Julian Charles Shillcock
Ch. des Mines 9
+41 21 693 96 79
Office: B1 4 279.050
EPFL > VPA > VPA-AVP-CP > BBP > BBP-CORE
Web site: Web site: https://www.epfl.ch/research/domains/bluebrain/
+41 21 693 96 79
EPFL > SV > SV-SSV > SSV-ENS
Web site: Web site: https://sv.epfl.ch/education
Web site: Web site: https://go.epfl.ch/edne
Fields of expertise
Mesoscale simulations of soft matter
BiographyI received my PhD at Simon Fraser University in Canada for work on Monte Carlo simulations of liquid crystal phase transitions and the elastic properties of fluid and polymerized membranes.
Then I moved to the Max Planck Institute of Colloids and Interfaces, Germany, and was a group leader for five years applying coarse-grained simulation techniques - principally Dissipative Particle Dynamics (DPD) and Brownian Dynamics - to equilibrium and dynamic properties of fluid lipid membranes. A major target of this research was to reveal the molecular rearrangements that occur during vesicle fusion. During this time, I developed a parallel DPD code that is still being used by several universities (https://github.com/Osprey-DPD/osprey-dpd)
I was then an Associate Professor at MEMPHYS in the Department of Physics and Chemistry, University of Southern Denmark. In a previous life, I performed mission analysis for communication satellites, designed and wrote software for satellite simulations (British Aerospace, 1986-1990), and developed commercial fluid simulation software (Accelrys, Inc., 1998-1999).
I joined the Blue Brain Project in 2011 to develop mesoscale simulations of cellular dynamics, and am now studying the structure of biomolecular condensates using mesoscale simulations. I teach Master's and PhD courses in computational cell biology and biophysics, and was awarded the Polysphère prize for Best Teacher in Life Sciences in 2021.
Pour l'excellence de son enseignement
Macromolecular Crowding Is Surprisingly Unable to Deform the Structure of a Model Biomolecular CondensateBiology-Basel. 2023-02-01. DOI : 10.3390/biology12020181.
Model biomolecular condensates have heterogeneous structure quantitatively dependent on the interaction profile of their constituent macromoleculesSoft Matter. 2022-08-25. DOI : 10.1039/d2sm00387b.
Computational synthesis of cortical dendritic morphologiesCell Reports. 2022-04-05. DOI : 10.1016/j.celrep.2022.110586.
Investigating the morphological transitions in an associative surfactant ternary systemSoft Matter. 2022-03-07. DOI : 10.1039/d1sm01668g.
Coupling Bulk Phase Separation of Disordered Proteins to Membrane Domain Formation in Molecular Simulations on a Bespoke Compute FabricMembranes. 2022-01-01. DOI : 10.3390/membranes12010017.
Non-monotonic fibril surface occlusion by GFP tags from coarse-grained molecular simulationsComputational and Structural Biotechnology Journal. 2022. DOI : 10.1016/j.csbj.2021.12.017.
Computational Approaches to Explore Bacterial Toxin Entry into the Host CellToxins. 2021-06-28. DOI : 10.3390/toxins13070449.
Phase behaviour and structure of a model biomolecular condensateSoft Matter. 2020-07-21. DOI : 10.1039/d0sm00813c.
Characterization of Protein-Membrane Interfaces through a Synergistic Computational-Experimental ApproachLausanne, EPFL, 2020. DOI : 10.5075/epfl-thesis-7278.
Mechanism of Shiga Toxin Clustering on Membranes (vol 11, pg 314, 2017)ACS NANO. 2018. DOI : 10.1021/acsnano.8b00537.
A Topological Representation of Branching Neuronal MorphologiesNEUROINFORMATICS. 2018. DOI : 10.1007/s12021-017-9341-1.
Clustering on Membranes: Fluctuations and MoreTrends in Cell Biology. 2018. DOI : 10.1016/j.tcb.2018.01.009.
Neuronal morphologies: the shapes of thoughtsLausanne, EPFL, 2018. DOI : 10.5075/epfl-thesis-8255.
Bio-physically plausible visualization of highly scattering fluorescent neocortical models for in silico experimentationBmc Bioinformatics. 2017. DOI : 10.1186/s12859-016-1444-4.
Mechanism of Shiga Toxin Clustering on MembranesACS Nano. 2017. DOI : 10.1021/acsnano.6b05706.
Framework for efficient synthesis of spatially embedded morphologiesPhysical Review E. 2016. DOI : 10.1103/PhysRevE.94.023315.
Membrane invagination induced by Shiga toxin B-subunit: from molecular structure to tube formationSoft Matter. 2016. DOI : 10.1039/C6SM00464D.
Reconstructing the brain: from image stacks to neuron synthesisBrain Informatics. 2016. DOI : 10.1007/s40708-016-0041-7.
In situ synthesis and simulation of polydisperse amphiphilic membranesInternational Journal of Advances in Engineering Sciences and Applied Mathematics. 2015. DOI : 10.1007/s12572-015-0156-8.
The neocortical microcircuit collaboration portal: a resource for rat somatosensory cortexFrontiers In Neural Circuits. 2015. DOI : 10.3389/fncir.2015.00044.
Reconstruction and Simulation of Neocortical MicrocircuitryCell. 2015. DOI : 10.1016/j.cell.2015.09.029.
The effects of globotriaosylceramide tail saturation level on bilayer phasesSoft Matter. 2015. DOI : 10.1039/c4sm02456g.
Vesicles and Vesicle Fusion: Coarse-Grained SimulationsBiomolecular Simulations; Totowa, NJ: Humana Press, 2013. p. 659-697.
Spontaneous Vesicle Self-Assembly: A Mesoscopic View of Membrane DynamicsLangmuir. 2012. DOI : 10.1021/la2033803.
Tension-induced fusion of bilayer membranes and vesiclesNature Materials. 2005. DOI : 10.1038/nmat1333.
Phase transitions in neurodegenerative disease
Mechanism of Shiga toxin entry into cellsThe plasma membrane of cells protects the interior from the environment while permitting signals to be transduced across it and allowing material to be taken in or expelled in a controlled way. Bacteria and viruses have evolved to co-opt signalling and endocytic pathways to invade a cell in order to propagate themselves. Some of these pathways are independent of the cellular endocytic machinery, an example being that used by Ricin, Shiga and Shiga-like bacterial toxins.
Shiga toxin invasion begins when toxin particles in the bulk solution adsorb to the plasma membrane by binding to globotriaosylceramide glyoclipids (Gb3) lipids. They subsequently diffuse around and form clusters. This clustering process takes place over distances much larger than the particle size, and in the absence of direct protein-protein attractive forces. We have used atomistic and mesoscopic simulations to characterise the toxin
Accelerating Coarse-Grained Molecular SimulationsI have developed and maintain a parallel Dissipative Particle Dynamics (DPD) code to perform complex fluid simulations on length and time scales far beyond those attainable with Molecular Dynamics simulations. The code is used under license from the Max Planck Institute, where part of it was developed. It uses the common Message Passing Interface protocol, and its execution shows excellent weak scaling up to 2000 processors. The code has been used in more than a dozen publications, and is in current use at several universities and research institutes.
I am working with Imperial College London and the University of Southampton to implement the code on a novel computing platform called POETS - Partially-Oriented Event Triggered Systems (www.poets-project.org) which has the potential to speed up DPD simulations by several orders of magnitude. POETS is funded by the UK
Teaching & PhD
Life Sciences Engineering