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
Peter Bosman appointed part-time professor Delft University of Technology
Recently, Peter A.N. Bosman, senior researcher in the CWI Life Sciences and Health (LSH) group, has been appointed part-time professor Evolutionary Algorithms in the department of Software Technology of the faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) of Delft University of Technology.
Joint eScience and Data Science grant for CWI's Peter Bosman and AMC
Recently, a research proposal that is spearheaded by CWI was granted in the Joint eScience and Data Science programme that was organized jointly by the NWO Domain Science and Netherlands eScience Center (NLeSC). In all projects in this programme, researchers collaborate with eScience engineers of the NLeSC.
Alexander Schoenhuth appointed Professor Genome Data Science
Starting 1 October 2017, Alexander Schoenhuth of Centrum Wiskunde & Informatica (CWI) in Amsterdam is appointed Professor ‘Genome Data Science’ at the Faculty of Science of Utrecht University. It concerns a part-time appointment for one day a week.
CWI PhD student Jasmijn Baaijens wins Best Talk Award at the ISMB-HitSeq conference
Jasmijn Baaijens, PhD student from CWI’s Life Sciences and Health group, has won the Best Talk Award at ISMB-HitSeq, the world's leading conference on high-throughput genomics.
Current events
LSH Seminar Joke Blom
- 2018-08-28T16:00:00+02:00
- 2018-08-28T17:00:00+02:00
LSH Seminar Joke Blom
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
LSH Seminar Andre Dekker (MAASTRO clinic, Maastricht)
- 2018-09-24T16:00:00+02:00
- 2018-09-24T17:00:00+02:00
LSH Seminar Andre Dekker (MAASTRO clinic, Maastricht)
Start: 2018-09-24 16:00:00+02:00 End: 2018-09-24 17:00:00+02:00
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.
- Web
- Email: Marleen Balvert
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iCal
LSH Seminar Marco Virgolin
- 2018-09-25T16:00:00+02:00
- 2018-09-25T17:00:00+02:00
LSH Seminar Marco Virgolin
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
LSH Seminar Ziyuan Wang
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
PhD defense Ngoc Hoang Luong (LSH)
Start: 2018-10-17 15:00:00+02:00 End: 2018-10-17 16:00:00+02:00
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.
- Email: Ngoc Hoang Luong
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iCal
Members
Associated Members
Publications
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Medvet, E, Virgolin, M, Castelli, M, Bosman, P.A.N, Gonçalves, I, & Tušar, T. (2018). Unveiling evolutionary algorithm representation with DU maps. Genetic Programming and Evolvable Machines - Topical Collection: Genetic Programming, Evolutionary Computation and Visualization, 1–39. doi:10.1007/s10710-018-9332-5
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Orphanou, K, Thierens, D, & Bosman, P.A.N. (2018). Learning Bayesian network structures with GOMEA. In GECCO 2018 - Proceedings of the 2018 Genetic and Evolutionary Computation Conference (pp. 1007–1014). doi:10.1145/3205455.3205502
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Luong, N.H, Alderliesten, T, & Bosman, P.A.N. (2018). Improving the performance of MO-RV-GOMEA on problems with many objectives using Tchebycheff scalarizations. In GECCO 2018 - Proceedings of the 2018 Genetic and Evolutionary Computation Conference (pp. 705–712). doi:10.1145/3205455.3205498
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Bouter, A, Alderliesten, T, Bel, A, Witteveen, C, & Bosman, P.A.N. (2018). Large-scale parallelization of partial evaluations in evolutionary algorithms for real-world problems. In GECCO 2018 - Proceedings of the 2018 Genetic and Evolutionary Computation Conference (pp. 1199–1206). doi:10.1145/3205455.3205610
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Rens, E.G. (2018, June 27). Multiscale mathematical biology of cell-extracellular matrix interactions during morphogenesis.
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Chikhi, R, & Schönhuth, A. (2018). Dualities in tree representations. In 29th Annual Symposium on Combinatorial Pattern Matching, CPM 2018. doi:10.4230/LIPIcs.CPM.2018.18
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Wang, Z, Dijk, van, I.W.E.M, Wiersma, J, Ronckers, C.M, Oldenburger, F, Balgobind, B.V, … Alderliesten, T. (2018). Are age and gender suitable matching criteria in organ dose reconstruction using surrogate childhood cancer patients' CT scans?. Medical Physics. doi:10.1002/mp.12908
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Virgolin, M, Dijk, van, I.W.E.M, Wiersma, J, Ronckers, C.M, Witteveen, C, Bel, A, … Bosman, P.A.N. (2018). On the feasibility of automatically selecting similar patients in highly individualized radiotherapy dose reconstruction for historic data of pediatric cancer survivors. Medical Physics. doi:10.1002/mp.12802
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Sadowski, K.L, Thierens, D, & Bosman, P.A.N. (2018). GAMBIT: A parameterless model-based evolutionary algorithm for mixed-integer problems. Evolutionary Computation, 26(1), 117–143. doi:10.1162/evco_a_00206
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Luong, N.H, La Poutré, J.A, & Bosman, P.A.N. (2018). Multi-objective Gene-pool Optimal Mixing Evolutionary Algorithm with the interleaved multi-start scheme. Swarm and Evolutionary Computation. doi:10.1016/j.swevo.2018.02.005
Software
VirtualLeaf: a modeling framework for plant tissue morphogenesis
VirtualLeaf is a computer modeling framework for the simulation of plant tissue morphogenesis, i.e., the biological development of an organism's shape