Evert Bosdriesz
Assistant Professor, Vrije Universiteit Amsterdam
Bioinformatics, Department of Computer Science
e.bosdriesz@vu.nl - +31 (0)6 20678153
Specialized in
Computational cancer biology, statistical analysis of -omics data, (quasi) mechanistic modeling.
Experience
2020-
Assistant Professor, Bioinformatics, Vrije Universiteit Amsterdam.
- Organizing MSc course “Bioinformatics for Translational Medicine”
- Track coordinator “Bioinformatics and Systems Biology” MSc program
- Developing network-reconstruction methods.
2014-2019
Postdoctoral Fellow, Computational Cancer Biology, Netherlands Cancer Institute.
- Developed network-reconstruction methods.
- Analysed multi-omics data sets (pre-clinical and clinical).
- Collaborated with many “wet-lab” groups.
- Supervised MSc students and a bioinformatician.
- Member of the Postdoc-committee.
- Gave guest lectures and organized BioSB graduate student course.
2009-2014
PhD Candidate, Systems Bioinformatics, Vrije Universiteit Amsterdam.
- Analysed ODE-models.
- Identified design principles in regulatory circuits.
- Performed some experiments in yeast.
- Taught various bachelor and master courses.
- Organized NISB seminar series.
2008-2013
Various teaching jobs
- Teaching assistant as MSc student (physics, beta-gamma bachelor)
- Giving exam trainings (physics and math, VMBO and HAVO)
- One-on-one tutoring of high-school students (physics, math and chemistry, HAVO and VWO)
Education
2009-2013
PhD, Systems Bioinformatics, Vrije Universiteit Amsterdam.
Thesis: “Darwin`s invisible hand: Optimality principles in cellular resource allocation.”
Advisers: Prof. B. Teusink, Prof. F.J. Bruggeman and Dr. D. Molenaar.
2006-2009
MSc Theoretical Physics (Cum Laude), University of Amsterdam
Thesis: “The Central Spin Problem and the Richardson Equations.”
Adviser: Prof. J.S. Caux
2007-2008
Erasmus program, Humboldt University, Berlin, Germany.
2003-2006
BSc Physics and Astrophysics, University of Amsterdam.
Thesis: “Learning by Reward and Punishment in a Biologically Inspired Neural Network.”
Advisor: Dr. W.A. van Leeuwen
2002-2003
Beta-Gamma Propedeuse, University of Amsterdam.
Coding
Proficient
Python, R, CPLEX, Mathematica
Intermediate
bash, snakemake, git
Rusty
C, C++ (It’s been a while)
Awards
2013
SB@NL symposium poster prize (2th place)
2011
FEBS Youth Travel Fund, Grant covering expenses to attend the FEBS-SysBio2011 advanced lecture course.
2010
Shell Theoretical Physics Stipend, Awarded annually to the best graduates in theoretical physics in the Netherlands.
2009
MSc Theoretical Physics Cum laude
Publications
A list is also available at google scholar or pubmed. # indicates equal contribution.
Key
E. Bosdriesz, J. Fernandes Neto, A. Sieber, R. Bernards,N. Blüthgen and L.F.A. Wessels, ‘Identifying selective drug combinations using Comparative Network Reconstruction’. bioRxiv 2020.12.17.423240; doi:10.1101/2020.12.17.423240, 2020.
Shows that Comperative Network Reconstruction can be be used to predict which low-dose multi-drug combinations that are likely to selective, using an isogenic cell-line pair.
Code and Data
J. Fernandes Neto, E. Nadal#, E. Bosdriesz#, S. N. Ooft, L. Farre, C. McLean, S. Klarenbeek, A. Jurgens, H. Hagen, L. Wang, E. Felip, A. Martinez-Marti, A. Vidal, E. Voest, L.F.A. Wessels, O. van Tellingen, A. Villanueva and & R. Bernards, ‘Multiple Low Dose Therapy as an Effective Strategy to Treat EGFR Inhibitor-Resistant NSCLC Tumours.’ Nature Communications, 11 (1): 3157.doi:10.1038/s41467-020-16952-9, 2018. Shows that combining multiple drugs at low dose is effective, prevents emergence resistance, and is well tolerated by mice.
E. Bosdriesz, A. Prahallad, B. Klinger, A. Sieber, A. Bosma, R. Bernards, N. Blüthgen and L.F.A. Wessels, ‘Comparative Network Reconstruction Using Mixed Integer Programming’, Bioinformatics, 34:i997–1004. doi:10.1093/bioinformatics/bty616, 2018.
