Author Correction: Biophysical prediction of protein–peptide interactions and signaling networks using machine learning
Nature Methods ,
May 2026
Cunningham, Joseph M. , Koytiger, Grigoriy , Sorger, Peter K. , AlQuraishi, Mohammed
Author Correction: Biophysical prediction of protein–peptide interactions and signaling networks using machine learning
Corrections & amendments
Author Correction: Biophysical prediction of protein–peptide
interactions and signaling networks using machine learning
Correction to: Nature Methods
https://doi.org/10.1038/s41592-019-0687-1,
published online 6 January 2020.
Joseph M. Cunningham
Mohammed AlQuraishi
https://doi.org/10.1038/s41592-026-03117-7
In the version of the article initially published, there was an error in the tyrosine kinase dataset
used to train the model and as a result the model did not accurately reflect overall kinase binding preferences. The article has now been updated with a corrected dataset and newly trained
model and as a result Figs. 1–6, the main text of the article (including the Methods) and the
Supplementary information have been corrected. Additionally, Julia R. Rogers (Department
of Systems Biology, Columbia University, New York, NY, USA) has been added to the author
list given her contributions to constructing an updated dataset, training a new model, designing and performing analyses and computational experiments, and revising the manuscript.
These corrections have been made to the HTML and PDF versions of the article. The original,
uncorrected article is available for comparison as Supplementary information alongside the
online version of this notice.
Published online: xx xx xxxx
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, Grigoriy Koytiger, Peter K. Sorger
&
Additional information
Supplementary information The online version contains supplementary material available at
https://doi.org/10.1038/s41592-026-03117-7.
© The Author(s), under exclusive licence to Springer Nature America, Inc. 2026
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Cunningham, Joseph M., Koytiger, Grigoriy, Sorger, Peter K., AlQuraishi, Mohammed.
Author Correction: Biophysical prediction of protein–peptide interactions and signaling networks using machine learning ,
Nature Methods,
2026, DOI: 10.1038/s41592-026-03117-7