Generate a co-expression network for genes
Generate a data profile report
Browse and explore datasets from Hugging Face
Evaluate model predictions and update leaderboard
Build, preprocess, and train machine learning models
Explore and submit NER models
This project is a GUI for the gpustack/gguf-parser-go
M-RewardBench Leaderboard
Analyze data using Pandas Profiling
Transfer GitHub repositories to Hugging Face Spaces
Generate a data report using the pandas-profiling tool
Browse and filter AI model evaluation results
statistics analysis for linear regression
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.