Method to reconstruct and compare signaling networks based on perturbation data using Mixed Integer Quadratic programming.:
Code -
Notebooks
A. Ressa#, E. Bosdriesz#, J. de Ligt, S. Mainardi, G. Maddalo, A. Prahallad, M. Jager, L. de la Fonteijne, M. Fitzpatrick, S. Groten, A.F.M. Altelaar, R. Bernards, E. Cuppen, L.F.A Wessels and J.R. Heck,
‘A System-Wide Approach to Monitor Responses to Synergistic BRAF and EGFR Inhibition in Colorectal Cancer Cells’,
Molecular & Cellular Proteomics, 17(10):1892-1908.
doi:10.1074/mcp.RA117.000486, 2018.
Transcriptomic, proteomic and phosphoproteomic, time-course analysis of cancer cells in response to targeted inhibitors:
Code
E. Bosdriesz, D. Molenaar, B. Teusink, and F.J. Bruggeman,
‘How Fast-Growing Bacteria Robustly Tune Their Ribosome Concentration to Approximate Growth-Rate Maximization.’,
FEBS Journal, 282(10):2029-2044. doi:10.1111/febs.13258, 2015.
Uses mechanistic, minimal models to understand the design principles of how bacteria control their macromolecular composition:
model
Peer-reviewed articles
2020
J. Fernandes Neto, E. Nadal#, E. Bosdriesz#, S. N. Ooft, L. Farre, C. McLean, S. Klarenbeek, A. Jurgens, H. Hagen, L. Wang, E. Felip, A. Martinez-Marti, A. Vidal, E. Voest, L.F.A. Wessels, O. van Tellingen, A. Villanueva and & R. Bernards, ‘Multiple Low Dose Therapy as an Effective Strategy to Treat EGFR Inhibitor-Resistant NSCLC Tumours.’ Nature Communications, 11 (1): 3157.doi:10.1038/s41467-020-16952-9, 2018.
T. Sustic, E. Bosdriesz, S. van Wageningen, L.F.A. Wessels and R. Bernards, ‘RUNX2/CBFB modulates the response to MEK inhibitors through activation of receptor tyrosine kinases in KRAS-mutant colorectal cancer’, Translational Oncology, 13(2):201-211. doi:[10.1016/j.tranon.2019.10.006(https://doi.org/10.1016/j.tranon.2019.10.006), 2020.
2018
E. Bosdriesz, A. Prahallad, B. Klinger, A. Sieber, A. Bosma, R. Bernards, N. Blüthgen and L.F.A. Wessels, ‘Comparative Network Reconstruction Using Mixed Integer Programming’, Bioinformatics, 34:i997–1004. doi:10.1093/bioinformatics/bty616, 2018.
A. Ressa#, E. Bosdriesz#, J. de Ligt, S. Mainardi, G. Maddalo, A. Prahallad, M. Jager, L. de la Fonteijne, M. Fitzpatrick, S. Groten, A.F.M. Altelaar, R. Bernards, E. Cuppen, L.F.A Wessels and J.R. Heck , ‘A System-Wide Approach to Monitor Responses to Synergistic BRAF and EGFR Inhibition in Colorectal Cancer Cells’, Molecular & Cellular Proteomics, 17(10):1892-1908. doi:10.1074/mcp.RA117.000486, 2018.
T. Šuštić#, S. van Wageningen#, E. Bosdriesz, R.J.D. Reid, J. Dittmar, C. Lieftink, R.L. Beijersbergen, L.F.A. Wessels, R. Rothstein and R. Bernards, ‘A Role for the Unfolded Protein Response Stress Sensor ERN1 in Regulating the Response to MEK Inhibitors in KRAS Mutant Colon Cancers’, Genome Medicine, 10:90. doi:10.1186/s13073-018-0600-z, 2018.
L. Wang#, R. Leite de Oliveira#, S. Huijberts, E. Bosdriesz, N. Pencheva, D. Brunen, A. Bosma, J.Y. Song, J. Zevenhoven, G. T. Los-de Vries, H. Horlings, B. Nuijen, J.H. Beijnen, J.H.M. Schellens and R. Bernards. ‘An Acquired Vulnerability of Drug-Resistant Melanoma with Therapeutic Potential’. Cell, 173(6):1413-1425.e14. doi:10.1016/j.cell.2018.04.012, 2018.
M. Dorel, B. Klinger, T. Gross, A. Sieber, A. Prahallad, E. Bosdriesz, L.F.A. Wessels and N. Blüthgen, ‘Modelling Signalling Networks from Perturbation Data’, Bioinformatics, 34(23):4079–4086. doi:10.1093/bioinformatics/bty473, 2018.
