RegLinker

RegLinker automates curation of signaling pathways by ranking candidate interactions from a background interactome and computing constrained short paths between pathway receptors and transcription factors using regular language constraints to propose pathway extensions.


Key Features:

  • Automated Curation: Ranks candidate interactions from a background interactome for inclusion into specified signaling pathways.
  • Regular Language Constraints: Uses regular language constraints to compute multiple short paths between pathway receptors and transcription factors and to control the number of non-pathway interactions within those paths.
  • Path Computation: Computes paths within a background protein–protein interaction network connecting receptors and transcription factors.
  • Pathway Extension Proposals: Proposes new extensions to existing signaling pathways by identifying candidate interactions from computed paths.
  • Performance Evaluation: Systematically evaluates performance against five alternative approaches across 15 signaling pathways, reporting precision and recall in recovering withheld pathway proteins and interactions.

Scientific Applications:

  • Pathway Curation and Expansion: Automatically identifies and proposes new interactions for inclusion in curated signaling pathways.
  • Validation and Recovery: Recovers withheld pathway proteins and interactions to support validation of pathway annotations.
  • Complementing Manual Curation: Provides computational proposals that can complement traditional manual curation of signaling mechanisms.
  • Network Exploration: Facilitates exploration and refinement of complex protein interaction networks underlying cellular signaling.

Methodology:

Computes multiple short paths within a background interaction network between receptors and transcription factors, applies regular language constraints to control inclusion of non-pathway interactions, ranks candidate interactions from the background interactome, and evaluates performance against five alternative approaches across 15 signaling pathways measuring precision and recall for recovering withheld pathway proteins and interactions.

Topics

Details

License:
GPL-3.0
Programming Languages:
Python
Added:
11/14/2019
Last Updated:
12/12/2020

Operations

Publications

Wagner MJ, Pratapa A, Murali TM. Reconstructing signaling pathways using regular language constrained paths. Bioinformatics. 2019;35(14):i624-i633. doi:10.1093/bioinformatics/btz360. PMID:31510694. PMCID:PMC6612893.

PMID: 31510694
PMCID: PMC6612893
Funding: - National Science Foundation: CCF-1617678, DBI-1759858 - National Institute of General Medical Sciences: R01-GM095955