Julio Saez-Rodriguez
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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 disease. Towards this goal, we integrate big (‘Omics’) data with mechanistic molecular knowledge into statistical and machine learning methods, and we share our tools as free open-source packages.
We are at the Institute for Computational Biomedicine at the Medical Faculty of Heidelberg University and Heidelberg University Hospital. We are also part of the Molecular Medicine Partnership Unit (MMPU) between the Medical Faculty of the University of Heidelberg and the European Molecular Biology Laboratory (EMBL).
Julio Saez-Rodriguez
More...Erika Schulz
More...Eleanor Fewings
More...Denes Turei
More...Attila Gabor
More...Jovan Tanevski
More...Rosa Hernansaiz Ballesteros
More...Javier Perales-Patón
More...Bartosz Bartmanski
More...Katharina Zirngibl
More...Arezou Rahimi
More...The following people spent over 6 months with us:
Name | Duration | Position |
---|---|---|
Igor Bulanov | 2019-2020 | intern |
Minoo Ashtiani | 2019-2020 | intern |
Alice Driessen | 2019-2020 | intern |
Ana Victoria Ponce-Bobadilla | 2019-2020 | Postdoc |
Alberto Valdeolivas Urbelz | 2019-2020 | Postdoc |
Charlie Pieterman | 2018-2018 | intern |
Anika Liu | 2018-2018 | Master Thesis |
Hyojin Kim | 2017-2020 | Phd student |
Nicolas Palacio-Escat | 2017-2020 | PhD Student |
Panuwat Trairatphisan | 2017-2019 | Postdoc |
Bence Szalai | 2017-2018 | Postdoc |
Ferenc Tajti | 2017-2018 | Intern |
Francesco Ceccarelli | 2017-2018 | intern |
Vigneshwari Subramanian | 2017-2018 | Postdoc |
Mahmoud Ibrahim | 2017 -2017 | Postdoc |
Enio Gjerga | 2016-2020 | Phd student |
Luis Tobalina Segura | 2016-2019 | Postdoc |
Melanie Rinas | 2016-2019 | Postdoc |
Mi Yang | 2015-2019 | PhD Student / Postdoc |
Angeliki Kalamara | 2015-2019 | PhD Student |
Jakob Wirbel | 2015-2017 | Intern & Master Thesis |
Fatemeh Ghavidel | 2015-2016 | Postdoc (w O Stegle & A Brazma) |
Pisanu Buphamalai | 2015-2016 | Trainee (w. M Brehme) |
Ricardo Ramirez | 2015-2016 | Trainee |
Luz Garcia-Alonso | 2014-2018 | Postdoc |
Johannes Stephan | 2014-2015 | Postdoc (w O Stegle) |
Claudia Hernandez | 2014-2015 | Trainee |
Martí Bernardo-Faura | 2013-2015 | Postdoc |
Ioannis Melas | 2013-2014 | Postdoc |
Vitor Costa | 2013-2013 | Master Thesis |
Luca Cerone | 2013-2013 | Postdoc |
Emanuel Gonçalves | 2012-2017 | PhD Student |
Michael Schubert | 2012-2016 | PhD Student |
Michael Menden | 2011-2016 | PhD student |
Thomas Cokelaer | 2011-2015 | Staff Scientist |
Martijn van Iersel | 2011-2012 | Postdoc |
Federica Eduati | 2011 - 2017 | Postdoc |
Francesco Iorio | 2010-2017 | Postdoc / Senior Bioinformatician |
Aidan MacNamara | 2010-2014 | Postdoc |
Camille Terfve | 2010-2014 | PhD Student |
David Henriques | 2010-2011 | Master Thesis |
Dugourd A et al. Molecular Systems Biology, 2021
Yang M et al. Cell Systems, 2020
Eduati F et al. Molecular systems biology, 2020
Holland CH et al. Genome Biology, 2020
Garcia-Alonso L et al. Genome Res, 2019
Menden MP et al. Nat Commun, 2019
Eduati F et al. Nat Commun, 2018
Schubert M et al. Nat Commun, 2018
Türei D et al. Nat Methods, 2016
Sciacovelli M et al. Nature, 2016
Iorio F et al. Cell, 2016
Hill SM et al. Nat Methods, 2016
Terfve CD et al. Nat Commun, 2015
Eduati F et al. Nat Biotechnol, 2015
Dugourd A et al. Molecular Systems Biology, 2021
Petkevicius et al et al. FASEB Journal, 2021
Pawluczyk et al. et al. Kidney Int, 2021
Cappelletti et al. Cell, 2020
Kuppe, Perales-Paton et al. Nephrol Dial Transplant, 2020
Wang et al. et al. eLife, 2020
Szalai et al. FEBS letters, 2020
Kuppe et al. Nature, 2020
Mohs et al. J Hepatology, 2020
Rinschen et al. Nature Rev Nephrology, 2020
Trairatphisan et al et al. 2021
Douglass Allaway, Szalai et al. 2020
Kuppe, Ramirez Flores, Li, et al. 2020
Turei et al. 2020
Ma et al. 2020
Ramirez-Flores, Lanzer et al. 2020
Tanevski J et al. 2020
A method to find causal signalling pathways upstream of gene expression data.
