PyPropel: a Python-based tool for efficiently processing and characterising protein data.

ABSTRACT:

Background

The volume of protein sequence data has grown exponentially in recent years, driven by advancements in metagenomics. Despite this, a substantial proportion of these sequences remain poorly annotated, underscoring the need for robust bioinformatics tools to facilitate efficient characterisation and annotation for functional studies.

Results

We present PyPropel, a Python-based computational tool developed to streamline the large-scale analysis of protein data, with a particular focus on applications in machine learning. PyPropel integrates sequence and structural data pre-processing, feature generation, and post-processing for model performance evaluation and visualisation, offering a comprehensive solution for handling complex protein datasets.

Conclusion

Py

SUBMITTER: Sun J 

PROVIDER: S-EPMC11871610 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature