ArticleBioinformatics advances2025
SurprisalAnalysis: an open-source software for information-theoretic analysis of gene expression.
Article in Bioinformatics advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Authors and funding
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Abstract
Summary: SurprisalAnalysis is an open-source R package with an accompanying web-based application that utilizes Surprisal analysis to extract patterns of genes that tend to get up or down regulated as a result of a biological process. Surprisal analysis frames gene expression values in thermodynamic terms and identifies entropy-driven constraints and relevant gene weights that allow the decomposition of each gene's expression into a baseline (maximal entropy) component and one or more constraint-driven components. These components correspond to distinct biological modules or processes whose coordinated up or down regulation underlies the observed system dynamics. Availability and implementation: SurprisalAnalysis is written in R and is freely available on GitHub (https://github.com/AnniceNajafi/SurprisalAnalysis). The package is distributed under a permissive license to promote scientific collaboration and reproducibility. A web-based application with a Graphical User Interface (GUI) is hosted on https://najafiannice.shinyapps.io/surprisal_analysis_app/.
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Registered trials
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