More about CARNIVAL
CARNIVAL (CAusal Reasoning for Network identification using Integer VALue programming) allows to derive perturbed signalling pathways topology after drugs perturbation based on gene expression data. CARNIVAL is available as an R package, also in Bioconductor.
Code Repository | Website | Publication |
---|---|---|
github.com/saezlab/carnival | saezlab.github.io/CARNIVAL |
Liu A et al., npj Systems Biology and Applications, 2019 |
Toolbox for creating logic models of signaling networks and training them against data.
More about CellNOpt
CellNetOptimizer (CellNOpt) is a toolbox for creating logic-based models of signal transduction networks, and training them against high-throughput biochemical data, and is freely available both for R and matlab.
Code Repository | Website | Publication |
---|---|---|
github.com/cellnopt/cellnopt | saezlab.github.io/CellNOptR/ |
Terfve C et al., BMC Syst Biol, 2012 |
A method to mechanistically and causally integrate phosphoproteomics, transcriptomics, and metabolomics.
More about COSMOS
COSMOS (Causal Oriented Search of Multi-Omic Space) is a method that integrates phosphoproteomics, transcriptomics, and metabolomics data sets. COSMOS leverages extensive prior knowledge of signaling pathways, metabolic networks, and gene regulation with computational methods to estimate activities of transcription factors and kinases as well as network-level causal reasoning. This pipeline can provide mechanistic explanations for experimental observations across multiple omic data sets.
Code Repository | Website | Publication |
---|---|---|
github.com/saezlab/COSMOS/ | saezlab.github.io/COSMOS/ |
Dugourd A et al., Molecular Systems Biology, 2021 |
An R package to decouple gene sets from statistics
More about decoupleR
Usually functional genomics tools consist of a fixed combination of gene sets and statistical approach. To overcome this limitation this package allows to combine a variety of gene sets with a variety of statistics.
Code Repository | Website |
---|---|
github.com/saezlab/decoupleR | saezlab.github.io/decoupleR/ |
Framework to estimate single sample TF activities from gene expression data based on a manually curated human regulon
More about DoRothEA
Framework to estimate single sample TF activities from gene expression data based on a manually curated human regulon
An explainable machine learning framework for knowledge extraction and analysis of single-cell, highly multiplexed, spatially resolved data.
More about MISTy
Multiview Intercellular SpaTial modeling framework (MISTy) is an explainable machine learning framework for knowledge extraction and analysis of single-cell, highly multiplexed, spatially resolved data. MISTy facilitates an in-depth understanding of marker interactions by profiling the intra- and intercellular relationships. MISTy is a flexible framework able to process a custom number of views. Each of these views can describe a different spatial context, i.e., define a relationship among the observed expressions of the markers, such as intracellular regulation or paracrine regulation.
Code Repository | Website |
---|---|
github.com/saezlab/misty/ | saezlab.github.io/misty/ |
A database of molecular prior knowledge focusing on literature curated signaling pathways and inter-cellular communication.
More about OmniPath
OmniPath is a comprehensive collection of molecular prior knowledge such as literature curated human and rodent signaling pathways, enzyme-substrate interactions, protein complexes, molecular annotations (function, localization and many others) and inter-cellular communication roles. OmniPath is built by pypath, a powerful Python module for molecular networks and pathways analysis. It is also available by a web service at http://omnipathdb.org/, an R/Bioconductor package OmnipathR and the OmniPath Cytoscape app.
Code Repository | Website | Publication |
---|---|---|
github.com/saezlab/pypath | omnipathdb.org/ |
Türei D et al., Nat Methods, 2016 Ceccarelli F et al., Bioinformatics, 2019 |
A tool to build logic models from discovery mass-spectrometry based Phosphoproteomic data.
More about PHONEMeS
A tool to build logic models from discovery mass-spectrometry based Phosphoproteomic data.
