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SurprisalAnalysis: an open-source software for information-theoretic analysis of gene expression.
1Department of Industrial and Manufacturing Engineering, California State Polytechnic University Pomona, Pomona, CA 91768, United States.
Bioinformatics Advances
|December 18, 2025
Summary
Surprisal analysis identifies gene regulation patterns by framing expression in thermodynamic terms. This R package and web app help uncover biological modules driving system dynamics.
Area of Science:
- Bioinformatics
- Computational Biology
- Systems Biology
Background:
- Gene expression analysis is crucial for understanding biological processes.
- Identifying coordinated gene regulation patterns remains a challenge.
- Thermodynamic principles offer a novel framework for analyzing biological systems.
Purpose of the Study:
- To introduce SurprisalAnalysis, an R package and web application for extracting gene regulation patterns.
- To apply Surprisal analysis, based on thermodynamic principles, to gene expression data.
- To identify biological modules and processes underlying observed system dynamics.
Main Methods:
- Utilizes Surprisal analysis, framing gene expression in thermodynamic terms.
- Identifies entropy-driven constraints and gene weights.
- Decomposes gene expression into baseline and constraint-driven components.
Main Results:
- Extracts patterns of genes that are up or down-regulated during biological processes.
- Identifies distinct biological modules or processes.
- Provides insights into the coordinated regulation underlying system dynamics.
Conclusions:
- SurprisalAnalysis offers a novel approach to understanding gene regulation.
- The R package and web application facilitate the application of Surprisal analysis.
- This method aids in uncovering the thermodynamic constraints governing biological systems.
