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
other OA: green CC0
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⚙ AI-generated summary by claude@2026-06, 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

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. [ expand to 2 hops ] — adds papers reached through this work's immediate citers/citees. Heavier; up to 60 extra dots.

References (92)

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