Multi-scale stochastic organization-oriented coarse-graining exemplified on the human mitotic checkpoint

Chunyan Mu, Richard Henze, Mata Puljiz, Nishanthan Kamaleson, Jan Huwald, John Haslegrave, Pietro Speroni Di Fenizio, David Parker, Christopher Good, Jonathan E. Rowe, Peter Dittrich* (Corresponding Author), Bashar Ibrahim* (Corresponding Author)

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)
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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.
Original languageEnglish
Article number3902
Pages (from-to)1-17
Number of pages17
JournalNature Scientific Reports
Issue number1
Publication statusPublished - 7 Mar 2019

Bibliographical note

This work has been financially supported by the European Union through funding under FP7-ICT-2011-8 project HIERATIC, coordinated by J.R. Contract Grant Number: 316705. Bashar Ibrahim research was funded by the German Research Foundation (DFG) within the Collaborative Research Center 1127 ChemBioSys (SFB 1127, Project C07).

Data Availability Statement

No data availability statement.


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