bio-data-visualization-network-visualization

Version Compatibility

Reference examples tested with: matplotlib 3.8+, numpy 1.26+

Before using code patterns, verify installed versions match. If versions differ:

• Python: pip show <package> then help(module.function) to check signatures

If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.

Network Visualization

"Visualize a biological network" → Display protein-protein interaction, gene regulatory, or pathway networks as node-edge graphs.

• Python: networkx + matplotlib, pyvis.network.Network() (interactive)
• CLI: Cytoscape with py4cytoscape for programmatic control

Visualize biological networks with static (matplotlib), interactive (PyVis), and publication-quality (Cytoscape) approaches.

NetworkX + Matplotlib

Basic Network Plot

import networkx as nx
import matplotlib.pyplot as plt
import numpy as np

G = nx.karate_club_graph()

fig, ax = plt.subplots(figsize=(10, 8))
pos = nx.spring_layout(G, seed=42)
nx.draw_networkx(G, pos, node_size=300, node_color='#4DBBD5', edge_color='gray',
                 font_size=8, width=0.8, ax=ax)
ax.set_title('Network')
ax.axis('off')
plt.tight_layout()
plt.savefig('network.png', dpi=300, bbox_inches='tight')

Layout Algorithms

Layout	Function	Best For
Spring	nx.spring_layout(G, k=1.5, seed=42)	General-purpose, force-directed
Kamada-Kawai	nx.kamada_kawai_layout(G)	Small-medium networks, clean separation
Circular	nx.circular_layout(G)	Showing all connections, small networks
Shell	nx.shell_layout(G, nlist=[core, periphery])	Hub-spoke topology
Spectral	nx.spectral_layout(G)	Revealing clusters

The spring layout k parameter controls node spacing: increase for sparse layouts, decrease for compact. Always set seed for reproducibility.

Degree-Based Node Sizing

def draw_network(G, pos=None, title='', ax=None, node_cmap='YlOrRd'):
    '''Draw network with degree-proportional node sizes and colored by degree'''
    if pos is None:
        pos = nx.spring_layout(G, seed=42, k=1.5)
    if ax is None:
        fig, ax = plt.subplots(figsize=(10, 8))

    degrees = dict(G.degree())
    node_sizes = [100 + degrees[n] * 150 for n in G.nodes()]
    node_colors = [degrees[n] for n in G.nodes()]

    nx.draw_networkx_edges(G, pos, alpha=0.3, edge_color='gray', width=0.8, ax=ax)
    nodes = nx.draw_networkx_nodes(G, pos, node_size=node_sizes, node_color=node_colors,
                                   cmap=plt.cm.get_cmap(node_cmap), edgecolors='black',
                                   linewidths=0.5, ax=ax)
    nx.draw_networkx_labels(G, pos, font_size=7, ax=ax)

    plt.colorbar(nodes, ax=ax, label='Degree', shrink=0.8)
    ax.set_title(title)
    ax.axis('off')
    return ax