相关实验视频

Updated: Jun 5, 2025

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
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JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics

Published on: October 19, 2021

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预测模型生物基因的亲长寿或反长寿效应,以增强的高斯噪声增强为基础,对蛋白质-蛋白质相互作用网络进行对比学习

Ibrahim Alsaggaf1, Alex A Freitas2, Cen Wan1

  • 1School of Computing and Mathematical Sciences, Birkbeck, University of London, WC1E 7HX, London, UK.

NAR genomics and bioinformatics
|December 5, 2024
PubMed
概括

这项研究引入了一种新的机器学习方法,即增强的高斯噪声增强基于对比学习 (EGsCL),以预测衰老基因的影响. 在使用蛋白质-蛋白质相互作用网络识别与长寿相关的基因方面,EGsCL表现出卓越的性能.

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