In this article, the team demonstrates the application of Alchemite™, a deep learning imputation method which underpins our Cerella™ technology, to physicochemical and sensory data. They compare the deep learning model with traditional QSAR models, demonstrating significantly improved accuracy using Cerella.
Citation details
S. Mahmoud, B. Irwin, D. Chekmarev, S. Vyas, J. Kattas, T. Whitehead, T. Mansley, J. Bikker, G. Conduit, M. Segall,
J. Comput. Aided Mol. Des., 2021, 35(11), pp. 1125-1140
DOI: 10.1007/s10822-021-00424-3
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You can read this publication on the journal webpage via the button below. Alternatively, find out more about the application of deep learning methods to sensory data in our webinar led by three authors of this paper, Samar Mahmoud and Tamsin Mansley (Optibrium) and Dmitriy Chekmarev (IFF).
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