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scientific-network-analysis

Construct and analyze biological networks with NetworkX to reveal hubs and modular structure.

3|1|Updated Feb 11, 2026

Search Tags:#visualization #centrality #community-detection #network-analysis #graph-construction #ppi-network #psp-diagram

Ready to run

npx skills add https://github.com/nahisaho/satori --skill scientific-network-analysis

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: scientific-network-analysis
Source: https://github.com/nahisaho/satori/tree/main/src/.github/skills/scientific-network-analysis
Command: npx skills add https://github.com/nahisaho/satori --skill scientific-network-analysis

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires networkx, pandas, numpy, matplotlib.

What problem does it solve?

Networks in biological data require structured graphs to reveal key nodes and modules; this skill provides end-to-end construction, analysis, and visualization.

Core Features & Use Cases

Graph construction from edge lists and correlation matrices
Centrality, hub detection, and community detection
PSP path diagrams and standard network visualizations

Quick Start

Build a simple network from an edge list and run centrality, community detection, and visualization in one step.

Frequently Asked Questions about scientific-network-analysis

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I construct and analyze a PPI network from a correlation matrix?▼

Network construction from a correlation matrix is done using NetworkX to build a structured graph, which then allows for centrality and community detection to reveal key nodes and modules in biological data.

Can I detect hub nodes and modular structure in biological networks using NetworkX?▼

Yes, hub node detection and modular structure analysis are performed using NetworkX centrality measures and community detection algorithms on biological datasets to identify key components.

What is the best way to visualize network analysis results from an edge list?▼

Visualizing network analysis results from an edge list is best handled by generating standard network figures and PSP path diagrams using matplotlib to reveal graph structures and relationships.

Do I need pandas and numpy to run network analysis on biological datasets?▼

Yes, pandas and numpy are required dependencies alongside NetworkX and matplotlib to construct graphs, analyze centrality, and output CSVs and figures for downstream analysis.

How do I build a network from an edge list and run centrality analysis in one step?▼

You can build a network from an edge list and execute centrality, community detection, and visualization in a single step to quickly reveal hub nodes and modular structures.

What downstream outputs can I expect from graph construction and community detection?▼

Downstream outputs from graph construction and community detection include CSV files containing centrality metrics and matplotlib figures visualizing the PSP diagrams and network structure.