.png){kind=icon}
返回
A comprehensive computational benchmark for evaluating deep learning-based protein function prediction approaches
.png){kind=icon}
OA
AI
DOI：10.1093/bib/bbae050.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Proteins play an important role in life activities and are the basic units for performing functions. Accurately annotating functions to proteins is crucial for understanding the intricate mechanisms of life and developing effective treatments for complex diseases. Traditional biological experiments struggle to keep pace with the growing number of known proteins. With the development of high-throughput sequencing technology, a wide variety of biological data provides the possibility to accurately predict protein functions by computational methods. Consequently, many computational methods have been proposed. Due to the diversity of application scenarios, it is necessary to conduct a comprehensive evaluation of these computational methods to determine the suitability of each algorithm for specific cases. In this study, we present a comprehensive benchmark, BeProf, to process data and evaluate representative computational methods. We first collect the latest datasets and analyze the data characteristics. Then, we investigate and summarize 17 state-of-the-art computational methods. Finally, we propose a novel comprehensive evaluation metric, design eight application scenarios and evaluate the performance of existing methods on these scenarios. Based on the evaluation, we provide practical recommendations for different scenarios, enabling users to select the most suitable method for their specific needs. All of these servers can be obtained from https://csuligroup.com/BEPROF and https://github.com/CSUBioGroup/BEPROF.
Keyword:
protein
protein function
deep learning
benchmark
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
7.7
论文数:
5.8K
被引数:
2.7W
机构
引用论文
Interactive video conferencing: A means of providing interim care to parkinson's disease patients交互式视频会议: 为帕金森氏病患者提供临时护理的一种手段
PREAI
分享收藏分享收藏Extreme and superextreme events in a loss-modulatedCO2laser: Nonlinear resonance route and precursors损失调制中的极端和超极端事件 CO2 激光: 非线性共振路线和前体OAAI
OAAI分享收藏A Deep Learning Framework for Gene Ontology Annotations With Sequence- and Network-Based Information基于序列和网络信息的基因本体注释深度学习框架OAAI
OAAI分享收藏NetGO: improving large-scale protein function prediction with massive network information.png)
NUCLEIC ACIDS RESEARCHOAAI
NUCLEIC ACIDS RESEARCHIF13.1
OAAI分享收藏
查看更多内容