Code Repository | Website | Publication |
---|---|---|
github.com/saezlab/PHONEMeS/ | saezlab.github.io/PHONEMeS/ |
Terfve CD et al., Nat Commun, 2015 |
An R package to infer pathway activity from gene expression data
More about PROGENy
PROGENy (Pathway RespOnsive GENes) aims to infer activity of cancer-relevant signaling pathways using transcriptomics data.
Code Repository | Website | Publication |
---|---|---|
github.com/saezlab/progeny | saezlab.github.io/progeny/ |
Schubert M et al., Nat Commun, 2018 Holland CH et al., Biochim Biophys Acta Gene Regul Mech, 2019 |
Python package to access Bioinformatics Web Services.
More about BioServices
BioServices is a Python package that provides access to many Bioinformatics Web Services (e.g., UniProt) and a framework to easily implement Web Service wrappers (based on WSDL/SOAP or REST protocols).
Code Repository | Website | Publication |
---|---|---|
github.com/cokelaer/bioservices | pypi.python.org/pypi/bioservices |
Cokelaer T et al., Bioinformatics, 2013 |
R package for the randomisation of bipartite graphs.
More about Birewire
Birewire is an R package implementing high-performing routines for the randomisation of bipartite graphs preserving their node degrees (i.e. Network Rewiring), through the Switching Algorithm (SA) . BiRewire analytically estimates the number of Switching Steps to be performed in order for the similarity between the original network and its rewired version to reach a plateau (i.e. to achieve the maximal level of randomness) according to the lower bound.
Code Repository | Website | Publication |
---|---|---|
github.com/saezlab/BiRewire | saezlab.github.io/BiRewire/ |
Iorio F et al., BMC Bioinformatics, 2016 |
Interface between R and Cytoscape.
More about Cyrface
Cyrface establishes an interface between R and Cytoscape by using different Java-R libraries, e.g. Rserve, RCaller. Cyrface can be used as a Cytos cape plug-in, e.g. to run R commands within Cytoscape, or used as a library to allow your plug-in to connect to R.
Code Repository | Website | Publication |
---|---|---|
github.com/saezlab/cyrface/ | saezlab.github.io/cyrface/ |
Gonçalves E et al., F1000Res, 2013 |
Cytoscape plug-in for SBGN maps.
More about CySBGN
CySBGN is a Cytoscape plug-in that extends the use of Cytoscape visualization and analysis features to SBGN maps. CySBGN adds support to Cytoscape to import, export, visualize, validate and analyse SBGN maps.
Code Repository | Website | Publication |
---|---|---|
github.com/saezlab/cysbgn | saezlab.github.io/cysbgn/ |
Gonçalves E et al., BMC Bioinformatics, 2013 |
Code used in the scoring of DREAM challenges.
More about DREAMTools
DREAMTools provides the code used in the scoring of DREAM challenges that pose fundamental questions about system biology and translational medicine.
Code Repository | Website | Publication |
---|---|---|
github.com/dreamtools/dreamtools | dreamtools.readthedocs.io/en/latest/ |
Cokelaer T et al., F1000Res, 2015 |
R/Cytoscape pipeline to compare drug and disease gene expression profiles.
More about DrugVsDisease
DrugVsDisease (DvD) provides a pipeline, available through R or Cytoscape, for the comparison of drug and disease gene expression profiles from public microarray repositories.
Code Repository | Website | Publication |
---|---|---|
github.com/saezlab/DrugVsDisease | saezlab.github.io/DrugVsDisease/ |
Pacini C et al., Bioinformatics, 2012 |
Python library dedicated to the study pharmacogenomic relationships.
More about GDSCTools
GDSCTools is an open-source Python library dedicated to the study pharmacogenomic relationships in the context of the GDSC (Genomics of Drug Sensitivity in Cancer) project. The main developer is Thomas Cokelaer (Institut Pasteur), and it is a joint effort with the groups of Mathew Garnett (Sanger Institute) and Julio Saez-Rodriguez.
GDSCTools is hosted by GitHub and documented here.
Code Repository | Website | Publication |
---|---|---|
github.com/CancerRxGene/gdsctools | gdsctools.readthedocs.io/en/master/ |
Cokelaer T et al., Bioinformatics, 2018 |
An R package for interactive network guided connectivity mapping.
More about iNRG-cMap
iNRG_cMap (iterative NetwoRk Guided connectivity Mapping) a strategy that refines these unbiased approaches by making use of prior knowledge about the analysed compounds to compute refined transcriptional signatures of drug response. Making use of transcriptional data from the Connectivity Map and building on the MANTRA method, iNRG_cMap is able to disentangle spurious effects due to non-relevant secondary drug effects, thus enhancing the predictive power of the resulting refined signatures.
