The Journey of Data: Lessons Learned in Modeling Kinase Affinity, Selectivity, and Resistance

This document provides general information about the paper called "The Journey of Data: Lessons Learned in Modeling Kinase Affinity, Selectivity, and Resistance".

List of Authors

• Raquel López-Ríos de Castro [1,2,3]
• Jaime Rodríguez-Guerra [1,3]
• David Schaller [1,3]
• Talia B. Kimber [1,3]
• Corey Taylor [1,3]
• Jessica B. White [3]
• Michael Backenköhler [2]
• Joschka Groß [4]
• Alexander M. Payne [3]
• Benjamin Kaminow [3]
• Iván Pulido [3]
• Sukrit Singh [3]
• Paula Linh Kramer [2]
• Guillermo Pérez-Hernández [1,2,3]
• Andrea Volkamer* [1,2]
• John D. Chodera* [3]

[1] In silico Toxicology and Structural Bioinformatics, Institute of Physiology, Charité-Universitatsmedizin Berlin, Germany.

[2] Data Driven Drug Design, Saarland University, Saarbrücken, Germany.

[3] Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, USA.

[4] Neuro-Mechanistic Modeling, German Research Center for Artificial Intelligence, Saarbrücken, Germany.

List of Contributors

• Same as Authors' List

Paper writing as code development

This paper is being developed as a living document, open to changes from the community. You can read more about the concept of writing a paper in the same way one would write software code in the essay "Paper writing as code development". If you have comments or suggestions, we welcome them! Please submit them as issues to this GitHub repository so they can be recorded and given credit for the contribution. Specific changes can be proposed via pull requests.

List of Released Versions

• v1.0: Submitted to LiveCoMS, and posted on BioRxiv. Code available at: https://github.com/openkinome/kinoml

Changelog

• None