Julio's research focuses on the development and application of computational methods to acquire a functional understanding of signaling networks and their deregulation in disease, and to apply this knowledge to develop novel therapeutics.
To this end, he collaborates closely with experimental groups and pharmaceutical companies.
|2015-present||Professor of Computational Biomedicine, RWTH-Aachen University Hospital, Aachen, Germany|
|2015-present||Visiting group leader at the European Bioinformatics Institute, European Molecular Biology Laboratory (EMBL-EBI)|
|2010-2015||Group Leader at the European Bioinformatics Institute, European Molecular Biology Laboratory (EMBL-EBI), with a joint appointment in the EMBL Genome Biology Unit in Heidelberg|
|2010-2015||Senior fellow at Wolfson College (Cambridge, UK)|
|2008-2010||Scientific Coordinator of the NIH-NIGMS Cell Decision Process Center, Cambridge, MA, USA|
|2007-2010||Postdoctoral Fellow, Harvard Medical School and MIT, Boston USA|
|2002-2007||Research Assistant, Max Planck Institute, Magdeburg, Germany|
|2001-2002||Research assistant, University of Stuttgart, Institute of Biochemical Engineering, Germany, and Insilico Biotechnology, Germany|
Current scientific activities
|2014-present||Co-director of the DREAM challenges|
|2013-present||Affiliated member of Sage bionetworks|
|2002-2007||PhD summa cum laude in Process Engineering; Max-Planck-Institute for Dynamics of Complex Technical Systems and University of Magdeburg, Germany (Advisor: E. D. Gilles)|
|2000-2001||Exchange Erasmus student at the University of Stuttgart, Germany|
|1996-2001||’Licenciatura’ (MS), in Chemical Engineering University of Oviedo, Spain, finished with the best academic record of the year|
Julio Saez-Rodriguez is Professor of Computational Biomedicine at the Faculty of Medicine of RWTH-Aachen University,and a visiting group leader at the European Bioinformatics Institute, European Molecular Biology Laboratory (EMBL-EBI).
- Methods for logic modeling of signaling networks
- Logic modeling to find therapies for prostate cancer
- Linking signal transduction and metabolism with mechanistic models
- Personalizing health care in multiple sclerosis using systems medicine
- Multiscale pharmacogenomic analysis in cancer
- Modeling signaling networks from single cell data
OmniPath: guidelines and gateway for literature-curated signaling pathway resources.
Türei D, Korcsmáros T, Saez-Rodriguez J., Nat Methods, Volume 13 (2016), p. 966-967
Fumarate is an epigenetic modifier that elicits epithelial-to-mesenchymal transition.
Sciacovelli M et al., Nature, Volume 537 (2016), p. 544-547
Crowdsourcing biomedical research: leveraging communities as innovation engines.
Saez-Rodriguez J et al., Nat Rev Genet, Volume 17 (2016), p. 470-486
A Landscape of Pharmacogenomic Interactions in Cancer.
Iorio F et al., Cell, Volume 166 (2016), p. 740-754
Inferring causal molecular networks: empirical assessment through a community-based effort.
Hill SM et al., Nat Methods, Volume 13 (2016), p. 310-318
Pharmacogenomic agreement between two cancer cell line data sets.
Cancer Cell Line Encyclopedia Consortium, Genomics of Drug Sensitivity in Cancer Consortium., Nature, Volume 528 (2015), p. 84-87
Large-scale models of signal propagation in human cells derived from discovery phosphoproteomic data.
Terfve CD et al., Nat Commun, Volume 6 (2015), p. 8033
Prediction of human population responses to toxic compounds by a collaborative competition.
Eduati F et al., Nat Biotechnol, Volume 33 (2015), p. 933-940
Comparing signaling networks between normal and transformed hepatocytes using discrete logical models.
Saez-Rodriguez J et al., Cancer Res, Volume 71 (2011), p. 5400-5411
Discrete logic modelling as a means to link protein signalling networks with functional analysis of mammalian signal transduction.
Saez-Rodriguez J et al., Mol Syst Biol, Volume 5 (2009), p. 331