ◽  
Xiao Li ◽  
Hongbin Yang ◽  
Yingchun Cai ◽  
Yinyin Wang ◽  
...  

Chemical fingerprints combined with machine learning methods were used to build binary classification models for predicting the potential EC/EI of compounds.


2019 ◽  
Vol 8 (3) ◽  
pp. 341-352 ◽  
Author(s):  
Lin Liu ◽  
Hongbin Yang ◽  
Yingchun Cai ◽  
Qianqian Cao ◽  
Lixia Sun ◽  
...  

Six machine learning methods combined with descriptors or fingerprints were employed to predict chemical toxicity on marine crustaceans.


2017 ◽  
Vol 30 (5) ◽  
pp. 1209-1218 ◽  
Author(s):  
Hanwen Du ◽  
Yingchun Cai ◽  
Hongbin Yang ◽  
Hongxiao Zhang ◽  
Yuhan Xue ◽  
...  

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