Office Office 30 (C3b/148)
Phone +34 673 261300
E-mail gdalmasso@crm.cat
Position Postdoctoral Researcher
Funding Maria de Maeztu
Research interests Computational & Mathematical Biology
Area Life Sciences
Group Mathematical & Computational Biology
Dalmasso, Giovanni
Biosketch

About me

After getting my bachelor (2009) and master (2011) degrees in Mathematics for Engineering Sciences and Mathematical Engineering at the Polytechnic University of Turin I moved to the ETH of Zürich (Switzerland) in the Koumoutsakos lab where I completed my master thesis and worked as research assistant. Here I focused my research in swarming dynamics and collective behaviours using an agent-based modelling (ABM) approach on HPC frameworks based on reinforcement learning.

Afterwards (2012) I joined the Attinger lab at the Center of Environmental Research (UFZ) of Leipzig (Germany) where my main focus was to investigate the effects of the environment on T-lymphocyte cells differentiation. Additionally I was collaborating in the implementation of a computationally inexpensive sequential screening method able to reduce the number of parameters in environmental models.

In 2017 obtained my PhD in Biology at the University of Heidelberg working at the German Cancer Research Center (DKFZ) in the group of Anne Hamacher-Brady. My main project here consisted in using ABM to predict the role of mitochondria in the interplay of autophagy and apoptosis.

In 2017 I joined as PostDoc the Sharpe lab in Barcelona (Spain) at the Centre for Genomic Regulation (CRG) which later the same year moved to the European Molecular Biology Laboratory (EMBL). Here I was working on the development of a mathematical method based on the concept of spherical harmonics which has created the first ever continuous numerical description of morphogenesis of the limb bud over time and space. Additionally, I deepened my biological knowledge and started doing experiments. Specifically, I began to be interested and working on the understanding of the formation of the vasculature inside the limb using an in vitro approach. 

As of November 2022, I work at the Centre de Recerca Matematica (Bellaterra, Barcelona) where I joined the group of Tomas Alarcon.

Projects

Current projects at CRM

  • Vasculature remodelling: in a joint work with the group of James Sharpe at EMBL Barcelona, the aim of this project is to combine biological experiments and mathematical modelling to unveil the phenomenon of vasculature regression during cartilage condensation (i.e. digit formation) in the growing limb.

Other projects

  • Vedo: A python module for scientific analysis and visualization of эd objects --> https://vedo.embl.es

Past projects

Selected publications

More information on Google Scholar.

 

  • M. Blanc, G. Dalmasso, F. Udina and C. Pujades (2022) "The Digital 3D-Atlas MAKER (DAMAKER): a dynamic and expandable digital 3D- tool for monitoring the temporal changes in tissue growth during hindbrain morphogenesis". eLife 11:e78300. DOI.
  • G. Dalmasso, M. Musy, M. Niksic, A. Robert-Moreno, C. Badia- Careaga, J. J. Sanz-Ezquerro and J. Sharpe. (2022) "4D reconstruction of developmental trajectories using spherical harmonics". Developmental Cell 57, 1-11. DOI.
  • J. Klatzow, G. Dalmasso, N. Martinez-Abadias, J. Sharpe and V. Uhlmann. (2022) "Match: 3D shape correspondence for microscopy data". Frontiers in Computer Science 4:777615. DOI.
  • M. Musy, G. Dalmasso et al. (2022) "Vedo, a python module for scientific analysis and visualization of 3D objects and point clouds". Zenodo. DOI.
  • L. Aguilera, F. Bergmann, G. Dalmasso, R. Grosseholz, P. Holzheu, P. Kalra, U. Kummer, S. Sahle and N Veith. (2018) "Advantages and disadvantages of frequency vs. amplitude coding of calcium oscillations during changing temperatures". Biophysical Chemistry 245, 17-24.
  • G. Dalmasso, P.A. Marin Zapata, N.R. Brady, A. Hamacher-Brady (2017) "Agent-based modeling of mitochondria links sub-cellular dynamics to cellular homeostasis and heterogeneity", PLoS One 12 (1), e0168198. DOI.
  • P. A. Marin Zapata, C. J. Beese, A. Jünger, G. Dalmasso, N. R. Brady, A. Hamacher-Brady (2016) "Time course decomposition of cell heterogeneity in TFEB signaling states reveals homeostatic mechanisms restricting the magnitude and duration of TFEB responses to mTOR activity modulation", BMC cancer 16 (1), 355. DOI.
  • M. Cuntz et al. and L. Samaniego (2015) "Computationally inexpensive identification of noninformative model parameters by sequential screening", Water Resources Research 51 (8), 6417- 6441. DOI.