Functional enrichment analysis based on low-risk and high-risk groups.

Functional enrichment analysis based on low-risk and high-risk groups.

<p>a) Top 10 enrichment pathways in KEGG based on the largest absolute NES. b) Top 10 enriched GO pathways based on the largest absolute NES.</p>

محفوظ في:

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Jiadong Chu (12418575) (author)
مؤلفون آخرون:	Na Sun (535425) (author), Wei Hu (6560) (author), Xuanli Chen (12418578) (author), Nengjun Yi (27315) (author), Yueping Shen (745072) (author)
منشور في:	2022
الموضوعات:	Cell Biology Genetics Molecular Biology Biotechnology Developmental Biology Cancer Infectious Diseases Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified receiver operating characteristic model could provide including pyrimidine metabolism 017 – 3 identify prognostic factors gene expression omnibus multivariate analysis demonstrated function enrichment analysis significant enrichment pathway prognostic signature screening multivariate cox regression gene signature included gene prognostic signature predict gc patients kaplan &# 8211 meier analysis showed predict overall survival improve prediction performance gene signature prognostic nomogram spearman analysis curve analysis univariate cox significant difference prediction performance overall survival xlink "> tpmt </ tor2a </ tnfrsf11a </ related genes psma5 </ poor survival notch3 </ nmnat1 </ likely related kif11 </ independent predictor gastric cancer findings suggested exploration based eif5a </ e2f8 </ clinical decision biomarkers would better diagnosis asian population 370 ), 001 ).
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