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Split-and-pool Synthesis and Characterization of Peptide Tertiary Amide Library
Published on: June 20, 2014
peptidy: a light-weight Python library for peptide representation in machine learning
Rıza Özçelik1,2, Laura van Weesep1, Sarah de Ruiter1
1Department of Biomedical Engineering, Institute for Complex Molecular Systems, Eindhoven University of Technology, Eindhoven 5612AZ, Netherlands.
Motivation:
Peptides are widely used in applications ranging from drug discovery to food technologies. Machine learning has become increasingly prominent in accelerating the search for new peptides, and user-friendly computational tools can further enhance these efforts.
Results:
In this work, we introduce peptidy-a lightweight Python library that facilitates converting peptides (expressed as amino acid sequences) to numerical representations suited to machine learning. peptidy is free from external dependencies, integrates seamlessly into modern Python environments, and supports a range of encoding strategies suitable for both predictive and generative machine learning approaches. Additionally, peptidy supports peptides with post-translational modifications, such as phosphorylation, acetylation, and methylation, thereby extending the functionality of existing Python packages for peptides and proteins.
Availability And Implementation:
peptidy is freely available with a permissive license on GitHub at the following URL: https://github.com/molML/peptidy.
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