The most significant GO terms and p-values for each of the five modules.

<p>The most significant GO terms and p-values for each of the five modules.</p>

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Bibliographic Details
Main Author:	Zongjin Li (38031) (author)
Other Authors:	Liqin Tian (802035) (author), Libing Bai (20614186) (author), Zeyu Jia (12438600) (author), Xiaoming Wu (388718) (author), Changxin Song (20614189) (author)
Published:	2025
Subjects:	Microbiology Cell Biology Genetics Space Science Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified supervised learning ideas small sample size loss function based high feature dimensionality critical risk factor gene module detection xlink "> hypertension algorithm &# 8217 obtaining hypertension biomarkers gene expression data gene biomarkers gene node preventing hypertension validation dataset using gse113439 significantly differentiated significantly different significant advantages reach 97 proposed algorithm posing challenges literature methods link prediction interaction information important source graph network gnn model experiment revealed comparative methods cardiovascular diseases biological significance algorithm utilizes 50 %, 45 %,
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