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GP-BT-1RIFVYLBiotechnologyReady

Cell-Free Lead Biosensor Kinetic Design

A completed cell-free biotechnology study of lead dose response, time-dependent colour development, cross-reactivity, freeze-drying response, municipal-water observations, and design robustness.

Cell-Free Lead Biosensor Kinetic Design project visual
GP-BT-1RIFVYL · Biotechnology
  • Python 3.11
  • NumPy
  • Pandas
  • SciPy
  • Matplotlib
  • OpenPyXL

Project definition

Problem statement

A cell-free biosensor can produce a visible colour response while still having uncertain sensitivity, selectivity, response time, storage behaviour, and performance outside clean buffer conditions.

The biotechnology problem is to analyse those behaviours together and keep observed evidence separate from detection-limit, safety, or field-validation claims that the source data cannot support.

Project objectives

  • Validate and retain the published cell-free PbrR biosensor source workbook.
  • Fit and compare lead and zinc endpoint response models.
  • Estimate lead-model uncertainty with 2,000 bootstrap fits.
  • Fit a resource-limited kinetic model and test its later-time prediction.
  • Compare lead, zinc, mercury, freeze-dry, and municipal-water observations.
  • Explore 576 design cases and measure robustness under 1,000 parameter draws.
  • Retain complete results, figures, tests, references, and interpretation boundaries.

Project structure

Project components

01

Source validation

Checks the retained workbook byte count, SHA-256 checksum, sheet structure, and extracted row counts.

02

Endpoint analysis

Fits lead and zinc response models, compares models with AICc, calculates empirical separation, and bootstraps lead parameters.

03

Kinetic analysis

Fits the time-dependent reporter response and evaluates sustained separation and later-time prediction.

04

External-condition analysis

Compares cross-reactivity, freeze-dry response, and five municipal-water observations without expanding the claims.

05

Design study

Evaluates 576 candidate cases, identifies Pareto cases, and runs 1,000 seeded robustness samples.

06

Evidence and verification

Retains processed data, result tables, figures, tests, references, documents, and provenance.

Methodology

Project workflow

  1. 01
    Prepare the source data

    Verify the published workbook and reproduce the six processed datasets.

  2. 02
    Analyse endpoint behaviour

    Fit response models, compare zinc alternatives, calculate empirical separation, and estimate lead uncertainty.

  3. 03
    Analyse time response

    Fit the kinetic model and compare fitted, observed, and held-out behaviour.

  4. 04
    Compare operating evidence

    Review cross-reactivity, freeze-dry, municipal-water, and design-case results.

  5. 05
    Interpret the study

    Use the retained tables and figures while preserving the analytical and experimental limitations.

Demonstration scenario

The retained lead response fit gives an EC50 of 0.7528 micromolar with R squared of 0.9665. The lowest tested separated concentration is 0.01 micromolar, but it is not reported as a detection limit. Mercury remains a documented off-target response, and the early kinetic fit performs poorly on the later holdout window.

Engineering

Tools and method

Tools
The project uses Python 3.11, NumPy, Pandas, SciPy, Matplotlib, OpenPyXL for subject analysis, simulation, and results.
Data preparation
OpenPyXL and Pandas extract traceable tables from the retained published workbook.
Dose-response analysis
SciPy fits Hill and constant models and performs seeded bootstrap parameter estimation.
Kinetic model
A declared resource-limited transcription and translation model is fitted to the retained time series.
Design exploration
A deterministic parameter matrix and seeded uncertainty sampling compare response and resource tradeoffs.
Evidence
CSV, JSON, PNG, PDF, and Word files retain the source trail, calculations, results, figures, and report.
Verification
Automated tests cover provenance, extraction, equations, model behavior, retained results, and the complete workflow.

Testing

Evaluation

Evaluation measures

  • Lead EC50, Hill slope, fit error, R squared, and bootstrap intervals
  • Lead and zinc model comparison using AICc
  • Empirical separation from the control response without calling it a detection limit
  • Kinetic fit quality, sustained-separation time, and later-time holdout error
  • Lead, zinc, mercury, freeze-dry, and municipal-water comparisons
  • Pareto design cases and robustness intervals from 1,000 seeded draws
  • Automated tests, dependency audit, document checks, and non-root Docker execution

Project boundaries

  • This is a retrospective computational analysis of published data.
  • The lowest tested separated concentration is not an analytical limit of detection.
  • The five municipal-water samples do not establish method validation or water safety.
  • Mercury remains an off-target response and selectivity is not universal.
  • Three freeze-dry replicates per condition do not establish equivalence or shelf life.
  • The model does not replace ICP-MS, a validated laboratory assay, or supervised wet-lab work.

Included

  1. 01Complete cell-free biosensor analysis source code
  2. 02Published source workbook with checksum and provenance record
  3. 03Processed dose-response, kinetic, cross-reactivity, freeze-dry, and municipal-water data
  4. 04Endpoint fits, kinetic fits, model comparisons, bootstrap intervals, and design exploration
  5. 05Sixteen generated analytical figures and two attributed literature images
  6. 06Thirty-five automated tests with 97.76 percent combined coverage
  7. 07Complete project files, calculations, results, and analysis material in a private GitHub repository
  8. 0874-page project documentation in PDF and editable Word formats
  9. 096-page setup and usage guide in PDF and editable Word formats
  10. 10Sixty annotated references

Project record

No information is collected on this page.

Permanent project ID
GP-BT-1RIFVYL
Catalogued
21 Aug 2026
Completed
27 Aug 2026
Verified
27 Aug 2026
Demonstration
Included in repository

Handover

After purchase

  1. 01
    Payment is confirmed

    The project is marked unavailable and cannot be purchased again.

  2. 02
    Repository access is granted

    The buyer's submitted GitHub account receives access to the private repository.

  3. 03
    The purchase record is delivered

    The certification sheet is prepared from the reviewed buyer details and sent privately by email.