PlanNET

PlanNET predicts protein-protein interactions (PPIs) in Schmidtea mediterranea by homology-based inference against the Human interactome to enable transcript-centric exploration of planarian interactomes and investigation of regeneration-related pathways.

Key Features:

• Homology-based PPI prediction: Predicts protein-protein interactions using sequence homology data referenced to an established Human interactome.
• Transcriptomic scope: Applies predictions across 11 transcriptomic datasets from Schmidtea mediterranea to build comprehensive interaction networks.
• Graph storage: Stores and manages predicted interaction networks and associated sequence annotations using the Neo4j graph database.
• RNA-seq integration: Maps RNA-seq expression data onto predicted networks to provide a transcript-centric view of the interactome.
• Predicted interaction networks: Produces reconstructed interactomes for downstream pathway and network analyses.
• Reproducible methodology: Implements a reproducible approach for predicting, storing, and exploring protein interaction networks applicable to non-model organisms.

Scientific Applications:

• Interactome reconstruction: Reconstruction of predicted protein interaction networks in planarians, specifically Schmidtea mediterranea.
• Regeneration research: Investigation of molecular mechanisms and pathways potentially involved in planarian regeneration.
• Transcript-centric pathway analysis: Integration of RNA-seq data with networks to analyze expression-driven pathway activity.
• Candidate prioritization: Prioritization of interactions and pathways for experimental validation in regenerative biology studies.

Methodology:

Predicts PPIs by homology-based inference using sequence homology and a reference Human interactome; applies this approach to 11 Schmidtea mediterranea transcriptomic datasets to construct predicted interaction networks; stores networks and sequence annotations in Neo4j and integrates RNA-seq expression data onto the predicted networks.