Protocol | Published:

Nonlinear least-squares data fitting in Excel spreadsheets

Nature Protocols volume 5, pages 267281 (2010) | Download Citation

Abstract

We describe an intuitive and rapid procedure for analyzing experimental data by nonlinear least-squares fitting (NLSF) in the most widely used spreadsheet program. Experimental data in x/y form and data calculated from a regression equation are inputted and plotted in a Microsoft Excel worksheet, and the sum of squared residuals is computed and minimized using the Solver add-in to obtain the set of parameter values that best describes the experimental data. The confidence of best-fit values is then visualized and assessed in a generally applicable and easily comprehensible way. Every user familiar with the most basic functions of Excel will be able to implement this protocol, without previous experience in data fitting or programming and without additional costs for specialist software. The application of this tool is exemplified using the well-known Michaelis–Menten equation characterizing simple enzyme kinetics. Only slight modifications are required to adapt the protocol to virtually any other kind of dataset or regression equation. The entire protocol takes 1 h.

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Acknowledgements

We thank Professor Heiko Heerklotz (University of Toronto, Canada), Dr. Alekos Tsamaloukas (Rensselaer Polytechnic Institute, USA), Natalie Bordag (FMP) and Martin Kemmer (23karat GmbH, Berlin, Germany) for helpful discussions and constructive comments on the manuscript. This work was supported by grant KE 1478/1-1 from the Deutsche Forschungsgemeinschaft (DFG) to S.K.

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Affiliations

  1. Leibniz Institute of Molecular Pharmacology FMP, Berlin, Germany.

    • Gerdi Kemmer
    •  & Sandro Keller

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Contributions

G.K. designed and performed experiments, analyzed and fitted data, and wrote the manuscript. S.K. designed experiments, analyzed data and wrote the manuscript.

Corresponding author

Correspondence to Sandro Keller.

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DOI

https://doi.org/10.1038/nprot.2009.182

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