Saez-Rodriguez Group

Systems biomedicine

Our goal is to acquire a functional understanding of the deregulation of signalling networks in disease and to apply this knowledge to develop novel therapeutics. We focus on cancer, auto-immune and fibrotic diseases.


Our research is hypothesis-driven and tailored towards producing mathematical models that integrate diverse data sources. Because of this, we collaborate closely with experimental groups. A key emphasis of our work is to build models that are both mechanistic (to provide understanding) and predictive (to generate novel hypotheses). To build these models, we combine the existing knowledge of the underlying biochemical processes with functional data. A major focus of our group is the development of logic models of signaling networks that are trained with data derived from mass spectrometry and antibody-based technologies, as well as single-cell approaches.
In parallel, we analyse genomic and phenotypic data collected in large-scale drug screenings. We then strive to combine this information with our prior knowledge of the underlying pathways to ultimately build integrated mechanistic models. Our premise is that these will have enhanced ability to discern the mode of action of existing therapies and provide avenues for the development of new drugs.
While our research is driven by applications, we develop open-source computational tools that we share freely with the scientific community.
Finally, we also support the development of crowdsourcing, in particular collaboratives competitions for systems biology, through the DREAM challenges.

Group Leader

Julio Saez-Rodriguez



Gabriele Luetzeler


Staff Scientists

Francesco Iorio



Luis Tobalina Segura


Melanie Rinas


Luz Maria Garcia Alonso


Federica Eduati


Denes Turei


Bence Szalai


Attila Gabor


Vigneshwari Subramanian


Panuwat Trairatphisan


Mahmoud Ibrahim


PhD Students

Angeliki Kalamara


Aurélien Dugourd


Mi Yang


Enio Gjerga


Nicolàs Palacio


Christian Holland



Jakob Wirbel


Ferenc Tajti


Celine Chevalier


Hyojin Kim


The following people spent over 6 months with us:

Name Duration Position
Emanuel Gonçalves 2012-2017 PhD Student
Fatemeh Ghavidel 2015-2016 Postdoc (w O Stegle & A Brazma)
Pisanu Buphamalai 2015-2016 Trainee (w. M Brehme)
Ricardo Ramirez 2015-2016 Trainee
Johannes Stephan 2014-2015 Postdoc (w O Stegle)
Claudia Hernandez 2014-2015 Trainee
Martí Bernardo-Faura 2013-2015 Postdoc
Vitor Costa 2013-2013 Master Thesis
Luca Cerone 2013-2013 Postdoc
Ioannis Melas 2013-2014 Postdoc
Michael Schubert 2012-2016 PhD Student
Michael Menden 2011-2016 PhD student
Thomas Cokelaer 2011-2015 Staff Scientist
Martijn van Iersel 2011-2012 Postdoc
Aidan MacNamara 2010-2014 postdoc
Camille Terfve 2010-2014 PhD Student
David Henriques 2010-2011 Master Thesis





Toolbox for creating logic models of signaling networks and training them against data.

More about CellNOpt


Collection of literature curated signaling pathways and the Python module pypath.

More about OmniPath


A tool to build logic models from discovery mass-spectrometry based Phosphoproteomic data.

More about PHONEMeS


Python package to access Bioinformatics Web Services.

More about BioServices


Interface between R and Cytoscape.

More about Cyrface


Cytoscape plug-in for SBGN maps.

More about CySBGN


Code used in the scoring of DREAM challenges.

More about DREAMTools


R/Cytoscape pipeline to compare drug and disease gene expression profiles.

More about DrugVsDisease


Python library dedicated to the study pharmacogenomic relationships.

More about GDSCTools


Python package to infer kinase activities from phosphoproteomics datasets.

More about KinAct


Global optimization toolbox including metaheuristic and Bayesian methods.

More about MEIGO


R package for the randomisation of bipartite graphs.

More about Birewire


An R package for interactive network guided connectivity mapping.

More about iNRG-cMap


R package to identify pathway-level enrichments of genetic alterations.

More about SLAPenrich


An R package to infer pathway activity from gene expression data

More about PROGENy

The wordcloud is based on the number of joint publications with our collaborators

We are part of the Joint Research Center for Computational Biomedicine. We are thankful to our present and past collaborators, including (in alphabetic order):

  • Ruedi Aebersold, ETH Zurich
  • Leonidas G. Alexopoulos, National Technical University of Athens
  • Bernd Bodenmiller, University of Zurich
  • Julio Banga, (Bio)Process Engineering Group, CSIC
  • Pedro Beltrao, EMBL-EBI
  • CoLoMoTo Consortium, in particular Claudine Chaouiya, Denis Thieffry, Tomas Helikar, and Laurence Calzone
  • Thorsten Cramer, RWTH Aachen
  • Pedro R. Cutillas, Imperial College
  • Christian Frezza, MRC - Cambridge
  • DREAM Challenges, in particular Gustavo Stolovitzky
  • Mathew Garnett and Ultan McDermott, Sanger Institute
  • Anne-Claude Gavin, EMBL Heidelberg
  • Steffen Klamt, Max Planck Institute
  • Tamás Korcsmáros, Earlham Institute and Institute of Food Research
  • Rafael Kramann, RWTH Aachen
  • Douglas Lauffenburger, Massachusetts Institute of Technology
  • Christoph Merten, EMBL
  • Alexander Mitsos, RTWH Aachen, Germany
  • Miguel Angel Pujana, IDIBELL
  • Miguel Rocha, University of Minho
  • Eduard Sabido, CRG
  • Anne Siegel, INRIA/IRISA
  • Peter K. Sorger, Harvard Medical School
  • Oliver Stegle, EMBL-EBI
  • Pablo Villoslada, IDIBAPS - Hospital Clinic of Barcelona

Duration Name
2017-2022 EU IMI -TransQST: Translational quantitative systems toxicology to improve the understanding of the safety of medicines
2016-2019 ERACOSYSMED (BMBF) SYS4MS: Personalizing health care in Multiple Sclerosis using sytems medicine tools
2016-2019 EU H2020-PHC-02-2015: PrECISE: Personalized engine for Cancer integrative study and evaluation
2016-2020 BMBF LiSym: Liver systems medicine
2015-2019 EU H2020-MSCA-ITN-2014: SyMBioSys: Systematic Models for Biological Systems Engineering
2014-2018 Open Targets: Target identification and validation using pathway activities derived from functional genomics data
2014-2018 Open Targets: Novel Target Identification Through Genome-Scale CRISPR-Cas9 Knockout Screening in Human Cancer Cell Lines


While we do not have any specific opening at the moment, we are generally looking for talented PhD students and Postdocs interested in working at the interface of computational science, biomedicine and pharmacology. You are expected to hold a degree in statistics, mathematics, physics, engineering or computer science, or a degree in biological science with substantial experience in computational and statistical work.

We also have opportunities for student assistants (HiWi), master thesis, and internships, for a period of typically at least six months. We have often funding available for these positions.

If you are interested, please contact us at . Please include your CV, academic transcripts and the names of several references. In your e-mail please explain in which specific project, or recent publication you are interested and why. Please also explain how you think you could fit in our group. Include the words ’saezlab' in the email subject. Non-specific applications without this expression of interest or sent to a different address will not be considered.