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Cell Specific Gene Expression

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Cell Specific Gene Expression

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Multicellular organisms contain a variety of structurally and functionally distinct cell types, but the DNA in all the cells originated from the same parent cells. The differences in the cells can be attributed to the differential gene expression. Liver cells, whose functions include detoxification of blood, production of bile to metabolize fats, and synthesis of proteins essential for metabolism, must express a specific set of genes to perform their functions. Gene expression also varies with...

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Updated: Mar 9, 2026

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

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GE-mini: a mobile APP for large-scale gene expression visualization.

Zefang Tang¹, Chenwei Li¹, Karena Zhang¹

¹College of Life Sciences and BIOPIC, Peking University, Beijing, China.

Bioinformatics (Oxford, England)

|January 10, 2017

Summary

This summary is machine-generated.

The GE-mini app offers mobile access to integrated gene expression data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) projects. This tool facilitates easy visualization of gene expression profiles across numerous tumor and normal tissues.

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Area of Science:

Genomics
Bioinformatics
Molecular Biology

Background:

The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) projects have generated extensive RNA sequencing data.
Integrated analysis of this large-scale data across diverse tissue types is crucial for biological research.
Current data access methods may lack convenience for on-the-go researchers.

Purpose of the Study:

To develop a mobile application for visualizing integrated gene expression data.
To provide researchers with easy access to data from TCGA and GTEx projects.
To enable gene-centric expression profiling across various tumor and normal tissues.

Main Methods:

Development of the GE-mini mobile application for iOS and Android platforms.
Integration of gene expression data from TCGA and GTEx.
Implementation of a gene-centric viewer with drill-down capabilities for specific tissue types.

Main Results:

The GE-mini app provides a user-friendly interface for exploring gene expression data.
Users can visualize expression profiles for all available tumor and tissue types.
Detailed views for specific tissue types are accessible within the app.

Conclusions:

GE-mini enhances accessibility and visualization of crucial gene expression data.
The mobile tool supports biological research by simplifying data exploration.
The application is freely available for non-commercial use.