Work

peptidy : a light-weight Python library for peptide representation in machine learning

Year: 2024

Type: article

Abstract: 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.

Source: Bioinformatics Advances

DOI: 10.1093/bioadv/vbaf058

Authors: Rıza Özçelik, Laura van Weesep, Sarah de Ruiter, Francesca Grisoni

Institutions: University Medical Center Utrecht, Eindhoven University of Technology

Language: English

Topic: Machine Learning in Bioinformatics

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: gold

Estimated APC paid: $2,917

Funder: European Commission