一站式蛋白工程数据与模型微调平台，打通生物与计算机科研壁垒。
VenusFactory: A Unified Platform for Protein Engineering Data Retrieval and Language Model Fine-Tuning
- 集成40+蛋白数据集与40+语言模型，支持多任务基准测试
- 提供命令行与无代码界面，降低跨学科使用门槛
- 开源可复现，适合生物、计算机双背景研究者使用
自然语言处理（NLP）已扩展至蛋白工程领域，预训练蛋白语言模型（PLMs）表现优异。然而，跨学科应用受限于数据获取难、任务评估不统一及应用复杂等问题。本文提出VenusFactory，一个融合生物数据检索、标准化任务基准测试与模块化PLM微调的统一平台。该平台支持命令行与Gradio无代码界面，集成40余个蛋白相关数据集和40余个主流PLMs。所有代码已开源，地址为https://github.com/tyang816/VenusFactory。
原文摘要 · Abstract (English)
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.
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