Research Groups

Portrait Ivo Sbalzarini

Ivo Sbalzarini

Scientific Computing for Systems Biology

Previous and Current Research

The “MOdels, Simulations, and Algorithms for Interdisciplinary Computing” Group develops and applies computational methods for image-based systems biology. This includes particle methods for deterministic and stochastic spatiotemporal simulations, bio-image processing, optimization, and parallel high-performance computing. We aim at addressing significant biological challenges using novel computational methods and algorithms, without which the problem could not be solved. Our interdisciplinary group combines expertise from computer science, mathematics, physics, and engineering.

Ivo Sbalzarini research: animation video Animation: Particle-method simulation of the diffusion of Green Fluorescent Protein in the 3D geometry of the Endoplasmic Reticulum (ER) of a mammalian cell during a FRAP experiment. The ER geometry has been reconstructed from confocal images using an image segmentation algorithm. The same set of computational particles (not shown) that is used to represent the geometry is also used to simulate diffusion, leading to efficient and parallel computations. The code is implemented based on the PPM Library
Future Projects and Goals

We develop computational methods based on the algorithmic abstraction of particles. Particle methods can cover the entire workflow of image-based systems biology from image processing to computer simulations and model/systems validation. We exploit this unifying framework to develop novel theories and tools and demonstrate them in biological applications ranging from intra-cellular transport processes to tissue development and growth. In particular, we focus on adaptive multi-resolution simulations using particles, bio-image segmentation using particle methods, and randomized algorithms for particle-based sampling and black-box optimization. All algorithms rely on efficient parallelization and implementation on multi-core computer systems using the PPM Library developed in our group.

PPM Library

Methodological and Technical Expertise
  • mesh-free discretization schemes for partial differential equations
  • Bayesian bio-image analysis
  • parallel high-performance computing
  • bio-inspired computation
  • image-based modeling and simulation of biological processes in space and time
Selected Publications

R. Ramaswamy, G. Bourantas, F. Jülicher, and I. F. Sbalzarini
A hybrid particle-mesh method for incompressible active polar viscous gels.
J. Comput. Phys., 291:334–361 (2015)

S. Reboux, B. Schrader, and I. F. Sbalzarini
A self-organizing Lagrangian particle method for adaptive-resolution advection–diffusion simulations.
J. Comput. Phys., 231:3623–3646 (2012)

G. Paul, J. Cardinale, and I. F. Sbalzarini
Coupling image restoration and segmentation: A generalized linear model/Bregman perspective.
Int. J. Comput. Vis., 104(1):69–93 (2013)

I. F. Sbalzarini
Modeling and simulation of biological systems from image data.
Bioessays, 35(5):482–490 (2013)

I. F. Sbalzarini, A. Mezzacasa, A. Helenius, and P. Koumoutsakos
Effects of Organelle Shape on Fluorescence Recovery after Photobleaching
Biophysical Journal 89(3):1482–1492 (2005)


since 2014
Full Professor (W3) of Computer Science at TU Dresden, Chair of Scientific Computing for Systems Biology at the Center for Systems Biology Dresden (CSBD)

since 2012
Senior Research Group Leader, MPI-CBG, Dresden, Germany

Assistant Professor of Computational Science, Department of Computer Science, ETH Zurich, Switzerland

Group Leader in Bioinformatics, Mediterranean Institute for Life Sciences, Split, Croatia

Invited Professor of Biology, École Normale Supérieure, Paris, France

Ph.D. in Computer Science, ETH Zurich, Switzerland


Max Planck Institute of Molecular Cell Biology and Genetics
Pfotenhauerstraße 108
01307 Dresden