ProphTools
ProphTools performs prioritization on heterogeneous biological networks to identify and rank candidate genes, long noncoding RNAs (lncRNAs), and drug targets using network propagation algorithms.
Key Features:
- Heterogeneous network representation: Defines prioritization problems with an arbitrary number of entity types and their interconnections within a single network model.
- Flow propagation algorithm: Implements a flow propagation algorithm inspired by Random Walk with Restarts to propagate information across network nodes.
- Weighted propagation method: Incorporates varying importance of connections and entities via a weighted propagation scheme to refine prioritization scores.
- Hybrid propagation approach: Combines flow propagation and weighted propagation methods into a hybrid strategy for heterogeneous network analysis.
- Cross-validation functionality: Provides cross-validation tests to evaluate and select optimal network configurations for specific datasets.
Scientific Applications:
- Gene-disease prioritization: Ranks genes associated with particular diseases by propagating association signals through the heterogeneous network.
- Drug repositioning: Identifies candidate drugs for repositioning by analyzing network relationships among drugs, targets, and disease entities.
- lncRNA-disease prioritization: Applies prioritization to long noncoding RNAs (lncRNAs) and in a proof-of-concept matched the performance of specialized prioritization tools while remaining general across entity types.
Methodology:
Implements a hybrid approach combining flow propagation (inspired by Random Walk with Restarts) and weighted propagation methods, and supports cross-validation to evaluate network configurations.
Topics
Details
- License:
- GPL-3.0
- Tool Type:
- command-line tool
- Operating Systems:
- Linux
- Programming Languages:
- Python
- Added:
- 7/14/2018
- Last Updated:
- 11/25/2024
Operations
Publications
Navarro C, Martínez V, Blanco A, Cano C. ProphTools: general prioritization tools for heterogeneous biological networks. GigaScience. 2017;6(12). doi:10.1093/gigascience/gix111. PMID:29186475. PMCID:PMC5751048.