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VenusFactory: A Unified Platform for Protein Engineering Data Retrieval and Language Model Fine-Tuning

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arxiv 2503.15438 v1 pith:HCKDZ6YQ submitted 2025-03-19 cs.CL cs.AIq-bio.QM

Yang Tan , Chen Liu , Jingyuan Gao , Banghao Wu , Mingchen Li , Ruilin Wang , Lingrong Zhang , Huiqun Yu
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Guisheng Fan Liang Hong Bingxin Zhou
This is my paper · ORCID
classification cs.CLcs.AIq-bio.QM
keywords languagevenusfactorydataplmsproteinbenchmarkingengineeringfine-tuning
verification ladder T0 review T1 audit T2 compute T3 formal
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abstract

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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Cited by 1 Pith paper

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  1. PFMBench: Protein Foundation Model Benchmark

    q-bio.BM 2025-06 conditional novelty 5.0 of 10

    A comprehensive benchmark of 17 protein foundation models across 38 tasks yields task correlations, a streamlined protocol, and identifies ProTrek as the strongest general performer.

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