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Scalable simulation of stochastic multicellular systems

Posted on November 5, 2016February 6, 2019 By admin No Comments on Scalable simulation of stochastic multicellular systems

In multicellular systems, cells of different types interact in various ways, both mechanically and chemically, to regulate complex processes. There is a large computational gap between detailed models of sub-cellular, molecular processes in single cells, and models of multicellular systems comprising of large numbers of interacting cells such as bacterial colonies, tissue and tumors. In the lab we seek to bridge this gap. We also develop new simulation methodology for modeling specific biological systems together with collaborators.

Scaling mechanisms of cartilage sheets

During embryo development cartilaginous structures assemble that later densify into bone and form the basis for the embryo’s skeleton. Understanding the cellular dynamics responsible for the correct shaping and growth of the cartilage is hence of high importance for modeling the full embryogenesis.

In this collaboration with the Adameyko lab at the Karolinska Institute we study the key question of how mechanical interactions and individual behavior at the cellular level enable the accurate shaping of the cartilage sheet. In order to analyse the influence of different mechanisms in-silico, we built a computational model of the cartilage sheet, combining the center-based model (CBM) as a mathematical framework for the cellular mechanics with rules governing the cellular behavior based on biological observations. We validate the model against in-vivo data, obtained from cell-lineage tracing performed by the Adameyko Lab [1].

Recent publications

    1. Kaucka, M., Zikmund, T., Tesarova, M., Gyllborg, D., Hellander, A., Jaros, J., … & Dyachuk, V. (2017). Oriented clonal cell dynamics enables accurate growth and shaping of vertebrate cartilage. eLife, 6, e25902.2
  1. Marketa Kaucka, Evgeny Ivashkin, Daniel Gyllborg, Tomas Zikmund, Marketa Tesarova, Jozef Kaiser, Meng Xie, Julian Petersen, Vassilis Pachnis, Silvia K Nicolis , Tian Yu, Paul Sharpe, Ernest Arenas, Hjalmar Brismar, Hans Blom, Hans Clevers , Ueli Suter, Andrei S Chagin, Kaj Fried, Andreas Hellander and Igor Adameyko, (2016) Analysis of neural crest-derived clones reavals novel aspects of facial development, Science Advances 2(8). 

Collaborators

  • Igor Adameyko

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Data-and simulation-driven life science. Much of our work in eScience and applied ML has applications in life science, and in Systems Biology in particular. We aim to enable data-and simulation-driven scientific discovery.

HASTE - a cloud native framework for intelligent processing of image streams: http://haste.research.it.uu.se/

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SciLifeLab_DCSciLifeLab_DataCentre@SciLifeLab_DC·
3 Nov

Join our great team at @SciLifeLab_DC!

We are now looking for IT-ansvarig SciLifeLab
👉Apply by Dec 12th.
👉More & apply here: https://www.kth.se/om/work-at-kth/lediga-jobb/what:job/jobID:546469/where:4/
👉More about @SciLifeLab_DC here: https://scilifelab.se/data

@scilifelab @KTHuniversity

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A_HellanderAndreas Hellander@A_Hellander·
25 Oct

Starting in 30mins :-)

Prashant Singh@prashant_rsingh

Join us tomorrow for an exciting seminar by @uPicchini on “guided sequential ABC schemes for intractable Bayesian models”. The seminar starts at 13.15 until 14.00 CEST in Room 101127, Ångströmlaboratoriet, Uppsala University & online: https://uu-se.zoom.us/j/65354024469. Warmly welcome!

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A_HellanderAndreas Hellander@A_Hellander·
6 Oct

eSSENCE, SERC and Chalmers e-science Centre are providing core e-science education to PhD students from the SeSE platform: https://sese.nu/

Researchers - get funding to develop and give a PhD course!
@uppsalauni @lunduniversity @umeauniversitet

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A_HellanderAndreas Hellander@A_Hellander·
6 Oct

Day two of the Swedish eScience Academy organized by eSSENCE.

Interesting to learn from Sverker Holmgren of Chalmers eCommons about the holistic approach to infrastructure and support for data centric research at Chalmers!

@UmeaUniversity @UU_University @lunduniversity

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A_HellanderAndreas Hellander@A_Hellander·
6 Oct

So great to be at the Swedish e-science Academy organized by #essenceofescience! Two days of scientific exchange between colleagues nationally, and in particular from the partner universities @UU_University @UmeaUniversity @lunduniversity.

Keynote day one by Kersti Hermansson.

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Decentralized AI, Federated Learning. One focus area of the group is development of methods and software to address decentralized and privacy-preserving AI. We are core contributors to the FEDn open source framework for scalable federated machine learning:

https://github.com/scaleoutsystems/fedn
Introduction to Federated Learning by Andreas Hellander
Join the discussion on Decentralized AI:

Scaleout Systems is a spin-out from ISCL on a mission to enable decentralized AI and federated learning to production.

https://www.scaleoutsystems.com/

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