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Mathematical Justification of Expression-Based Pathway Activation Scoring (PAS).

Alexander M Aliper1,2,3, Michael B Korzinkin2,3, Natalia B Kuzmina4

  • 1Drug Research and Design Department, Pathway Pharmaceuticals, Wan Chai, Hong Kong, Hong Kong SAR.

Methods in Molecular Biology (Clifton, N.J.)
|August 30, 2017
PubMed
Summary

Pathway activation scores (PAS) are kinetically justified and closely align with complex stiffness analysis. A pathway-based approach improves correlation between transcriptome data from different techniques.

Keywords:
Mitogenic cell signalingParameter sensitivity/stiffness analysisProtein-protein interactionRNA microarray analysisSystems biology

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Area of Science:

  • Systems Biology
  • Bioinformatics
  • Computational Biology

Background:

  • Kinetic modeling of cell signaling pathways is sophisticated but often lacks practical biomedical value.
  • Recent advances apply signaling pathway science to personalized medicine, evaluating pathological changes using gene expression and pathway interaction data.
  • Algorithms like OncoFinder assess molecular pathway activation from gene/protein expression data.

Purpose of the Study:

  • To kinetically justify the pathway activation score (PAS) by comparing it with stiffness analysis.
  • To demonstrate the utility of a pathway-based approach over individual gene analysis for correlating transcriptome data.

Main Methods:

  • Stiffness analysis of full-scaled kinetic models to determine gene importance coefficients.
  • Calculation of expression-based pathway activation score (PAS).
  • Comparison of gene importance coefficients from stiffness analysis with PAS values.
  • Analysis of correlations between transcriptome samples using a pathway-based approach versus individual gene analysis.

Main Results:

  • Gene importance coefficients from time-consuming stiffness analysis differ by at most 30% from the easier-to-calculate PAS.
  • The pathway activation score (PAS) is kinetically justified.
  • A pathway-based approach restores correlations between samples analyzed with different transcriptome techniques, leveraging the law of large numbers.

Conclusions:

  • The pathway activation score (PAS) provides a kinetically valid and computationally efficient method for assessing pathway activation.
  • A pathway-based analysis enhances the reliability and comparability of gene expression data across different experimental techniques.