Limits of Prediction for Machine Learning in Drug Discovery
In drug discovery, molecules are optimized towards desired properties. In this context, machine learning is used for extrapolation in drug discovery projects. The limits of extrapolation for regression models are known. However, a systematic analysis of the effectiveness of extrapolation in drug dis...
Main Authors: | Modest von Korff, Thomas Sander |
---|---|
Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2022-03-01
|
Series: | Frontiers in Pharmacology |
Subjects: | |
Online Access: | https://www.frontiersin.org/articles/10.3389/fphar.2022.832120/full |
Similar Items
-
Partial Least Squares tutorial for analyzing neuroimaging data
by: Patricia Van Roon, et al.
Published: (2014-09-01) -
Investigation of Drug–Polymer Compatibility Using Chemometric-Assisted UV-Spectrophotometry
by: Amir Ibrahim Mohamed, et al.
Published: (2017-01-01) -
Detection and Quantification of Alprazolam Added to Long Drinks by Near Infrared Spectroscopy and Chemometrics
by: Claudia Scappaticci, et al.
Published: (2022-09-01) -
Estimating the Biomass of Maize with Hyperspectral and LiDAR Data
by: Cheng Wang, et al.
Published: (2016-12-01) -
Partial Least Squares Regression Methods with Application of Mas Cement Factory in Sulaymaniyah Governorate
by: Sherin mohyaldeen, et al.
Published: (2022-06-01)