Tumor Progression
Cancer Survival Analysis
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Updated: Dec 18, 2025

A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information
Published on: July 1, 2020
Qingyang Zhang1, Ghadeer Mahdi2, Jian Tinker1
1Department of Mathematical Sciences, University of Arkansas, USA.
This study introduces a new computational method to analyze dynamic pathway changes during cancer progression. The approach identifies key pathways, like cell cycle and ERBB signaling, crucial for serous ovarian cancer development.
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