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 Joke Blom

  • 2018-08-28T16:00:00+02:00
  • 2018-08-28T17:00:00+02:00
August 28 Tuesday

Start: 2018-08-28 16:00:00+02:00 End: 2018-08-28 17:00:00+02:00

Title and abstract will follow.

LSH Seminar Leen Stougie

  • 2018-09-11T16:00:00+02:00
  • 2018-09-11T17:00:00+02:00
September 11 Tuesday

Start: 2018-09-11 16:00:00+02:00 End: 2018-09-11 17:00:00+02:00

TBA

LSH Seminar Andre Dekker (MAASTRO clinic, Maastricht)

  • 2018-09-24T16:00:00+02:00
  • 2018-09-24T17:00:00+02:00
September 24 Monday

Start: 2018-09-24 16:00:00+02:00 End: 2018-09-24 17:00:00+02:00

L016

Prof. dr. ir. Andre Dekker (MAASTRO clinic, Maastricht)

From Big Data to Better Cancer Care – FAIR, Linked Data & Personal Health Train

Abstract:
Big data, artificial intelligence, machine learning and data science are expected to have a major impact on day-to-day cancer practice. Big data based services such as automated image segmentation, radiomics, decision support systems and literature mining are products already available to the cancer community and these are expected to rapidly change the way we practice medicine.
Since 2008 Maastricht University and MAASTRO Clinic have developed a research program on this topic. A global IT infrastructure has been developed in which cancer centers are being connected with currently up to 25 partners. The aim is to enable cross-institute, privacy-preserving, data sharing & machine learning and more efficient clinical evidence generation: a concept now commonly referred to as "Rapid Learning".
In the seminar innovative technology to extract, store and process (big) data for Rapid Learning and will be discussed.  All this data is often seen as tremendously promising and is predicted to change health care radically, but at this point in time is mostly a challenge as we keep accumulating data without a clear path to clinical applications while privacy concerns are on the rise. Methods and examples how we go from data to making a difference in lives of cancer patients will be presented. As will the methods to do this in a way that preserves the privacy of patients such as the Personal Health Train and distributed learning.

LSH Seminar Marco Virgolin

  • 2018-09-25T16:00:00+02:00
  • 2018-09-25T17:00:00+02:00
September 25 Tuesday

Start: 2018-09-25 16:00:00+02:00 End: 2018-09-25 17:00:00+02:00

Title and abstract will follow.

LSH Seminar Ziyuan Wang

  • 2018-10-09T16:00:00+02:00
  • 2018-10-09T17:00:00+02:00
October 9 Tuesday

Start: 2018-10-09 16:00:00+02:00 End: 2018-10-09 17:00:00+02:00

Title and abstract will follow.

PhD defense Ngoc Hoang Luong (LSH)

  • 2018-10-17T15:00:00+02:00
  • 2018-10-17T16:00:00+02:00
October 17 Wednesday

Start: 2018-10-17 15:00:00+02:00 End: 2018-10-17 16:00:00+02:00

Senaatszaal of the Auditorium (Aula), Delft University of Technology, Mekelweg 5, Delft

Everyone is invited to attend the public defense of Ngoc Hoang Luong of his PhD thesis:

Design and Application of Scalable Evolutionary Algorithms in Electricity Distribution Network Expansion Planning

Promotoren: prof.dr. Han La Poutré and prof.dr. Peter Bosman

 

Summary of the dissertation is here.

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
  • Identificatie van homogene subgroepen bij mensen met een chronische ziekte, die ernstig vermoeid zijn, door middel van een persoonsgerichte studie opzet. (Beter Gezond)
  • 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