Natural language processing (NLP) has significantly influenced scientific domains beyond human language, including protein engineering, where pre-trained protein language models (PLMs) have demonstrated remarkable success. However, interdisciplinary adoption remains limited due to challenges in data collection, task benchmarking, and application. This work presents VenusFactory, a versatile engine that integrates biological data retrieval, standardized task benchmarking, and modular fine-tuning of PLMs. VenusFactory supports both computer science and biology communities with choices of both a command-line execution and a Gradio-based no-code interface, integrating 40+ protein-related datasets and 40+ popular PLMs. All implementations are open-sourced on https://github.com/tyang816/VenusFactory.
@article{arxiv.2503.15438,
title = {VenusFactory: A Unified Platform for Protein Engineering Data Retrieval and Language Model Fine-Tuning},
author = {Yang Tan and Chen Liu and Jingyuan Gao and Banghao Wu and Mingchen Li and Ruilin Wang and Lingrong Zhang and Huiqun Yu and Guisheng Fan and Liang Hong and Bingxin Zhou},
journal= {arXiv preprint arXiv:2503.15438},
year = {2025}
}