Identifying Potential Machine Learning Algorithms for the Simulation of Binding Affinities to Molecularly Imprinted Polymers

Identifying Potential Machine Learning Algorithms for the Simulation of Binding Affinities to Molecularly Imprinted Polymers

Molecularly imprinted polymers (MIPs) are synthetic receptors engineered towards the selective binding of a target molecule; however, the manner in which MIPs interact with other molecules is of great importance. Being able to rapidly analyze the binding of potential molecular interferences and dete...

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Bibliographic Details
Main Authors: Joseph W. Lowdon, Hikaru Ishikura, Malene K. Kvernenes, Manlio Caldara, Thomas J. Cleij, Bart van Grinsven, Kasper Eersels, Hanne Diliën
Format: Article
Language:English
Published: MDPI AG 2021-09-01
Series:Computation
Subjects:
molecularly imprinted polymers
artificial intelligence
neural networking
simulation
Online Access:https://www.mdpi.com/2079-3197/9/10/103

Internet

https://www.mdpi.com/2079-3197/9/10/103

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