WGCNA was employed to identify modules associated with the synthetic periodontitis dataset.

<p>(A, B) Based on scale independence and average connectivity, β = 8 was considered the optimal soft-thresholding value. (C) Gene clustering tree with multiple partitioned modules. Different clusters are connected by different colors. (D) Heatmap of adjacency of feature genes.</p>

محفوظ في:

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Zhifeng Wu (303016) (author)
مؤلفون آخرون:	Fan Zhang (46132) (author), Yuan Wang (14955) (author), Chunjiang Liu (125011) (author), Zhaokun Sun (19197309) (author), Xiaoqi Tang (12996656) (author), Liming Tang (2231494) (author)
منشور في:	2025
الموضوعات:	Biochemistry Microbiology Cell Biology Genetics Molecular Biology Immunology Biological Sciences not elsewhere classified Information Systems not elsewhere classified targeted drug prediction receiver operating characteristic conducted differential analysis abdominal aortic aneurysm expression network analysis external independent datasets ppi network analysis related module genes identified key genes ppi network candidate genes obtained datasets xlink "> validation confirmed ten drugs robustly associated positive correlations neutrophil infiltration machine learning intersection initially geo database bioinformatics approaches
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WGCNA was employed to identify modules associated with the synthetic periodontitis dataset.

مواد مشابهة