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.

Documentation