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Multi-scale stochastic organization-oriented coarse-graining exemplified on the human mitotic checkpoint
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Henze, Richard, Mu, Chunyan, Puljiz, Mate, Kamaleson, Nishanthan, Huwald, Jan, Haslegrave, John, Speroni di Fenizio, Pietro, Parker, David, Good, Chris, Rowe, Jonathan E., Ibrahim, Bashar and Dittrich, Peter (2019) Multi-scale stochastic organization-oriented coarse-graining exemplified on the human mitotic checkpoint. Scientific Reports, 9 . 3902 . doi:10.1038/s41598-019-40648-w ISSN 2045-2322.
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Official URL: https://doi.org/10.1038/s41598-019-40648-w
Abstract
The complexity of biological models makes methods for their analysis and understanding highly desirable. Here, we demonstrate the orchestration of various novel coarse-graining methods by applying them to the mitotic spindle assembly checkpoint. We begin with a detailed fine-grained spatial model in which individual molecules are simulated moving and reacting in a three-dimensional space. A sequence of manual and automatic coarse-grainings finally leads to the coarsest deterministic and stochastic models containing only four molecular species and four states for each kinetochore, respectively. We are able to relate each more coarse-grained level to a finer one, which allows us to relate model parameters between coarse-grainings and which provides a more precise meaning for the elements of the more abstract models. Furthermore, we discuss how organizational coarse-graining can be applied to spatial dynamics by showing spatial organizations during mitotic checkpoint inactivation. We demonstrate how these models lead to insights if the model has different “meaningful” behaviors that differ in the set of (molecular) species. We conclude that understanding, modeling and analyzing complex bio-molecular systems can greatly benefit from a set of coarse-graining methods that, ideally, can be automatically applied and that allow the different levels of abstraction to be related.
| Item Type: | Journal Article | |||||||||
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| Subjects: | Q Science > QA Mathematics Q Science > QH Natural history > QH301 Biology |
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| Divisions: | Faculty of Science, Engineering and Medicine > Science > Mathematics | |||||||||
| Library of Congress Subject Headings (LCSH): | Stochastic analysis, Spindle (Cell division) | |||||||||
| Journal or Publication Title: | Scientific Reports | |||||||||
| Publisher: | Nature Publishing Group | |||||||||
| ISSN: | 2045-2322 | |||||||||
| Official Date: | 7 March 2019 | |||||||||
| Dates: |
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| Volume: | 9 | |||||||||
| Article Number: | 3902 | |||||||||
| DOI: | 10.1038/s41598-019-40648-w | |||||||||
| Status: | Peer Reviewed | |||||||||
| Publication Status: | Published | |||||||||
| Access rights to Published version: | Open Access (Creative Commons) | |||||||||
| Date of first compliant deposit: | 12 March 2019 | |||||||||
| Date of first compliant Open Access: | 13 March 2019 | |||||||||
| RIOXX Funder/Project Grant: |
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