Binding Affinity Predictions

The Journey of Data: Lessons Learned in Modeling Kinase Affinity, Selectivity, and Resistance [Article v1. 0]
Recent advances in machine learning (ML) are reshaping drug discovery. Structure-based ML methods use physically-inspired models to …
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@article{castroTheJourneyOfData2025,
 author = {Raquel López-Ríos de Castro and Jaime Rodríguez-Guerra and David Schaller and Talia K Kimber and Corey Taylor and Jessica B White and Michael Backenköhler and Joschka Groß and Alexander M Payne and Benjamin Kaminow and Ivan Pulido and Sukrit Singh and Paula Linh Kramer and Guilermo Pérez-Hernández and Andrea Volkamer and John D Chodera},
 doi = {10.33011/livecoms.6.1.3875},
 editor = {David L. Mobley and Michael R. Shirts and Daniel M. Zuckerman},
 journal = {Living Journal of Computational Molecular Science (LiveCoMS)},
 month = {11},
 number = {1},
 pages = {3875-3875},
 publisher = {University of Colorado Boulder, Boulder, Colorado, USA},
 title = {The Journey of Data: Lessons Learned in Modeling Kinase Affinity, Selectivity, and Resistance [Article v1. 0]},
 url = {https://www.dfki.de/fileadmin/user_upload/import/16917_The_Journey_of_Data_Lessons_Learned_in_Modeling_Ki.pdf},
 volume = {6},
 year = {2025}
}
DOI