Additional file 3 of Unraveling pathogenesis, biomarkers and potential therapeutic agents for endometriosis associated with disulfidptosis based on bioinformatics analysis, machine learning and experiment validation

Zhao, Xiaoxuan, Zhao, Yang, Zhang, Yuanyuan, Fan, Qingnan, Ke, Huanxiao, Chen, Xiaowei, Jin, Linxi, Tang, Hongying, Jiang, Yuepeng, Ma, Jing
2024 · doi:10.6084/m9.figshare.26754253.v1 · W6977485312
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⚙ AI-generated summary by gemini-2.5-flash-lite, 2026-06-07 ⓘ

This study used bioinformatics analysis and machine learning to identify disulfidptosis-related genes in endometriosis and validated potential therapeutic targets.

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Abstract

Supplementary Material 3: Supplement figure 1. Correlation plot of eutopic disulfidptosis-related DEGs (A) and ectopic disulfidptosis-related DEGs (B) remaining after filtering out those with high correlation.

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Condition tags

endometriosis

Citation neighborhood (2-hop)

Papers in the corpus that this work cites (lower rings, blue) and that cite this one (upper rings, green). Dot size scales with the paper's in-corpus citation count — bigger dot = more influential within the endo/adeno field. Click a dot to open that paper. Outer rings show 2-hop neighbours — papers reached through the immediate citers/citees. [ collapse to 1-hop ]

References (92)

Source provenance

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last seen: 2026-05-11T08:48:50.894309+00:00
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