Examples

Interactive Jupyter notebooks demonstrating FlatProt's capabilities, from basic protein projections to advanced overlay visualizations.

🚀 Getting Started

Quick Start

  • New to FlatProt? Start with the Basic Projection example
  • Want to compare proteins? Try the Protein Alignment example
  • Need publication graphics? Use the Protein Overlay example

Running Examples

  • Google Colab: Click any badge below - setup is automatic!
  • Local Jupyter: Clone the repo and run notebooks directly
  • Command Line: Extract the core commands marked with 🎯

📖 Core Examples

Basic Protein Projection

Open In Colab

Perfect for beginners! Ultra-clean example using native Jupyter shell commands (!flatprot project). Creates 2D visualizations with minimal complexity.

Protein Family Overlay

Open In Colab

One command, multiple proteins! Ultra-simplified demonstration using shell commands. Shows automatic clustering, alignment, and family visualization.

Protein Alignment and Projection

Open In Colab

Compare related protein structures with consistent alignment! Shows how to align three similar toxins to a reference database and create side-by-side projections with consistent orientation.

Protein Domain Splitting

Open In Colab

Extract and visualize protein domains separately! Demonstrates how to use flatprot split to extract structural domains and create individual visualizations for comparative analysis.

🔬 Advanced Examples

UniProt to AlphaFold Visualization

Open In Colab

From UniProt ID to visualization in minutes! Automatically downloads AlphaFold structures, extracts functional annotations from UniProt, aligns to protein families, and creates publication-ready visualizations. Features automatic binding site detection and multiple visualization variants.

Custom Styling and Annotations

Open In Colab

Create protein visualizations with custom colors and annotations! Demonstrates modern color schemes, point/line/area annotations, and style variations. Includes a side-by-side comparison gallery showing different aesthetic approaches.

Disulfide Bond Detection

Open In Colab

Automated disulfide bond analysis! Shows how to detect disulfide bonds, generate annotation files programmatically, and create annotated visualizations. Perfect example of structural bioinformatics automation.

💡 Learning Path

🚀 Recommended (Clean & Simple): 1. Start: Basic Projection - Pure shell commands, minimal complexity 2. Align: Protein Alignment and Projection - Structure comparison with consistent alignment 3. Domains: Protein Domain Splitting - Extract and visualize domains separately 4. Features: Disulfide Bond Detection - Automated bond analysis + annotations 5. Scale up: Protein Family Overlay - Multi-protein visualization

🔬 Advanced (Full-Featured): 6. Customize: Custom Styling - Color schemes and annotations 7. Research: UniProt to AlphaFold - Complete research workflow

🔧 Technical Notes

About Notebook Complexity: Much of the code in these notebooks handles automatic Google Colab setup (dependency installation, data download, environment configuration). The actual FlatProt usage is typically just 1-3 commands per example!

Essential Commands (in Jupyter):

# Basic projection (SVG output)
!flatprot project structure.cif -o output.svg

# Multi-protein overlay (PNG/PDF available)
!flatprot overlay "structures/*.cif" -o overlay.png --family 3000114 --clustering

# Structure alignment
!flatprot align structure.cif matrix.npy info.json

Output Formats: - flatprot project → SVG only (vector graphics, perfect for notebooks) - flatprot overlay → SVG, PNG, PDF (PNG great for Colab compatibility) - flatprot split → SVG only

Automation: Notebooks are automatically generated from Python source files using scripts/create-notebooks.sh and jupytext.