Application of Bioactivity Profile Based Fingerprints for Building Machine Learning Models
Keyword(s):
<div>This article describes an application of high-throughput fingerprints (HTSFP) built upon industrial data accumulated over the years. </div><div>The fingerprint was used to build machine learning models (multi-task deep learning + SVM) for compound activity predictions towards a panel of 131 targets. </div><div>Quality of the predictions and the scaffold hopping potential of the HTSFP were systematically compared to traditional structural descriptors ECFP. </div><div><br></div>
2020 ◽
Keyword(s):
2019 ◽
Predictive modelling of turbofan engine components condition using machine and deep learning methods
2021 ◽
Vol 23
(2)
◽
pp. 359-370
2021 ◽
2020 ◽
Keyword(s):
2020 ◽
Vol 34
(7)
◽
pp. 717-730
◽
2021 ◽