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Updated: Sep 17, 2025

Mass Spectrometry-Based Proteomics Analyses Using the OpenProt Database to Unveil Novel Proteins Translated from Non-Canonical Open Reading Frames

Mass Spectrometry-Based Proteomics Analyses Using the OpenProt Database to Unveil Novel Proteins Translated from Non-Canonical Open Reading Frames

Published on: April 11, 2019

使用蛋白质语言模型对蛋白质组的功能性注释:ProtTrans模型的高通量实现

Ildefonso Cases¹, Gemma Martínez-Redondo², Rosa Fernández²

¹CSIC, Andalusian Center for Developmental Biology, Computational Biology and Bioinformatics Group, Seville, Spain.

Methods in molecular biology (Clifton, N.J.)

|July 2, 2025

概括

蛋白质功能预测现在使用蛋白质语言模型更准确. FANTASIA工具利用这些模型进行大规模注释非特征蛋白质组,改进生物研究.

科学领域:

计算生物学是一种计算生物学.
基因组学就是基因组学.
生物信息学是一种生物信息学.

背景情况:

准确的蛋白质功能预测对于生物研究至关重要,但仍然具有挑战性,特别是对于非模型生物.
传统的序列相似性方法往往无法注释大量的蛋白质.
蛋白质语言模型在提高功能注释准确性和全面性方面取得了重大进展.

研究的目的:

为了突出ProtTrans蛋白质语言模型对每种蛋白质进行注释的卓越性能.
介绍FANTASIA (基于嵌入空间相似性的功能注释),这是一种使用蛋白质语言模型大规模注释非特征蛋白质的工具.
通过转录学,模型生物和非模型生物的案例研究来证明FANTASIA的实用性.

主要方法:

利用ProtTrans蛋白语言模型进行增强的蛋白质功能预测.
开发和实施用于大规模蛋白质组注释的FANTASIA工具.
将FANTASIA应用于三个不同的生物学案例研究.

主要成果:

与其他工具相比,ProtTrans模型在每蛋白注释方面表现出卓越的性能.
FANTASIA有效地利用了蛋白质语言模型的进步,以实现高效的大规模注释.
案例研究展示了FANTASIA在转录学,模型生物体基因功能分配和非模型生物体基因识别方面的实用性.

结论:

蛋白质语言模型为预测蛋白质功能提供了更精确的方法.
FANTASIA提供了一种强大且易于使用的工具,用于在各种生物环境中推进功能注释.
这些进展有可能显著加速功能基因组学和相关领域的发展.

关键词:

计算生物学是一种计算生物学.幻想的世界幻想的世界蛋白质功能的预测和预测蛋白质语言模型的模型蛋白质组注释蛋白质组注释

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