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Sci. Signal., 16 April 2013
[DOI: 10.1126/scisignal.2003849]

Using Partial Least Squares Regression to Analyze Cellular Response Data (Slides, Data File, Answer Key)

Pamela K. Kreeger*

*Corresponding author. E-mail: kreeger{at}

Slides. Using Partial Least Squares Regression (PLSR) to Analyze Cellular Response Data. This PDF contains the slides for a lecture on PLSR, which was part of an introductory systems biology course focused on implementation and analysis of systems biology models. The slides introduce students to the concept of PLSR and then describe the application of the method to specific examples from the literature.

Technical Details

Format: PDF

Size: 3.5 MB

Requirements: Adobe PDF Reader

[Access Slides]

PLS Data. This Excel spreadsheet includes data for completing the problem set. Each row indicates a unique sample; the values in the columns represent the values for the associated signaling time points (X matrix) and the percentage of cells that were dead (Y matrix). This problem set solution uses a publicly available MATLAB script for NIPALS (

Technical Details

Format: Excel (xls)

Size: 19 KB

Requirements: Microsoft Excel

[Access Data Set]

Answer Key. The answer key in PDF format for the problem set can be obtained by completing the "Request Resource" form.

Limits for Use

Cost: Free

Rights: This material may be downloaded for noncommercial, course-teaching purposes only, provided credit to Science Signaling is included by listing the citation for the Teaching Resource.

Citation: P. K. Kreeger, Using Partial Least Squares Regression to Analyze Cellular Response Data. Sci. Signal. 6, tr7 (2013).

© 2013 American Association for the Advancement of Science

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