VenusFactory: A Unified Platform for Protein Engineering Data Retrieval and Language Model Fine-Tuning
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arXiv
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| Main Authors: | , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866909543380811776 |
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| author | Tan, Yang Liu, Chen Gao, Jingyuan Wu, Banghao Li, Mingchen Wang, Ruilin Zhang, Lingrong Yu, Huiqun Fan, Guisheng Hong, Liang Zhou, Bingxin |
| author_facet | Tan, Yang Liu, Chen Gao, Jingyuan Wu, Banghao Li, Mingchen Wang, Ruilin Zhang, Lingrong Yu, Huiqun Fan, Guisheng Hong, Liang Zhou, Bingxin |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_15438 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | VenusFactory: A Unified Platform for Protein Engineering Data Retrieval and Language Model Fine-Tuning Tan, Yang Liu, Chen Gao, Jingyuan Wu, Banghao Li, Mingchen Wang, Ruilin Zhang, Lingrong Yu, Huiqun Fan, Guisheng Hong, Liang Zhou, Bingxin Computation and Language Artificial Intelligence Quantitative Methods 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. |
| title | VenusFactory: A Unified Platform for Protein Engineering Data Retrieval and Language Model Fine-Tuning |
| topic | Computation and Language Artificial Intelligence Quantitative Methods |
| url | https://arxiv.org/abs/2503.15438 |