Related Experiment Video
Updated: Jul 25, 2025

Linearization of the Bradford Protein Assay
Published on: April 12, 2010
Introduction to the Use of Linear and Nonlinear Regression Analysis in Quantitative Biological Assays
Stephen W Jarantow1, Eileen D Pisors2, Mark L Chiu2
1Janssen Biotherapeutics, Janssen R&D, Spring House, Pennsylvania.
Abstract:
Biological assays are essential tools in biomedical and pharmaceutical research. In simplest terms, such an assay is an analytical method used to measure or predict a response in a biological system in the presence of a given stimulus (e.g., drug). The inherent complexity involved in evaluating a biological system requires the use of rigorous and appropriate tools for data analysis. Linear and nonlinear regression models represent critically important statistical analyses used to define the relationships between variables of interest in biological systems. Recent challenges relating to the reproducibility of published data suggest the absence of standardized and routine use of statistics to support experimental results across a wide range of scientific disciplines. The current situation warrants an introductory review of basic regression concepts using current, practical examples, along with references to in-depth resources. The goal is to provide the necessary information to help standardize the analysis of biological assays in academic research and drug discovery and development, elevating their utility and increasing data transparency and reproducibility. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC.
Related Concept Videos
Calibration Curves: Linear Least Squares
For data that follow a straight line, the standard method for fitting is the linear...
Quantitative Analysis
In quantitative analysis, two key measurements are made: the sample quantity and a property proportional to the amount of the analyte (the substance being analyzed). This forms the basis of the...
Real Time RT-PCR
The real-time quantification of the number of amplified products is...
Mechanistic Models: Compartment Models in Individual and Population Analysis
Microsoft Excel: Regression Analysis
To perform regression...
Regression Analysis
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:

