Description
Leader of the group Life Sciences and Health: Leen Stougie.
The CWI Life Sciences and Health (LSH) group is a group of computer scientists and mathematicians whose research focus is on the analysis and design of models and algorithms as well as their direct application to important challenges in the LSH domain.
On the application side, our present team of researchers has expertise in, e.g., computational genomics, medical informatics, computational phylogenetics, and biological network analysis. On the methodological side, we come from different backgrounds, e.g., computational intelligence, computational data science, and operations research. Methodologically, we develop new theories, models, algorithms and decision support tools, for problems that arise mostly in collaboration with experimental biologists and medical experts. We actively collaborate in projects with academic hospitals, biological and biochemical research institutes, and industry. Click here for more information about our group structure.
The LSH group participates in the INRIA International team ERABLE.
Seminars: The LSH group organizes a biweekly seminar.
Watch our group video to get a glimpse of our activities.
News
Artificial Intelligence by CWI and Amsterdam UMC proposes the best radiation treatment plans in clinical practice for the first time
CWI and Amsterdam UMC have developed software that helps radiation oncologists to make internal radiation treatment plans for prostate cancer. Today, the first patient was treated with a plan made with the help of this new AI technique.
CWI researchers involved in two NWO-Groot grants
In the NWO Open Competition ENW-GROOT programme, four CWI researchers received in total two grants to study machine learning and neural networks: Nikhil Bansal, Monique Laurent, Benjamin Sanderse and Leen Stougie.
Peter Bosman awarded NWO KLEIN grant
Peter Bosman of CWI's Life Sciences & Health group has been awarded a NWO KLEIN grant together with Amsterdam UMC.
Life Sciences and Health group awarded RISE grant
The Life Sciences and Health group have been awarded a Research and Innovation Staff Exchange (RISE) grant from the European Commission.
Current events
PhD Defense Marco Virgolin
- 2020-06-08T12:30:00+02:00
- 2020-06-08T14:00:00+02:00
PhD Defense Marco Virgolin
Start: 2020-06-08 12:30:00+02:00 End: 2020-06-08 14:00:00+02:00
Everyone is invited to attend the public defense of Marco of his PhD thesis: Design and Application of Gene-pool Optimal Mixing Evolutionary Algorithms for Genetic Programming.
Promotor 1: Prof.dr. Peter A.N. Bosman, Life Sciences and Health group, CWI, Amsterdam / Algorithmics Group, Department of Software Technology, Faculty of Electrical Engineering, Mathematics and Computer Science, TU Delft, Delft
Promotor 2: Prof.dr. Cees Witteveen, TU Delft
Copromotor: Dr. Tanja Alderliesten, Department of Radiation Oncology, LUMC, Leiden / Algorithmics Group, Department of Software Technology, Faculty of Electrical Engineering, Mathematics and Computer Science, TU Delft, Delft
- Email: Marco Virgolin
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iCal
Members
Associated Members
Publications
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Lähnemann, D, Köster, J, Szczurek, E, McCarthy, D.J, Hicks, S.C, Robinson, M.D, … Schönhuth, A. (2020). Eleven grand challenges in single-cell data science. Genome Biology, 21. doi:10.1186/s13059-020-1926-6
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Pusa, T, Galvão Ferrarini, M, Andrade, R, Mary, A, Marchetti Spaccamela, A, Stougie, L, & Sagot, M.-F. (2020). MOOMIN - Mathematical explOration of 'Omics data on a MetabolIc Network. Bioinformatics, 36(2), 514–523. doi:10.1093/bioinformatics/btz584
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Bernardini, G, Chen, H, Fici, G, Loukides, G, & Pissis, S. (2020). Reverse-safe data structures for text indexing. In Proceedings of the Workshop on Algorithm Engineering and Experiments (pp. 199–213).
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Nersisyan, L, Nikoghosyan, M, Arakelyan, A, Francioli, L.C, Menelaou, A. (Androniki), Pulit, S.L. (Sara L.), … The Genome of the Netherlands Consortium, . (2019). WGS-based telomere length analysis in Dutch family trios implicates stronger maternal inheritance and a role for RRM1 gene. Nature Scientific Reports, 9(1). doi:10.1038/s41598-019-55109-7
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Bosman, T. (2019, November 26). Relax, Round, Reformulate: Near-Optimal Algorithms for Planning Problems in Network Design and Scheduling.
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Luong, N.H, Alderliesten, T, Pieters, B.R, Bel, A, Niatsetski, Y, & Bosman, P.A.N. (2019). Fast and insightful bi-objective optimization for prostate cancer treatment planning with high-dose-rate brachytherapy. Applied Soft Computing, 84. doi:10.1016/j.asoc.2019.105681
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Baller, A.C, van Ee, M, Hoogeboom, M, & Stougie, L. (2019). Complexity of inventory routing problems when routing is easy. Networks. doi:10.1002/net.21908
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Abedin, P, Ganguly, A, Pissis, S, & Thankachan, S.V. (2019). Range Shortest Unique Substring queries. In Proceedings of the International Symposium on String Processing and Information Retrieval (pp. 258–266). doi:10.1007/978-3-030-32686-9_18
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Lopez Rincon, A, Martinez-Archundia, M, Martinez-Ruiz, G.U, Schönhuth, A, & Tonda, A. (2019). Automatic discovery of 100-miRNA signature for cancer classification using ensemble feature selection. BMC Bioinformatics, 20(1). doi:10.1186/s12859-019-3050-8
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Janssen, R, Jones, M.E.L, Kelk, S.M, Stamoulis, G, & Wu, T. (2019). Treewidth of display graphs: bounds, brambles and applications. Journal of Graph Algorithms and Applications, 23(4), 715–743. doi:10.7155/jgaa.00508
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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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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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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Statistical Models for Structural Genetic Variants in the Genome of the Netherlands
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Evolutionary eXplainable Artificial Medical INtelligence Engine (EXAMINE)
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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)
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Networks
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Optimization for and with Machine Learning (OPTIMAL)
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Pan-genome Graph Algorithms and Data Integration (PANGAIA)
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Transparent, Reliable and Unbiased Smart Tool for AI (TRUST-AI)
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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Geneton S.R.O.
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Illumina Cambridge
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Institut Pasteur
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Technische Universiteit Delft
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Univerzita Komenskeho V Bratislave
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Universiteit Leiden
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Universitaet Bielefeld
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Universita' Degli Studi di Milano-Bicocca
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Universiteit van Tilburg