Back-PredicteR is an application which helps you to back-predict signals (response) to concentrations (results) when the relation between the response and the result is known.
This is particularly useful in laboratories when determining the concentration of unknown samples through assays such as absorbance or fluorescence measurements.
With Back-PredicteR, you can easily establish a calibration curve by measuring the response of your assay for samples of known concentration (calibration data) and fitting a regression model.
Once the calibration curve is established, you can use it to back-predict the concentration of unknown samples based on their signal.
  1. Load data or load a test data sample
  2. Choose your model(s)
  3. Visualize your results
  4. Download your results

Thomas de Marchin

Load data

Download a template or an example.

Review your data

Calibration data:

Data to back predict:


Specify the units for plotting

Select your model(s)


Linear regression:

Weighted (1/X) linear regression:

Weighted (1/X^2) linear regression:

Linear regression after (base 10) LOGARITHM transformation of both concentration and response:

Linear regression after SQUARE ROOT transformation of both concentration and response:

Quadratic regression:

Weighted (1/X) quadratic regression:

Weighted (1/X^2) quadratic regression:

Four parameters logistic Regression:

Weighted (POM) Four parameters logistic Regression:

Five parameters logistic Regression:

Weighted (POM) Five parameters logistic Regression:

Power Regression:

Weighted (POM) Power Regression:


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Release: 1.1 (April 2023)
Introduction HPLC diagram by DataBase Center for Life Science (DBCLS), distributed under a CC BY 4.0 license.

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