Graphery

Graphery provides interactive executable Python examples that demonstrate graph algorithms applied to real-world biological networks.

Key Features:

• Executable Python code: Contains executable Python code illustrating graph algorithms and concepts.
• Interactive graph execution: Enables execution of code on various graphs to observe algorithm behavior.
• Biological dataset support: Supports real-world biological network datasets for algorithm application and exploration.
• Graph and algorithm coverage: Covers foundational graph concepts and network algorithms relevant to biological network analysis.
• Code modification and program creation: Permits modification of provided code and creation of new programs for algorithm testing.
• Community-contributed resources: Accepts community-contributed datasets and example code.

Scientific Applications:

• Algorithm behavior exploration: Observing and comparing graph algorithm behaviors on biological networks.
• Network-structure analysis: Investigating structure and relationships within biological networks using graph algorithms.
• Application to real datasets: Applying graph algorithms to real-world biological network datasets to examine biological relationships.

Methodology:

Executable Python code is run interactively on graphs to illustrate and analyze network algorithms using real-world biological network datasets.