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

IF 2.4 Q2 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Bioinformatics advances Pub Date : 2025-03-21 eCollection Date: 2025-01-01 DOI:10.1093/bioadv/vbaf058
Rıza Özçelik, Laura van Weesep, Sarah de Ruiter, Francesca Grisoni
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引用次数: 0

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.

动机:肽被广泛应用于从药物发现到食品技术的各个领域。机器学习在加速寻找新肽方面的作用日益突出,而用户友好型计算工具可以进一步加强这些工作:在这项工作中,我们介绍了 peptidy--一个轻量级 Python 库,它有助于将多肽(以氨基酸序列表示)转换为适合机器学习的数字表示。peptidy 不依赖于外部环境,可无缝集成到现代 Python 环境中,并支持一系列适合预测式和生成式机器学习方法的编码策略。此外,peptidy 还支持磷酸化、乙酰化和甲基化等翻译后修饰的多肽,从而扩展了现有 Python 多肽和蛋白质软件包的功能。可用性和实现:peptidy 在 GitHub 上以许可的方式免费提供,网址如下:https://github.com/molML/peptidy。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
1.60
自引率
0.00%
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