Compound Network Visualization
Explore the relationships between medicinal compounds in mushroom species
Compound Relationship Network
Legend
Network Analysis
This network visualization shows the relationships between bioactive compounds found in medicinal mushrooms. Compounds are connected based on structural similarities, functional properties, and bioactivity profiles.
Node Size: Represents the compound's relevance in medicinal applications.
Node Color: Indicates the mushroom species in which the compound is found.
Edge Type: Shows the type of relationship between compounds.
The network helps identify compound clusters with similar properties, potential synergistic effects, and compounds that might share medicinal mechanisms. This analysis supports drug discovery by identifying promising compound candidates for further investigation.
Compound Details
Select a compound in the network to view details
Related Research
Analysis Methods
Network Visualization Methods
The network visualization uses advanced graph analysis techniques to display relationships between medicinal compounds found in mushrooms. The process involves:
Graph Construction
- Compounds are represented as nodes in the graph
- Relationships between compounds are shown as edges
- Force-directed layout positions nodes based on their relationships
- Community detection algorithms identify compound clusters
Similarity Measures
- Tanimoto coefficient for structural similarity
- Functional group analysis for activity relationships
- Machine learning models for bioactivity prediction
- Natural language processing of research literature
Data Integration
The network integrates data from multiple sources:
- Chemical structure databases (PubChem, ChEMBL)
- Scientific literature from PubMed
- CMID Research Intelligence Kit
- Experimental bioactivity assays
By visualizing these relationships, researchers can identify patterns and potential new medicinal compounds that might otherwise remain hidden in isolated datasets.