Pathways Analyzer
Pathways Analyzer converts metabolic pathway data into graph representations and identifies pathway connections to generate biobrick catalogs and visualizations for synthetic biology applications in biofuel production.
Key Features:
- Metabolic Pathway Transformation: Converts metabolic pathway data from sources such as KEGG into graph data structures for computational analysis.
- Pathfinding Algorithms: Implements pathfinding algorithms to identify significant connections between compounds and reactions relevant to biofuel synthesis.
- Biobrick Catalog Creation: Analyzes pathway subsets to generate a catalog of biobricks for synthetic assembly and to guide design of engineered organisms such as E. coli.
- Visualization and Support: Generates visualizations of novel biological constructs to represent assembly structure and functionality based on selected biobricks.
Scientific Applications:
- Metabolic Pathway Redesign: Redesigns metabolic pathways in synthetic biology to enable new biosynthetic routes for biofuel precursors.
- Biofuel Production from Organic Waste: Identifies and optimizes metabolic routes to convert unconventional organic waste materials into biofuels.
- Synthetic Organism Engineering: Guides engineering of organisms such as E. coli to perform novel metabolic functions for biofuel synthesis.
Methodology:
Converting metabolic pathway data (e.g., KEGG) into graph structures; applying pathfinding algorithms to identify critical links between compounds; analyzing pathway subsets to construct a biobrick catalog; and visualizing resulting biological constructs.
Topics
Details
- License:
- Unlicense
- Maturity:
- Mature
- Cost:
- Free of charge
- Tool Type:
- command-line tool
- Operating Systems:
- Linux
- Programming Languages:
- Java, Perl, Ruby
- Added:
- 8/9/2019
- Last Updated:
- 6/16/2020
Operations
Publications
Vasquez L, Alvarado R, Orozco A. Pathways Analyzer: Design of a Tool for the Synthetic Assembly of Escherichia Coli K-12 MG1655 Bacteria for Biofuel Production. Unknown Journal. 2019. doi:10.1101/634998.
DOI: 10.1101/634998