Z. Xue, D.J. Vis, A. Bruna, T. Šuštić, S. Van Wageningen, A. Sati Batra, O.M. Rueda, E. Bosdriesz, C. Caldas, L.F.A. Wessels and R. Bernards. ‘MAP3K1 and MAP2K4 Mutations Are Associated with Sensitivity to MEK Inhibitors in Multiple Cancer Models’. Cell Research, 28:719–729. doi:10.1038/s41422-018-0044-4, 2018.
E. Bosdriesz#, M.T. Wortel#, J.R. Haanstra, M.J. Wagner, P. de la Torre Cortés, and B. Teusink, ‘Low Affinity Uniporter Carrier Proteins Can Increase Net Substrate Uptake Rate by Reducing Efflux’, Scientific Reports, 8:5576. doi:10.1038/s41598-018-23528-7, 2018.
2016
M.T. Wortel#, E. Bosdriesz#, B. Teusink, and F.J. Bruggeman.
‘Evolutionary Pressures on Microbial Metabolic Strategies in the Chemostat’.
Scientific Reports, 6:29503. doi:10.1038/srep29503, 2016.
2015
E. Bosdriesz, D. Molenaar, B. Teusink, and F.J. Bruggeman, ‘How Fast-Growing Bacteria Robustly Tune Their Ribosome Concentration to Approximate Growth-Rate Maximization.’, FEBS Journal, 282(10):2029-2044. doi:10.1111/febs.13258, 2015.
E. Bosdriesz, S. Magnúsdóttir, F.J. Bruggeman, B. Teusink, and D. Molenaar, ‘Binding Proteins Enhance Specific Uptake Rate by Increasing the Substrate-Transporter Encounter-Rate’, FEBS Journal, 282:2394–2407. doi:10.1111/febs.13289, 2015.
2013
J. Berkhout, E. Bosdriesz, E. Nikerel, D. Molenaar, D. de Ridder, B. Teusink and F.J. Bruggeman,
‘How Biochemical Constraints of Cellular Growth Shape Evolutionary Adaptations in Metabolism.’,
Genetics, 194:505–512. doi:10.1534/genetics.113.150631, 2013.
Preprints
E. Bosdriesz, J. Fernandes Neto, A. Sieber, R. Bernards,N. Blüthgen and L.F.A. Wessels, ‘Identifying selective drug combinations using Comparative Network Reconstruction’. bioRxiv 2020.12.17.423240; doi:10.1101/2020.12.17.423240, 2020.
N. Aben, J. de Ruiter, E. Bosdriesz, Y. Kim, G. Bounova, D.J. Vis, L.F.A. Wessels and M. Michaut.
‘Identifying Biomarkers of Anti-Cancer Drug Synergy Using Multi-Task Learning.’
BioRxiv 243568. doi:10.1101/243568, 2018.
Talks
2018
INCOME2018,
Comparative network reconstruction to identify selective anti-cancer drug combinations,
Bernried, Germany.
17th European Conference on Computational Biology, Comparative Network Reconstruction using Mixed Integer Progamming, Athens, Greece.
VUmc seminar series on bioinformatics and data analysis, Comparative network reconstruction to identify selective anti-cancer drug combinations., Amsterdam, the Netherlands.
BioSB 2018, Comparative network reconstruction to identify selective anti-cancer drug combinations, Lunteren, the Netherlands.
2016
BioSB 2016,
Comparative network reconstruction identifies resistance mechanisms to targeted cancer treatment,
Lunteren, the Netherlands.
2014
EMBO: From Functional Genomics to Systems Biology,
The logic of the regulatory mechanism underlying growth rate control in Escherichia coli,
Heidelberg, Germany.
2013
14th International Conference on Systems Biology,
Escherichia coli implements a robust regulatory network motif that maximizes growth rate,
Copenhagen, Denmark.
Netherlands Bioinformatics Conference 2013, Design principles of nutrient-uptake systems involving binding proteins, Lunteren, the Netherlands.
2012
Netherlands Consortium for Systems Biology symposium,
Escherichia coli implements a robust regulatory network motif that maximizes growth rate,
Soesterberg, the Netherlands.
Netherlands Bioinformatics Conference 2012, Optimal and robust regulation of gene expression, Lunteren, the Netherlands.
Netherlands Biotechnology Congress, Optimal and robust regulation of gene expression, Ede, the Netherlands.
Reviewing
Independent
Bioinformatics, Cellular Oncology, Cancer Medicine, Molecular Cancer Therapeutics, Scientific Reports.
Co-reviewed
Nature Communications, Plos Computational Biology (with Prof. Wessels),
Lung Cancer (with Prof. Bernards),
Biophysical Journal (with Prof. Bruggeman).