Modelling gene expression profiles related to prostate tumor progression using binary states.

ABSTRACT:

Background

Cancer is a complex disease commonly characterized by the disrupted activity of several cancer-related genes such as oncogenes and tumor-suppressor genes. Previous studies suggest that the process of tumor progression to malignancy is dynamic and can be traced by changes in gene expression. Despite the enormous efforts made for differential expression detection and biomarker discovery, few methods have been designed to model the gene expression level to tumor stage during malignancy progression. Such models could help us understand the dynamics and simplify or reveal the complexity of tumor progression.

Methods

We have modeled an on-off state of gene activation per sample then per stage to select gene expression profiles associated to tumor progression. The select

SUBMITTER: Martinez E 

PROVIDER: S-EPMC3691825 | biostudies-literature | 2013 May

REPOSITORIES: biostudies-literature