PINOT

PINOT integrates and quality-controls protein–protein interaction (PPI) data to support construction and analysis of human and C. elegans PPI networks from low- and high-throughput assays.


Key Features:

  • Data sources: Mines PPI information from IMEx consortium-associated repositories and WormBase to compile interaction records.
  • Live data retrieval and merging: Uses PSICQUIC to download PPI data in real time and merges records from multiple sources into a consolidated dataset.
  • Quality control and confidence scoring: Applies quality checks and assigns confidence scores based on the number of distinct detection methods and publications reporting each interaction.
  • Assay coverage: Processes PPI data derived from both low-throughput and high-throughput experimental assays.
  • Interaction annotation: Provides detection method annotations and publication provenance for each PPI entry.
  • Query-based retrieval: Retrieves PPI data corresponding to submitted lists of proteins for downstream network analysis.

Scientific Applications:

  • PPI network construction: Enables assembly of comprehensive human and C. elegans protein interaction networks from integrated sources.
  • Network-scale analysis: Supports analyses ranging from focused studies on specific proteins to broader investigations of large interaction networks.
  • Biomedical research support: Facilitates data-driven investigation of molecular interactions relevant to basic biology and studies of health and disease.

Methodology:

PINOT mines IMEx-associated repositories and WormBase, downloads PPI records via PSICQUIC in real time, merges source records, performs quality checks, and assigns confidence scores based on distinct detection methods and publications reporting each interaction.

Topics

Details

Tool Type:
api
Added:
1/9/2020
Last Updated:
1/10/2021

Operations

Publications

Tomkins J, Ferrari R, Vavouraki N, Hardy J, Lovering R, Lewis P, McGuffin L, Manzoni C. PINOT: An Intuitive Resource for Integrating Protein-Protein Interactions. Unknown Journal. 2019. doi:10.1101/788000.