CANAlization: Control & Redundancy in Boolean Networks

This package implements a series of methods used to study control, canalization and redundancy in Boolean Networks.

Citation:

If you use cana in your research, please cite us and check out our related papers below!

• A.M. Marcus, J.C. Rozum, H. Sizek, L.M. Rocha [2025]. "CANA v1.0.0: efficient quantification of canalization in automata networks". Bioinformatics. btaf461. doi: 10.1093/bioinformatics/btaf461

• R.B. Correia, A.J. Gates, X. Wang, L.M. Rocha [2018]. "CANA: A python package for quantifying control and canalization in Boolean Networks". Frontiers in Physiology. 9: 1046. doi: 10.3389/fphys.2018.01046

Installation:

Latest stable release

    pip install cana

Manuscript-specific version

    pip install cana=1.0.0

Latest development release on GitHub

    pip install git+https://github.com/CASCI-lab/CANA

Windows

CANA includes compiled C extensions. On Windows, installing CANA requires a C/C++ compiler. If you do not already have one installed, install the Microsoft C++ Build Tools with the Desktop development with C++ workload selected.

See the Cython documentation for additional information about compiling Python extensions on Windows.

Docs:

The full documentation can be found at: casci-lab.github.io/CANA/

Papers with the Theory, Formulations, and Analytical Examples:

• F.X. Costa, J.C. Rozum, A.M. Marcus, L.M. Rocha [2023]. "Effective Connectivity and Bias Entropy Improve Prediction of Dynamical Regime in Automata Networks". Entropy. 25(2):374. doi: 10.3390/e25020374.

• S. Manicka, M. Marques-Pita, L.M. Rocha [2022]. "Effective connectivity determines the critical dynamics of biochemical networks". Journal of the Royal Society Interface. 19(186)20210659. doi: 10.1098/rsif.2021.0659.

• A.J. Gates, R.B. Correia, X. Wang, L.M. Rocha [2021]. "The effective graph reveals redundancy, canalization, and control pathways in biochemical regulation and signaling". Proceedings of the National Academy of Sciences (PNAS). 118(12). doi: 10.1073/pnas.20225981186

• A. Gates and L.M. Rocha. [2016] "Control of complex networks requires both structure and dynamics." Scientific Reports 6, 24456. doi: 10.1038/srep24456.

• A. Gates and L.M. Rocha [2014]. "Structure and dynamics affect the controllability of complex systems: a Preliminary Study". Artificial Life 14: Proceedings of the Fourteenth International Conference on the Synthesis and Simulation of Living Systems: 429-430, MIT Press.

• M. Marques-Pita and L.M. Rocha [2013]. "Canalization and control in automata networks: body segmentation in Drosophila Melanogaster". PLoS ONE, 8(3): e55946. doi:10.1371/journal.pone.0055946.

Credits:

CANA was originally written by Rion Brattig Correia and Alexander Gates, and has been developed with the help of many others. Thanks to everyone who has improved CANA by contributing code, bug reports (and fixes), documentation, and input on design, and features.

Original Authors

• Rion Brattig Correia, github: rionbr
• Alexander Gates, github: ajgates42

Contributors

• Srikanth Iyer, github: srikanth-iyer
• Kyu Hyong Park, github: kyuhyongpark
• Yoshiaki Fujita, github: yoshiakifujita
• Jordan C. Rozum, github: jcrozum
• Felipe Xavier Costa, github: fxcosta-phd
• Austin Marcus, github: austin-marcus
• Xuan Wang, github: xuan-w
• Thomas Parmer, github: tjparmer
• Etienne Nzabarushimana
• Luis M. Rocha

Support

Those who have contributed to CANA have received support throughout the years from a variety of sources. We list them below. If you have provided support to CANA and a support acknowledgment does not appear below, please help us remedy the situation, and similarly, please let us know if you'd like something modified or corrected.

Research Groups

CANA was developed with support from the following:

• CASCI, Indiana University, Bloomington, IN; PI: Luis M. Rocha
• CAPES Foundation, Ministry of Education of Brazil, Brasília, Brazil; Rion B. Correia.

Changelog

Master

• BooleanFunction: store and convert among bit_lut, one-/two-symbol schemata, and positional expressions; build BooleanNode from any of them
• High-k support: dense-LUT / coverage guardrails; sampled redundancy, activities, sensitivity, and bias
• Expression → primes (Quine–McCluskey, PySAT Primer-B / unate shortcuts)
• Fixed canalizing map (CM/DCM): LUT roundtrip, canonical builder with simplification, topology-based evaluation, and visualization
• Schemata order and k_r/k_s values are now identical across processes (prime implicants sorted, sums use math.fsum); last digits of some k_r/k_s means change accordingly
• Fixed input_symmetry_mean failing on a fresh node
• Added calculation of distinct and raw symmetry
• Added visualization routines to drawing (effective graph and conditional effective graph)

v1.0.1

• Add Python 3.13 support (schematodes 1.0.1, PyO3 0.22)

v1.0.0

• A.M. Marcus, J.C. Rozum, H. Sizek, L.M. Rocha [2025]. "CANA v1.0.0: efficient quantification of canalization in automata networks". Bioinformatics. btaf461. doi: 10.1093/bioinformatics/btaf461

v0.1

• Canalization methods ported to Cython

v0.0.4

• Pep8 and python3
• Pinned controllability methods

v0.0.3

• Bugfixes

v0.0.2

• Networkx 2.1 compatibility
• Inclusion of tutorials
• Derrida curve

v.0.0.1

• Control (FVS, MDS, CSTG) methods.
• Canalization methods.
• Implementation ported to public package.