Comparative microarray data analysis for the expression of genes in the pathway of glioma

Abstract

Our present work focuses on the set of genes, which are involved in primary brain tumors ‐ the glioma pathway. These gliomas are mostly malignant (cancerous) in nature and are difficult to be cured and that’s why they attract the attention of all the workers. To understand the relative functionality of these genes, we analyzed the expression pattern of all genes, using gene expression data, at genomic level, and then to check their universality in all other cancers, we compared their expression levels and patterns in all other types of cancers by using gene expression graphs, and observed their expression levels in all these cancers, whether they are over or under expressed. We found that every gene has its own unique expression pattern and level and on that basis it can be classified. We also found that oncogenes and tumor suppressor genes that were involved in the glioma pathway were showing similar expression patterns in other cancers too but their expression level is low.

Up regulated virulence genes in M. tuberculosis H37Rv gleaned from genome wide expression profiles

“…It is of interest to explore the genome data to glean valuable information on the disease causing virulence factors. Expression profiling using data at the Gene Expression Omnibus (GEO) helps to get clues for gene function [5,6]. Therefore, it is of interest to document data on the identification of virulence genes in M. tuberculosis H37Rv using genome wide expression profiles.…”

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“…It is of interest to explore the genome data to glean valuable information on the disease causing virulence factors. Expression profiling using data at the Gene Expression Omnibus (GEO) helps to get clues for gene function [5,6]. Therefore, it is of interest to document data on the identification of virulence genes in M. tuberculosis H37Rv using genome wide expression profiles.…”

Identifying novel glioma associated pathways based on systems biology level meta-analysis

“…Till now, most of research effort has been directed at identification of important genes in glioma. In 2010, Katara et al [ 8 ] suggested that CDK4, MDM2, EGFR, PDGFA, PDGFB and PDGFRA genes can be served as biomarkers for glioma. In addition, they also found that CDKN2A, PTEN, RB1 and TP53 are the tumor suppressor genes.…”