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Data Visualization
CryptoCEN Network

CryptoCEN Network

Generate a co-expression network for genes

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What is CryptoCEN Network ?

The CryptoCEN Network is a data visualization tool designed for bioinformatics applications, specifically for generating and analyzing co-expression networks of genes. It enables researchers to visualize gene interactions and understand their co-expression patterns across different biological conditions or samples. This tool is particularly useful in systems biology and genomic studies to identify relationships between genes that may share similar functions or pathways.

Features

• Gene Co-expression Analysis: Identify groups of genes with similar expression patterns. • Interactive Visualization: Customize and explore gene networks with real-time updates. • Custom Data Upload: Use your own gene expression datasets for analysis. • Scalable Graphics: Handle large datasets with efficient rendering. • Export Capabilities: Save and share network visuals in multiple formats. • Intuitive Interface: Accessible design for both novice and advanced users.

How to use CryptoCEN Network ?

  1. Access the Tool: Visit the CryptoCEN Network platform and log in or sign up for an account if needed.
  2. Upload Data: Load your gene expression dataset in a compatible format (e.g., CSV, Excel).
  3. Configure Settings: Choose parameters such as correlation thresholds and network rendering options.
  4. Generate Network: Run the analysis to create the co-expression network.
  5. Visualize and Explore: Interact with the generated network to identify modules, clusters, or key nodes.
  6. Share Findings: Export visualizations or data for further analysis.

Frequently Asked Questions

1. What is a co-expression network?
A co-expression network is a graphical representation of genes (nodes) and their co-expression relationships (edges) based on their expression levels across samples.

2. What does CryptoCEN Network do?
It generates networks for genes based on their co-expression patterns and offers interactive visualization for exploration.

3. How can I save my results?
You can export your co-expression networks as images, PDFs, or graph files for sharing and further analysis.

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