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BIOLOGY, NEUROSCIENCE & PSYCHOLOGY
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29 resources-
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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Lawvere, F. W. (1994). Tools for the Advancement of Objective Logic: Closed Categories and Toposes. In J. Macnamara & G. E. Reyes (Eds.), The Logical Foundations of Cognition (pp. 43–56). Oxford University Press USA.
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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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Rosen, R. (1958). The representation of biological systems from the standpoint of the theory of categories. The Bulletin of Mathematical Biophysics, 20(4), 317–341. https://doi.org/10/fdgzxz
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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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Boutillier, P., Feret, J., Krivine, J., & Fontana, W. (n.d.). The Kappa Language and Kappa Tools, 52.
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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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Gromov, M. (n.d.). Structures, Learning and Ergosystems: Chapters, 159.
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Wilkinson, D. J. (2006). Stochastic Modelling for Systems Biology. CRC Press.
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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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Baez, J. C., & Otter, N. (2015). Operads and Phylogenetic Trees.
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Baas, N. A., & Emmeche, C. (1997). On Emergence and Explanation. Intellectica. Revue de l’Association Pour La Recherche Cognitive, 25(2), 67–83. https://doi.org/10/ggdf9z
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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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Gómez, J. (2009). Modeling cognitive systems with Category Theory Towards rigor in cognitive sciences.
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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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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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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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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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Heller, M. (2019). Homunculus’ Brain and Categorical Logic. ArXiv, abs/1903.03424.
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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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