Colorectal Cancer Gene Expression and Regulatory Network Data

631 differentially expressed genes from microarray analysis of colorectal cancer, including up/down-regulated genes like jun, fos, and mapk1. The dataset identifies key regulatory transcription factors such as hnf4, nr2f1, znf219, and dr1, and uses novel statistical parameters to highlight 5 key genes (kras, araf, pik3r5, ralgds, akt3). It was created by Manika Sehgal and published in 2020.

Use Cases

• Analyze the differential expression of the 631 significant genes, such as jun and fos, to identify biomarkers for colorectal cancer progression.
• Investigate the regulatory influence of transcription factors like hnf4 and nr2f1 on the expression of the identified gene set.
• Validate the novel statistical parameters designed in the study by applying them to the network motifs associated with CRC pathophysiology.
• Examine the interactions and network motifs involving the 5 key genes (kras, araf, pik3r5, ralgds, akt3) for potential therapeutic targeting.

Strengths

• Focuses on 631 significant genes with identified expression changes in colorectal cancer.
• Identifies 5 key genes (kras, araf, pik3r5, ralgds, akt3) via novel statistical parameters.
• Includes analysis of specific regulatory transcription factors like hnf4 and nr2f1.

Limitations

• The dataset size, specific file formats, and row/column structure are not provided.
• As a focused bioinformatics study, the data may not be directly applicable for general population-level epidemiological modeling.
• Data is from a 2020 publication and may not reflect the most recent genomic discoveries.

Provenance

Source

Dryad digital repository.

Collection Method

Microarray analysis and systems biology approach integrating differential gene expression, transcription factor regulation, and network motif detection.

Freshness

Last updated 2020-06-24.