Skip to content

Integrative Scalable Computing Laboratory

A research group at the Department of Information Technology, Uppsala Universtity.

  • Home
  • Projects
  • People
  • Publications
  • Teaching
  • Software
  • Recruitment
  • About us
  • Toggle search form

Open PhD position

Posted on February 5, 2015February 5, 2015 By admin No Comments on Open PhD position

We are currently hiring a PhD student to work on the project From Single Cells to Tumors – Multiscale Simulation of Stochastic (multi)cellular Systems . Deadline for application: March 15. Instructions for how to apply can be found here: Instructions for application.

Multiscale methods, News, PyURDME, Reaction Diffusion Master Equation

StochSS 1.4: Introducing Spatial Stochastic Modeling and Simulations

Posted on September 1, 2014September 1, 2014 By admin No Comments on StochSS 1.4: Introducing Spatial Stochastic Modeling and Simulations

We are excited to announce the release of StochSS 1.4 Version 1.4 includes spatial stochastic simulation capabilities powered by  PyURDME (http://www.pyurdme.org/). Details and instructions on how to obtain the code can be found on the Download page Tutorials are available on the Documentation page Linda Petzold and Chandra Krintz – University of California Santa Barbara Per Lotstedt and Andreas Hellander – Uppsala…

Read More “StochSS 1.4: Introducing Spatial Stochastic Modeling and Simulations” »

News, PyURDME, Reaction Diffusion Master Equation, Software, Stochastic Chemical Kinetics, StochSS

Open PhD student position

Posted on June 25, 2014June 25, 2014 By admin No Comments on Open PhD student position

We have an opening for a PhD student in computational systems biology. Interested candidates are encouraged to contact me for more details. Apply to the position here.

Multiscale methods, News, Reaction Diffusion Master Equation

PyURDME 1.0

Posted on June 25, 2014June 25, 2014 By admin No Comments on PyURDME 1.0

After more than a year of development, we are happy to announce the release of PyURDME 1.0.0! PyURDME is a Python module for spatial stochastic simulation model development and simulation. PyURDME is connected to URDME in that is uses a modified version of its core solver. While URDME is mainly designed as an interactive Matlab…

Read More “PyURDME 1.0” »

News, PyURDME, Reaction Diffusion Master Equation, Software, StochSS, URDME

ECMTB 2014 and Computational Software

Posted on June 25, 2014June 25, 2014 By admin No Comments on ECMTB 2014 and Computational Software

I attended this years ECMTB 2014. Apart from many interesting sessions on mathematical modeling, I attended this minisymposia on software for multicellular simulations. All the speakers had done a great job developing software for the application community, but the impression was that they managed to do this despite being productive methods researchers, not as a…

Read More “ECMTB 2014 and Computational Software” »

News, Software, StochSS, URDME

PhD and Postdoc positions

Posted on January 17, 2014 By admin No Comments on PhD and Postdoc positions

The Center for Applied Mathematics (CIM) in Uppsala are looking for up to 3 PhD students in applied mathematics. Within this call there is an opportunity to joint the group working on the project From cell-cell interactions to embryo development: Multiscale models and simulation in systems biology. This project is a collaboration with Carolina Wählby….

Read More “PhD and Postdoc positions” »

Hes1, Multiscale methods, News, Reaction Diffusion Master Equation, Stochastic Chemical Kinetics, StochSS, URDME

First release of StochSS

Posted on July 20, 2013July 20, 2013 By admin No Comments on First release of StochSS

We are excited to announce the first release of StochSS: Stochastic Simulation Service.  StochSS is an integrated development environment featuring state of the art algorithms for discrete stochastic biochemical simulation. StochSS is designed to enable you to easily scale up your simulations in complexity, deploying compute resources as needed.  The current version includes algorithms for…

Read More “First release of StochSS” »

News, StochSS

Perspective: Stochastic Algorithms for Chemical Kinetics

Posted on May 15, 2013May 15, 2013 By admin No Comments on Perspective: Stochastic Algorithms for Chemical Kinetics

In a new paper in the Journal of Chemical Physics, Dan Gillespie, myself and Linda Petzold review theory and algorithms for well-mixed and spatial mesoscopic chemical kinetics. In an associated podcast, available in the journal’s Perspectives collection, we share some of our views on the grand challenges facing us as methods developers as the field…

Read More “Perspective: Stochastic Algorithms for Chemical Kinetics” »

