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Royal Society Open Science|September 19, 2018
Algorithmically probable mutations reproduce aspects of evolution, such as convergence rate, genetic memory and modularitySantiago Hernández-Orozco, Narsis A Kiani, Hector ZenilFrontiers in Computational Neuroscience|February 10, 2023
Approximations of algorithmic and structural complexity validate cognitive-behavioral experimental resultsHector Zenil, James A R Marshall, Jesper TegnérSeminars in Cell & Developmental Biology|February 7, 2016
Evaluating network inference methods in terms of their ability to preserve the topology and complexity of genetic networksNarsis A Kiani, Hector Zenil, Jakub Olczak, et al.Bioinformatics (Oxford, England)|September 30, 2017
HiDi: an efficient reverse engineering schema for large-scale dynamic regulatory network reconstruction using adaptive differentiationYue Deng, Hector Zenil, Jesper Tegnér, et al.Proceedings of the National Academy of Sciences of the United States of America|April 16, 2014
Training-free atomistic prediction of nucleosome occupancyPeter Minary, Michael LevittBehavior Research Methods|March 13, 2015
Algorithmic complexity for psychology: a user-friendly implementation of the coding theorem methodNicolas Gauvrit, Henrik Singmann, Fernando Soler-Toscano, et al.Nucleic Acids Research|October 21, 2020
crisprSQL: a novel database platform for CRISPR/Cas off-target cleavage assaysFlorian Störtz, Peter MinaryBMC Bioinformatics|October 15, 2024
Be-dataHIVE: a base editing databaseLucas Schneider, Peter MinaryEntropy (Basel, Switzerland)|July 2, 2021
Algorithmic Information Distortions in Node-Aligned and Node-Unaligned Multidimensional NetworksFelipe S Abrahão, Klaus Wehmuth, Hector Zenil, et al.Journal of Computational Biology : a Journal of Computational Molecular Cell Biology|August 24, 2010
Conformational optimization with natural degrees of freedom: a novel stochastic chain closure algorithmPeter Minary, Michael LevittPageof 6