Politano Gianfranco, Benso Alfredo, Rehman Hafeez Ur, Re Angela
Department of Control and Computer Engineering, Politecnico di Torino, Torino, 10129, Italy.
School of Computing and Data Sciences, Oryx Universal College with Liverpool John Moores University, Qatar.
NAR Genom Bioinform. 2024 Aug 27;6(3):lqae112. doi: 10.1093/nargab/lqae112. eCollection 2024 Sep.
Associating one or more Gene Ontology (GO) terms to a protein means making a statement about a particular functional characteristic of the protein. This association provides scientists with a snapshot of the biological context of the protein activity. This paper introduces PRONTO-TK, a Python-based software toolkit designed to democratize access to Neural-Network based complex protein function prediction workflows. PRONTO-TK is a user-friendly graphical interface (GUI) for empowering researchers, even those with minimal programming experience, to leverage state-of-the-art Deep Learning architectures for protein function annotation using GO terms. We demonstrate PRONTO-TK's effectiveness on a running example, by showing how its intuitive configuration allows it to easily generate complex analyses while avoiding the complexities of building such a pipeline from scratch.
将一个或多个基因本体（GO）术语与一种蛋白质相关联意味着对该蛋白质的特定功能特性做出陈述。这种关联为科学家提供了蛋白质活性生物学背景的简要描述。本文介绍了PRONTO-TK，这是一个基于Python的软件工具包，旨在使基于神经网络的复杂蛋白质功能预测工作流程的访问民主化。PRONTO-TK是一个用户友好的图形界面（GUI），用于帮助研究人员，即使是那些编程经验最少的研究人员，利用先进的深度学习架构使用GO术语进行蛋白质功能注释。我们通过一个运行示例展示了PRONTO-TK的有效性，展示了其直观的配置如何使其能够轻松生成复杂的分析，同时避免从头构建这样一个管道的复杂性。
