Description

Leader of the group Life Sciences and Health: Leen Stougie.

Our research group creates fundamental knowledge and applied solutions in the broad field of life sciences. We promote understanding of how biological processes work in detail. Our interdisciplinary team of computer scientists, mathematicians and theoretical biologists develops new models, theories, and decision support systems in collaboration with experimental biologists and medical experts. We are motivated by applications of our work in practice

 

Watch our group video to get a glimpse of our activities or click here for more information about our group structure.

 

News

Instable blood supply may help healthy cells compete with tumor cells

Instable blood supply may help healthy cells compete with tumor cells

Researchers of CWI’s Scientific Computing group have found that instabilities in the blood supply in cancerous tissue can, surprisingly, lead to a less favorable environment for tumor cells. Their findings shed light on the potential negative side effects of current treatments that aim to actually normalize the blood supply in cancerous tissues.

Instable blood supply may help healthy cells compete with tumor cells - Read More…

Comparing medical images better

Comparing medical images better

Together with the radiation oncology department of AMC, Peter Bosman of CWI’s Life Sciences and Health group has been awarded 1.4 million euros for a project in NWO’s Open Technology Programme for the research and development of a new medical image registration method. This project is co-funded by companies Elekta and Xomnia.

Comparing medical images better - Read More…

A puzzle with a million pieces:  assembling viral genomes from sequencing data

A puzzle with a million pieces: assembling viral genomes from sequencing data

Researchers from CWI’s Life Science and Health group have developed a new computational tool, SAVAGE, for reconstructing the genomes of the different virus strains that affect an infected person. SAVAGE makes it possible to reconstruct the different strains – of which there can be plenty in an infected person – even when so called reference genomes are not available

A puzzle with a million pieces: assembling viral genomes from sequencing data - Read More…

Current events

LSH Seminar Leen Stougie

  • 2019-02-26T16:00:00+01:00
  • 2019-02-26T17:00:00+01:00
February 26 Tuesday

Start: 2019-02-26 16:00:00+01:00 End: 2019-02-26 17:00:00+01:00

L016

Metabolic Network Analysis and Phylogeny

In this lecture I will sketch two subfields of my research in life sciences, that have otherwise little overlap.

First I will show how optimization and enumeration play a role in metabolic network analysis and that mathematics can help solving these problems. In particular I will consider so-called flux balance analysis. This is research that has been done and is going on in collaboration with Marie-France Sagot and Arne Reimers.

Then I will give you an example of my research in phylogeny. In particular I will show you that reticulation events like horizontal gene transfer (especially in lower order organisms) require us to abolish the generically used pedigree tree model, but instead settle for a phylogenetic network. I will give some examples of results that we obtained within this model. This is research in collaboration with Leo van Iersel and Steven Kelk.

Members

Associated Members

Publications

Software

Current projects with external funding

  • 3D dose reconstruction for children with long-term follow-up Toward improved decision making in radiation treatment for children with cancer
  • Enhancing protein-drug binding prediction
  • ICT based Innovations in the Battle against Cancer – Next - Generation Patient -Tailored Brachytherapy Cancer Treatment Planning
  • Improving Childhood Cancer Care when Parents Cannot be There - Reducing Medical Traumatic Stress in Childhood Cancer Patients by Bonding with a Robot Companion
  • Statistical Models for Structural Genetic Variants in the Genome of the Netherlands
  • Fusible Evolutionary Deep Neural Network Mixture Learning from Distributed Data for Robust Medical Image Analysis (FEDMix)
  • Multi-Objective Deformable Image Registration (MODIR) – An Innovative Synergy of Multi-Objective Optimization, Machine Learning, and Biomechanical Modeling for the Registration of Medical Images with (MODIR)

Related partners

  • AMC Medical Research
  • Elekta Limited
  • Nucletron Operations BV
  • Xomnia
  • Academisch Medisch Centrum
  • Biomedical Imaging Group Rotterdam
  • Erasmus Universiteit Rotterdam
  • KiKa
  • Technische Universiteit Delft
  • Universiteit Leiden