Generate a co-expression network for genes
Search for tagged characters in Animagine datasets
Explore and compare LLM models through interactive leaderboards and submissions
Execute commands and visualize data
Embed and use ZeroEval for evaluation tasks
Multilingual metrics for the LMSys Arena Leaderboard
Calculate VRAM requirements for running large language models
Generate benchmark plots for text generation models
Uncensored General Intelligence Leaderboard
Analyze and visualize car data
Browse and filter AI model evaluation results
Visualize amino acid changes in protein sequences interactively
Finance chatbot using vectara-agentic
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.
• 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.
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.