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| Auteurs principaux: | , |
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| Format: | Preprint |
| Publié: |
2025
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| Accès en ligne: | https://arxiv.org/abs/2509.03671 |
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| _version_ | 1866912739224453120 |
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| author | Toit, Nadine du Müller-Nedebock, Kristian K. |
| author_facet | Toit, Nadine du Müller-Nedebock, Kristian K. |
| contents | This paper builds on a recently introduced dynamical networking framework, applying it to model motor-driven transport along cytoskeletal filament networks. Within this approach, the networking functional describes the periodic binding and unbinding of motors to available filament sites,whilst accounting for all possible pairing, enabling a field-theoretic treatment of constrained motion in complex networks. In this application, the dynamical networking theory is introduced into a Martin-Siggia-Rose representation of the Langevin dynamics describing the motion of a motor protein and its cargo. Results are presented in a collective description of motors on a network, for two different scenarios, namely homogeneous and non-homogeneous networks. A diffusion coefficient is presented for homogeneous networks, whilst it is shown that various possibilities remain for disordered averaging over network densities for non-homogeneous networks. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_03671 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Applying a Gaussian networking theory to model motor-driven transport along cytoskeletal filaments Toit, Nadine du Müller-Nedebock, Kristian K. Soft Condensed Matter Biological Physics This paper builds on a recently introduced dynamical networking framework, applying it to model motor-driven transport along cytoskeletal filament networks. Within this approach, the networking functional describes the periodic binding and unbinding of motors to available filament sites,whilst accounting for all possible pairing, enabling a field-theoretic treatment of constrained motion in complex networks. In this application, the dynamical networking theory is introduced into a Martin-Siggia-Rose representation of the Langevin dynamics describing the motion of a motor protein and its cargo. Results are presented in a collective description of motors on a network, for two different scenarios, namely homogeneous and non-homogeneous networks. A diffusion coefficient is presented for homogeneous networks, whilst it is shown that various possibilities remain for disordered averaging over network densities for non-homogeneous networks. |
| title | Applying a Gaussian networking theory to model motor-driven transport along cytoskeletal filaments |
| topic | Soft Condensed Matter Biological Physics |
| url | https://arxiv.org/abs/2509.03671 |