News, Stochastic Chemical Kinetics

Spatial Stochastic Simulation of the Hes1 gene regulatory network

Posted on January 23, 2013 By admin No Comments on Spatial Stochastic Simulation of the Hes1 gene regulatory network

Individual mouse embryonic stem cells have been found to exhibit highly variable differentiation responses under the same environmental conditions. Recent experimatal evidence suggest that the noisy cyclic expression of Hes1 and its downstream genes are  responsible for this, but the mechanism underlying this variability in expression is not well understood. Together with Mark Chaplain’s group,…

Read More “Spatial Stochastic Simulation of the Hes1 gene regulatory network” »

Hes1, News, Reaction Diffusion Master Equation

Posts navigation

Previous 1 … 3 4

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/

Follow us on twitter

Andreas HellanderFollow

Andreas Hellander
Retweet on TwitterAndreas Hellander Retweeted
yannik_schaelteYannik Schälte@yannik_schaelte·
9 Jun

🎒Summer school: 𝐈𝐧𝐯𝐞𝐫𝐬𝐞 𝐩𝐫𝐨𝐛𝐥𝐞𝐦𝐬 𝐟𝐨𝐫 𝐦𝐮𝐥𝐭𝐢-𝐬𝐜𝐚𝐥𝐞 𝐦𝐨𝐝𝐞𝐥𝐬

💬With: Linda Petzold, Christiane Fuchs, @dennisprangle, @StefanEngblom, @A_Hellander

⏰August 22-26
📌@HCM_Bonn

✏️Details+register: http://www.hcm.uni-bonn.de/events/eventpages/hausdorff-school/hausdorff-schools-2022/inverse-2022/

Reply on Twitter 1534886971478261770Retweet on Twitter 15348869714782617709Like on Twitter 153488697147826177019Twitter 1534886971478261770
A_HellanderAndreas Hellander@A_Hellander·
25 May

Really enjoyed presenting our work on federated learning with FEDn at CCGRID22 last week. Some takeaways from the talk (1/3):

1. Algorithm development must have real-world scalability in mind and there is a risk in missing this aspect if only considering simulation of FL.

Reply on Twitter 1529360630087557120Retweet on Twitter 1529360630087557120Like on Twitter 15293606300875571201Twitter 1529360630087557120
A_HellanderAndreas Hellander@A_Hellander·
25 May

Such a beautiful paper put together by @adameykolab, and one of the most fun applications of fluid mechanics modeling I have seen in recent years @AnassBouchnita @MurtazoNazarov. Thanks for the collaboration!

Igor Adameyko@adameykolab

After a long struggle, failed revision in Science, loads of happiness and pain, our paper on surface-associated water streams integrating polyps into a coral colony, is out in Current Biology. https://www.cell.com/current-biology/fulltext/S0960-9822(22)00672-8?fbclid=IwAR0j5TqfenF0_tp1hDam43K6jdfWS9iw16OzGVHZsVZ89eDe0Yq8Aa-ykuY#%20 1/10

Reply on Twitter 1529359602516738049Retweet on Twitter 1529359602516738049Like on Twitter 15293596025167380493Twitter 1529359602516738049
Retweet on TwitterAndreas Hellander Retweeted
adameykolabIgor Adameyko@adameykolab·
14 May

After a long struggle, failed revision in Science, loads of happiness and pain, our paper on surface-associated water streams integrating polyps into a coral colony, is out in Current Biology. https://www.cell.com/current-biology/fulltext/S0960-9822(22)00672-8?fbclid=IwAR0j5TqfenF0_tp1hDam43K6jdfWS9iw16OzGVHZsVZ89eDe0Yq8Aa-ykuY#%20 1/10

Reply on Twitter 1525473700971175936Retweet on Twitter 152547370097117593631Like on Twitter 1525473700971175936158Twitter 1525473700971175936
A_HellanderAndreas Hellander@A_Hellander·
11 May

Are you using StochSS? Please help us gather insights into what is working well and what can be improved by filling in this short survey https://forms.gle/mEqfASuUd3MDWuPS9

@LindaPetzold @briandrawert @mhucka

Reply on Twitter 1524477596930654214Retweet on Twitter 15244775969306542141Like on Twitter 15244775969306542141Twitter 1524477596930654214
Load More...

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/

Copyright © 2022 Integrative Scalable Computing Laboratory.

Powered by PressBook Blog WordPress theme