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BIOLOGY, NEUROSCIENCE & PSYCHOLOGY
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Andreatta, M., Ehresmann, A., Guitart, R., & Mazzola, G. (2013). Towards a Categorical Theory of Creativity for Music, Discourse, and Cognition. In J. Yust, J. Wild, & J. A. Burgoyne (Eds.), Mathematics and Computation in Music (pp. 19–37). Berlin, Heidelberg: Springer. https://doi.org/10/ggdndz
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Baez, J. C., & Otter, N. (2015). Operads and Phylogenetic Trees.
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Boutillier, P., Maasha, M., Li, X., Medina-Abarca, H. F., Krivine, J., Feret, J., … Fontana, W. (2018). The Kappa platform for rule-based modeling. Bioinformatics, 34(13), i583–i592. https://doi.org/10/gdrhw6
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Brown, R., & Porter, T. (2008). Category Theory and Higher Dimensional Algebra: potential descriptive tools in neuroscience. ArXiv:Math/0306223. Retrieved from http://arxiv.org/abs/math/0306223
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Danos, V., Feret, J., Fontana, W., Harmer, R., & Krivine, J. (2008). Rule-Based Modelling, Symmetries, Refinements. In J. Fisher (Ed.), Formal Methods in Systems Biology (pp. 103–122). Berlin, Heidelberg: Springer. https://doi.org/10/dc5k68
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Ehresmann, A. C. (2018). Applications of Categories to Biology and Cognition. https://doi.org/10/ggdf93
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Ehresmann, A. C. (2012). MENS, an Info-Computational Model for (Neuro-)cognitive Systems Capable of Creativity. Entropy, 14, 1703–1716. https://doi.org/10/ggdf9t
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Ehresmann, A. C., & Gomez-Ramirez, J. (2015). Conciliating neuroscience and phenomenology via category theory. Progress in Biophysics and Molecular Biology, 119(3), 347–359. https://doi.org/10/f75jzr
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Engeler, E. (2008). Neural Algebra and Consciousness: A Theory of Structural Functionality in Neural Nets. In K. Horimoto, G. Regensburger, M. Rosenkranz, & H. Yoshida (Eds.), Algebraic Biology (Vol. 5147, pp. 96–109). Berlin, Heidelberg: Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-85101-1_8
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Fages, F., Calzone, L., & Soliman, S. (2006). BIOCHAM: an environment for modeling biological systems and formalizing experimental knowledge. Bioinformatics, 22(14), 1805–1807. https://doi.org/10/dfv
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Fages, F. (2014). Cells as Machines: Towards Deciphering Biochemical Programs in the Cell. In R. Natarajan (Ed.), Distributed Computing and Internet Technology (pp. 50–67). Cham: Springer International Publishing. https://doi.org/10/ggdf96
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Fages, F., Calzone, L., Chabrier-Rivier, N., & Soliman, S. (2006). Machine Learning Biochemical Networks from Temporal Logic Properties. In C. Priami & G. Plotkin (Eds.), Transactions on Computational Systems Biology VI (pp. 68–94). Berlin, Heidelberg: Springer. https://doi.org/10/dd8
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Fages, F., Martinez, T., Rosenblueth, D. A., & Soliman, S. (2018). Influence Networks Compared with Reaction Networks: Semantics, Expressivity and Attractors. IEEE/ACM Trans. Comput. Biol. Bioinformatics, 15(4), 1138–1151. https://doi.org/10/ggdf94
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Gómez, J. (2009). Modeling cognitive systems with Category Theory Towards rigor in cognitive sciences.
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Healy, M. J. (2000). Category theory applied to neural modeling and graphical representations. In Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium (pp. 35–40 vol.3). Como, Italy: IEEE. https://doi.org/10/dr29pc
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Heller, M. (2019). Homunculus’ Brain and Categorical Logic. ArXiv, abs/1903.03424.
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Kato, G. C., & Struppa, D. C. (2002). Category Theory and Consciousness. https://doi.org/10/ggdf92
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Mascari, J.-F., Giacchero, D., & Sfakianakis, N. (2017). Symetries and asymetries of the immune system response: A categorification approach. In 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (pp. 1451–1454). https://doi.org/10/ggdnd3
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Mazzola, G. (2002). The Topos of Music: Geometric Logic of Concepts, Theory, and Performance. Birkhäuser Basel. https://doi.org/10.1007/978-3-0348-8141-8
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Philipona, D., O’Regan, J., & Nadal, J.-P. (2003). Is There Something Out There? Inferring Space from Sensorimotor Dependencies. Neural Computation, 15, 2029–2049. https://doi.org/10/frg7gs
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