A Novel Method for Inference of Acyclic Chemical Compounds with Bounded Branch-height Based on Artificial Neural Networks and Integer Programming
Naveed Ahmed Azam(Quaid-i-Azam University), Tatsuya Akutsu(Kyoto University), Jianshen Zhu(Kyoto University), Hiroshi Nagamochi(Kyoto University), Liang Zhao(Shenyang Aerospace University), Aleksandar Shurbevski(Kyoto University), Yu Shi(First Affiliated Hospital Zhejiang University), Yanming Sun(National Development and Reform Commission)
Cited by 3
Related Papers
A Digital-Twin-Assisted Fault Diagnosis Using Deep Transfer Learning
|IEEE Access|2019|507
iLearn: an integrated platform and meta-learner for feature engineering, machine-learning analysis and modeling of DNA, RNA and protein sequence data
|Briefings in Bioinformatics|2019|436
PROSPER: An Integrated Feature-Based Tool for Predicting Protease Substrate Cleavage Sites
|PLoS ONE|2012|316
Recent advances in understanding the biochemical and molecular mechanism of diabetic retinopathy
|Biomedicine & Pharmacotherapy|2015|294