Using Bipartite Networks to Determine Interactions Between Analytes and Chemical Treatments

This patent describes a novel framework for identifying and ranking chemical treatment–analyte relationships by constructing bipartite networks from LC/MS metabolomic data.

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Summary:

• Inventors: Murali G. Meena, Armin G. Geiger, Daniel A. Jacobson, Matthew J. Lane
• Patent Publication No.: US 2024/0079083 A1
• Publication Date: March 7, 2024
• Filing Date: September 8, 2023
• Applicant: UT-Battelle, LLC, Oak Ridge, TN (United States)
• OSTI Accession: 2024-0079083-A1
• Primary Institution: Oak Ridge National Laboratory (ORNL)
• Sponsoring Agency: U.S. Department of Energy (DOE), Contract No. AC05-00OR22725

Capabilities:

• Two analysis routes:
  1. Direct route for known secondary metabolites.
  2. Auxiliary route for untargeted exploration of unknown analytes.
• Workflow Components:
  • LC-MS data preprocessing
  • Bipartite network construction linking treatments and metabolites
  • Network centrality calculations (PageRank, degree, etc.)
  • Post-analysis modules for ranking, prioritization, and validation

Visual Highlight:

The network analysis diagram on page 1 shows the integration of metabolomic inputs, graph-based modeling, and post-processing to guide biological interpretation.

This approach enables data-driven discovery of bioactive metabolites and potential drug-discovery targets, with applications in fungal biology, biotechnology, and chemical screening workflows.