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
Current events
LSH Seminar Leen Stougie
- 2019-02-26T16:00:00+01:00
- 2019-02-26T17:00:00+01:00
LSH Seminar Leen Stougie
Start: 2019-02-26 16:00:00+01:00 End: 2019-02-26 17:00:00+01:00
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.
- Web
- Email: Marleen Balvert
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iCal
Members
Associated Members
Publications
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Maree, S.C, Luong, N.H, Kooreman, E.S, van Wieringen, N, Bel, A, Hinnen, K.A, … Alderliesten, T. (2019). Evaluation of bi-objective treatment planning for high-dose-rate prostate brachytherapy—A retrospective observer study. Brachytherapy. doi:10.1016/j.brachy.2018.12.010
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Shvetsova, E, Sofronova, A, Monajemi, R, Gagalova, K, Draisma, H.H.M, White, S.J, … GoNL consortium. (2018). Skewed X-inactivation is common in the general female population. European Journal of Human Genetics. doi:10.1038/s41431-018-0291-3
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Luong, N.H. (2018, October 17). Design and application of scalable evolutionary algorithms in electricity distribution network expansion planning. Retrieved from http://dx.doi.org/10.4233/uuid:15818216-0eb5-4545-bd2e-27eaa38262ba
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Aalvanger, G.H, Luong, N.H, Bosman, P.A.N, & Thierens, D. (2018). Heuristics in permutation GOMEA for solving the permutation flowshop scheduling problem. In Lecture Notes in Computer Science/Lecture Notes in Artificial Intelligence (pp. 146–157). doi:10.1007/978-3-319-99253-2_12
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Koumoutsos, G. (2018, September). k-Server problems.
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Luong, N.H, La Poutré, J.A, & Bosman, P.A.N. (2018). Exploiting linkage information and problem-specific knowledge in evolutionary distribution network expansion planning. Evolutionary Computation, 26(3), 471–505. doi:10.1162/EVCO_a_00209
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Olver, N.K, Pruhs, K, Schewior, K, Sitters, R.A, & Stougie, L. (2018). The itinerant list update problem. In Proceedings of the 16th Workshop on Approximation and Online Algorithms (WAOA 2018) (pp. 310–326). doi:10.1007/978-3-030-04693-4_19
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Virgolin, M, Alderliesten, T, Bel, A, Witteveen, C, & Bosman, P.A.N. (2018). Symbolic regression and feature construction with GP-GOMEA applied to radiotherapy dose reconstruction of childhood cancer survivors. In GECCO 2018 - Proceedings of the 2018 Genetic and Evolutionary Computation Conference (pp. 1395–1402). doi:10.1145/3205455.3205604
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van der Meer, M.C, Alderliesten, T, Pieters, B.R, Bel, A, Niatsetski, Y, & Bosman, P.A.N. (2018). Better and faster catheter position optimization in HDR brachytherapy for prostate cancer using multi-objective real-valued GOMEA. In GECCO 2018 - Proceedings of the 2018 Genetic and Evolutionary Computation Conference (pp. 1387–1394). doi:10.1145/3205455.3205505
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Maree, S.C, Thierens, D, Alderliesten, T, & Bosman, P.A.N. (2018). Real-valued evolutionary multi-modal optimization driven by hill-valley clustering. In GECCO 2018 - Proceedings of the 2018 Genetic and Evolutionary Computation Conference (pp. 857–864). doi:10.1145/3205455.3205477
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
Current projects with external funding
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3D dose reconstruction for children with long-term follow-up Toward improved decision making in radiation treatment for children with cancer
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Enhancing protein-drug binding prediction
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ICT based Innovations in the Battle against Cancer – Next - Generation Patient -Tailored Brachytherapy Cancer Treatment Planning
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Improving Childhood Cancer Care when Parents Cannot be There - Reducing Medical Traumatic Stress in Childhood Cancer Patients by Bonding with a Robot Companion
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Statistical Models for Structural Genetic Variants in the Genome of the Netherlands
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Fusible Evolutionary Deep Neural Network Mixture Learning from Distributed Data for Robust Medical Image Analysis (FEDMix)
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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
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AMC Medical Research
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Elekta Limited
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Nucletron Operations BV
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Xomnia
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Academisch Medisch Centrum
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Biomedical Imaging Group Rotterdam
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Erasmus Universiteit Rotterdam
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KiKa
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Technische Universiteit Delft
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Universiteit Leiden