Figure - PMC

Skip to main content

An official website of the United States government

Here's how you know

Here's how you know

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

View full-text article in PMC

. 2024 Dec 19;15:1506663. doi: 10.3389/fimmu.2024.1506663

Search in PMC
Search in PubMed
View in NLM Catalog
Add to search

Copyright © 2024 Shen, Fan, Jiang, Yao, Qian, Tong, Fan, Liu, Dong, Zhang and Shi

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

PMC Copyright notice

Selection of diagnostic biomarkers for CAVD by PPI network and machine learning (ML). (A) The PPI network of IADEGs. (B) The top 10 hub genes identified using the degree method with the CytoHubba plugin (Cytoscape). (C) The 9 genes with the highest MCODE scores in the PPI network were defined as hub genes. (D, E) The DEGs corresponding to the lowest binomial deviance were identified as the most suitable candidates. (F, G) Random forest was used to analyze the relationships between the number of trees and the error rate. (H, I) The plot shows iDEGs ranked based on the importance score calculated from the random forest. (J) The 9 intersecting genes recognized by the two PPI-based methods. (K, L) 5 hub genes were respectively selected from two datasets by two ML algorithms as potential hub iDEGs for further evaluation.