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Cancer-Critical Genes II: Tumor Suppressor Genes

Cancer-Critical Genes II: Tumor Suppressor Genes

Genes usually encode proteins necessary for the proper functioning of a healthy cell. Mutations can often cause changes to the gene expression pattern, thereby altering the phenotype.
When the function of certain critical genes, especially those involved in cell cycle regulation and cell growth signaling cascades, gets disrupted, it upsets the cell cycle progression. Such cells with unchecked cell cycles start proliferating uncontrollably and eventually develop into tumors.
Such genes that act...

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Related Experiment Video

Updated: May 2, 2026

An Integrated Platform for Genome-wide Mapping of Chromatin States Using High-throughput ChIP-sequencing in Tumor Tissues

An Integrated Platform for Genome-wide Mapping of Chromatin States Using High-throughput ChIP-sequencing in Tumor Tissues

Published on: April 5, 2018

INsPeCT: INtegrative Platform for Cancer Transcriptomics.

Piyush B Madhamshettiwar¹, Stefan R Maetschke¹, Melissa J Davis¹

¹The University of Queensland, Institute for Molecular Bioscience, St. Lucia, Brisbane, Queensland, Australia. ; Australian Research Council Centre of Excellence in Bioinformatics, St. Lucia, Brisbane, Queensland, Australia.

Cancer Informatics

|March 22, 2014

Summary

This summary is machine-generated.

INsPeCT is a new, user-friendly platform for cancer transcriptomics analysis. It enables researchers without advanced computational skills to perform complex in-silico analyses of gene expression data from various sources.

Keywords:

ChIP-seq RNA-seq cancer microarray systems biology transcriptional module networks transcriptomics

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An Integrated Platform for Genome-wide Mapping of Chromatin States Using High-throughput ChIP-sequencing in Tumor Tissues

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Published on: April 5, 2018

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Cancer-Associated Fibroblasts from Mouse Mammary Tumors as Tools for Molecular and Computational Studies

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Published on: July 3, 2025

Area of Science:

Bioinformatics
Computational Biology
Cancer Research

Background:

High-throughput sequencing has generated vast cancer transcriptomics data.
Computational analysis and data integration are significant bottlenecks in cancer research.
Existing tools often require advanced computational expertise and infrastructure.

Purpose of the Study:

To present INsPeCT, an integrative platform for cancer transcriptomics.
To enable researchers with basic computer skills to perform in-silico analyses.
To facilitate comprehensive analysis of microarray, ChIP-seq, and RNA-seq data.

Main Methods:

INsPeCT offers automated workflows for data analysis.
Includes RMaNI (regulatory module network inference) for cancer subtype-specific networks.
Incorporates WGCNA (weighted gene co-expression network analysis) for gene module identification.

Main Results:

INsPeCT allows comprehensive in-silico analysis of transcriptomic data.
Users can select genes for advanced functional analysis.
Automated workflows facilitate the inference of gene modules and networks.

Conclusions:

INsPeCT democratizes computational analysis in cancer transcriptomics.
The platform supports user-friendly, integrative, and automated analytical approaches.
INsPeCT is freely available for researchers to advance cancer biology and translational research.