DeepProtein: deep learning library and benchmark for protein sequence learning

doi:10.1093/bioinformatics/btaf165

2025-10-01

Jiaqing Xie

Li, Yuqiang

Tianfan Fu *

DOI：10.1093/bioinformatics/btaf165

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动机深度学习已深刻影响蛋白质科学，实现了在预测蛋白质性质、高阶结构和分子相互作用方面的突破。结果本文介绍了DeepProtein，这是一个全面且用户友好的深度学习库，专为蛋白质相关任务设计。它使研究人员能够无缝地使用前沿深度学习模型处理蛋白质数据。为评估模型性能，我们建立了一个基准测试，用于评估不同深度学习架构在多个蛋白质相关任务上的表现，包括蛋白质功能预测、亚细胞定位预测、蛋白质-蛋白质相互作用预测和蛋白质结构预测。此外，我们介绍了DeepProt-T5，这是一系列基于Prot-T5微调的模型，在四项基准任务上实现了当前最佳性能，并在其他六项任务上表现出有竞争力的结果。全面的文档和教程可供使用，以确保易用性和支持可重复性。可用性与实现基于广泛使用的药物发现库DeepPurpose，DeepProtein已在 https://github.com/jiaqingxie/DeepProtein 上公开可用。

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Nanjing University

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swiss federal institutes of technology domain

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