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Graph neural networks and sequence embeddings enable the prediction and design of the cofactor specificity of Rossmann fold proteins
Kamil Kaminski, Jan Ludwiczak, Maciej Jasinski, Adriana Bukala, Rafal Madaj, Krzysztof Szczepaniak, View ORCID ProfileStanislaw Dunin-Horkawicz
doi: https://doi.org/10.1101/2021.05.05.440912
Kamil Kaminski
1Laboratory of Structural Bioinformatics, Centre of New Technologies, University of Warsaw, 02-097 Warsaw, Poland
Jan Ludwiczak
1Laboratory of Structural Bioinformatics, Centre of New Technologies, University of Warsaw, 02-097 Warsaw, Poland
2Laboratory of Bioinformatics, Nencki Institute of Experimental Biology, Pasteura 3, 02-093 Warsaw, Poland
Maciej Jasinski
1Laboratory of Structural Bioinformatics, Centre of New Technologies, University of Warsaw, 02-097 Warsaw, Poland
Adriana Bukala
1Laboratory of Structural Bioinformatics, Centre of New Technologies, University of Warsaw, 02-097 Warsaw, Poland
Rafal Madaj
3Centre of Molecular and Macromolecular Studies, Polish Academy of Sciences, Sienkiewicza 112, 90-363, Lodz, Poland
Krzysztof Szczepaniak
1Laboratory of Structural Bioinformatics, Centre of New Technologies, University of Warsaw, 02-097 Warsaw, Poland
Stanislaw Dunin-Horkawicz
1Laboratory of Structural Bioinformatics, Centre of New Technologies, University of Warsaw, 02-097 Warsaw, Poland

- Supplemental Tables and Figures[supplements/440912_file08.pdf]
Posted May 06, 2021.
Graph neural networks and sequence embeddings enable the prediction and design of the cofactor specificity of Rossmann fold proteins
Kamil Kaminski, Jan Ludwiczak, Maciej Jasinski, Adriana Bukala, Rafal Madaj, Krzysztof Szczepaniak, Stanislaw Dunin-Horkawicz
bioRxiv 2021.05.05.440912; doi: https://doi.org/10.1101/2021.05.05.440912
Graph neural networks and sequence embeddings enable the prediction and design of the cofactor specificity of Rossmann fold proteins
Kamil Kaminski, Jan Ludwiczak, Maciej Jasinski, Adriana Bukala, Rafal Madaj, Krzysztof Szczepaniak, Stanislaw Dunin-Horkawicz
bioRxiv 2021.05.05.440912; doi: https://doi.org/10.1101/2021.05.05.440912
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