Neko

NeKo automates the construction of biological networks by integrating and prioritizing molecular interactions from various databases based on prior knowledge.

Key Features:

• Molecule input flexibility: Users can provide molecules of interest including genes, proteins, or phosphosites as input for network construction.
• Database integration: The tool integrates molecular interactions from various interaction resources and databases selected by the user.
• Interaction filtering: Users can filter interactions by direct or indirect links and signed or unsigned interactions to tailor the network.
• Flexible network building strategies: Multiple strategies are available to build networks based on prior knowledge according to user needs.
• Network analysis tools: The package provides tools for analyzing constructed interactions and networks.

Scientific Applications:

• Transcriptomics network analysis: Construction of networks based on transcriptomics data from medulloblastoma to study gene expression patterns.
• Drug synergy modeling: Modeling and analysis of drug synergies through network-based approaches to predict combination effects.
• Cellular function research: Analysis of dynamic interplay and interactions between molecular entities to gain insights into cellular functions and biological processes.

Methodology:

NeKo is implemented as a Python package that automates network construction by integrating and prioritizing molecular interactions from user-selected databases. The method involves providing molecules of interest, selecting interaction resources, and applying flexible strategies to build networks based on prior knowledge with filtering by direct or indirect links and signed or unsigned interactions.