15N Tracing Analyzer

A focused tool for researchers analyzing 15N tracer data to quantify enrichment and fluxes in metabolic studies in labs.

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About This Tool

This tool analyzes isotopic tracer data from 15N experiments to provide corrected enrichment metrics and, optionally, simple flux estimates. It targets researchers in metabolomics, biochemistry, and systems biology who need transparent, reproducible analysis of isotope labeling data when designing or interpreting tracer experiments.
Conceptually, it parses a tabular dataset, applies natural abundance correction on 15N signals, converts to fractional enrichment, and aggregates results by metabolite and time point. When a network of metabolites is provided via inputs or assumed, it estimates fluxes using a simple mass-balance model and least-squares minimization; uncertainty can be approximated via bootstrap resampling.
Core features include data ingestion; 15N correction; fractional enrichment calculation; optional flux estimation; exportable results; and support for multiple timepoints. The tool uses standard isotopic definitions and SI units, enabling cross-lab use and reproducible documentation.
Use cases include tracking label incorporation over time, comparing conditions, and validating pathway activity. It differentiates by offering an integrated correction and minimal modeling pipeline suitable for publication-ready figures and reproducible analyses.

How to Use

  1. Provide inputs: upload data CSV with required columns (sample_id, metabolite, time, enrichment_15N) and optional correction factors.
  2. Choose analysis_method: isotopomer or mass-balance (default).
  3. Run calculation: execute workflow to produce corrected enrichment and flux estimates.
  4. Review outputs: inspect per-metabolite enrichment, time trends, and summary statistics.
  5. Export results: download CSV/JSON and, if enabled, bootstrap uncertainty.
How to use advanced tool for analysing 15n tracing data

Frequently Asked Questions

Find Quick Answers

What inputs are required for analysis?
A CSV with columns sample_id, metabolite, time, enrichment_15N is required. Optional correction_factors and network_constraints can refine results. Time units must be consistent across the dataset.
Does it correct for natural abundance?
Yes. The tool applies 15N natural abundance correction before calculating enrichment metrics, ensuring results reflect true tracer incorporation rather than background signal.
What flux estimation methods are supported?
A simple mass-balance approach estimates fluxes under defined constraints using least-squares. Bootstrap can be enabled to provide uncertainty estimates without requiring full kinetic modeling.
Can it handle multi-metabolite networks?
Yes, provided you supply a network or constraints. The tool performs flux estimation within the specified network and reports per-metabolite flux estimates and fit quality, with caveats about data density.

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