NFP

NFP characterizes annotated biological networks by quantifying their functional and topological similarity to a set of well-studied basic networks using a knowledge-based computational framework.

Key Features:

• Knowledge-based computational framework: Implements a knowledge-based computational framework for systematic comparison of biological networks.
• Comparison to basic networks: Compares target networks against a predefined set of well-studied "basic networks".
• Functional and topological similarity metrics: Measures both functional and topological similarities between networks.
• Network Fingerprint vectors: Encodes each network as a spectrum-like vector (Network Fingerprint) representing degrees of similarity to basic networks.
• Support for annotated network types: Applicable to annotated networks representing genetic, metabolic, gene regulatory, and protein-protein relationships.
• Analysis functions: Provides an extensive set of functions tailored for Network Fingerprint analysis.

Scientific Applications:

• System-level network characterization: Enables system-level characterization and comparison of annotated biological networks.
• Comparative analysis across network types: Facilitates comparison of genetic, metabolic, gene regulatory, and protein-protein interaction networks.
• Functional and topological inference: Aids understanding of underlying functionalities and topologies of biological systems through fingerprint-based comparison.

Methodology:

Implements a knowledge-based computational framework that systematically compares networks to a set of basic networks by measuring functional and topological similarities and encoding results as spectrum-like vectors (Network Fingerprints).