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Updated: May 30, 2026

Analyzing Tumor Gene Expression Factors with the CorExplorer Web Portal
Published on: October 11, 2019
Cancer progression analysis based on ordinal relationship of cancer stages and co-expression network modularity
Yoon Soo Pyon1, Xin Li, Jing Li
1Department of Electrical Engineering and Computer Science, Case Western Reserve University, 10900 Euclid Avenue, Olin 514, Cleveland, OH 44106, USA. yoon.pyon@case.edu
Abstract:
A comprehensive understanding of cancer progression may shed light on genetic and molecular mechanisms of oncogenesis, and provide important information for effective diagnosis and prognosis. We propose a multicategory logit model to identify genes that show significant correlations across multiple cancer stages. We have applied the approach on a Prostate Cancer (PCA) progression data and obtained a set of genes that show consistent trends across multiple stages. Further analysis based on multiple evidences demonstrates that our candidate list includes not only some well-known prostate-cancer-related genes, but also novel genes that have been confirmed very recently.
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