Drug Discovery Maps, a Machine Learning Model That Visualizes and Predicts Kinome–Inhibitor Interaction Landscapes

[Image: see text] The interpretation of high-dimensional structure–activity data sets in drug discovery to predict ligand–protein interaction landscapes is a challenging task. Here we present Drug Discovery Maps (DDM), a machine learning model that maps the activity profile of compounds across an en...

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Detalles Bibliográficos
Autores principales: Janssen, Antonius P. A., Grimm, Sebastian H., Wijdeven, Ruud H. M., Lenselink, Eelke B., Neefjes, Jacques, van Boeckel, Constant A. A., van Westen, Gerard J. P., van der Stelt, Mario
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2018
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6437696/
https://www.ncbi.nlm.nih.gov/pubmed/30372617
http://dx.doi.org/10.1021/acs.jcim.8b00640

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