Information Theoretic Analysis of Gene Expression Data // Implements Surprisal analysis for gene expression data such as RNA-seq or microarray experiments. Surprisal analysis is an information-theoretic method that decomposes gene expression data into a baseline state and constraint-associated deviations, capturing coordinated gene expression patterns under different biological conditions. References: Kravchenko- Balasha N. et al. (2014) doi:10.1371/journal.pone.0108549. Zadran S. et al. (2014) doi:10.1073/pnas.1414714111. Su Y. et al. (2019) doi:10.1371/journal.pcbi.1007034. Bogaert K. A. et al. (2018) doi:10.1371/journal.pone.0195142.