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