Code Repository | Website | Publication |
---|---|---|
github.com/saezlab/iNRG_cMAP | saezlab.github.io/iNRG_cMAP/ |
Iorio F et al., PLoS One, 2015 |
Python package to infer kinase activities from phosphoproteomics datasets.
More about KinAct
KinAct is a python package with different computational methods to infer kinase activities from phosphoproteomics datasets.
Code Repository | Website |
---|---|
github.com/saezlab/kinact | saezlab.github.io/kinact/ |
lipyd is a Python module for lipidomics LC MS/MS data analysis.
More about lipyd
Code Repository | Website |
---|---|
github.com/saezlab/lipyd | saezlab.github.io/lipyd |
Global optimization toolbox including metaheuristic and Bayesian methods.
More about MEIGO
MEIGO is a global optimization toolbox that includes a number of metaheuristic methods as well as a Bayesian inference method for parameter estimation. It is developed jointly with the group of Julio Banga.
MEIGO is described in (Egea et al, BMC Bioinformatics, 2014), and hosted here.
Website | Publication |
---|---|
gingproc.iim.csic.es/meigo.html |
Egea JA et al., BMC Bioinformatics, 2014 |
R package to identify pathway-level enrichments of genetic alterations.
More about SLAPenrich
SLAPEnrich, a statistical method implemented in an open source R package, to identify pathway-level enrichments of genetic alterations.
Code Repository | Website | Publication |
---|---|---|
github.com/saezlab/SLAPenrich | saezlab.github.io/SLAPenrich/ |
Iorio F et al., Sci Rep, 2018 |
The wordcloud is based on the number of joint publications with our collaborators
We are thankful to our present and past collaborators, including (in alphabetic order):
Duration | Name | Agency |
---|---|---|
2021-2025 | DECIDER: Improved clinical decisions via integrating multiple data levels to overcome chemotherapy resistance in high-grade serous ovarian cancer |
European Union |
2021 | Analysis of essentiality in cancer using CRISPR-Cas9 screenings |
Sanofi |
2020-2022 | MSCare-A Systems Medicine Approach to Stratification of Cancer Recurrence |
German Ministry of Education and Research (BMBF) |
2020-2022 | Analysis of multi-omics and spatial transcriptomics data |
GSK |
2020-2021 | BioDATEN : Bioinformatics DATa Environment |
Ministry of Science, Research and Art, Baden Wuerttemberg |
2020-2021 | Single cell resolution of human chronic kidney disease for precision medicine in nephrology |
DFG German Research Council |
2020 - 2024 | StrategyCKD: System omics to unravel the gut-kidney axis in Chronic Kidney Disease |
European Uunion H220-MSCA-ITN |
2020 - 2022 | HPC Center of Excellence in Personalised Medicine – PerMedCoE |
European Union (H2020-EU.1.4.1.3) |
2019-2022 | individualizedPaediatricCure: Cloud-based virtual-patient models for precision paediatric oncology |
European Union H2020 Health |
2019-2022 | LaMarcK: Longitudinal Multiomics Characterization of disease using prior Knowledge |
German Ministry of Education and Research (BMBF) |
2019-2022 | Validating microfluidics-based personalized cancer therapy in mouse models |
DFG German Research Council |
2019-2021 | Informatics for Life |
Klaus-Tschira Stiftung |
2017-2021 | TransQST: Translational quantitative systems toxicology to improve the understanding of the safety of medicines |
EU IMI Innovative Medicines Initiative |
2017-2018 | Analysis of mass spectrometry proteomics and drug treatment |
OncoSignature/Acrivon |
2016-2020 | LiSym: Liver systems medicine |
BMBF |
2016-2019 | SYS4MS: Personalizing health care in Multiple Sclerosis using sytems medicine tools |
BMBF |
2016-2018 | PrECISE: Personalized engine for Cancer integrative study and evaluation |
EU H2020 Health |
2016-2018 | CPTAC DREAM Challenge |
National Cancer Institute (USA) |
2015-2019 | Joint Research Center for Computational Biomedicine |
Bayer AG |
2015-2018 | SyMBioSys : Systematic Models for Biological Systems Engineering Training Network |
EU H2020 Health MSCA-ITN |
2014-2016 | Novel Target Identification Through Genome-Scale CRISPR-Cas9 Knockout Screening in Human Cancer Cell Lines |
Center for Therapeutic Target Validation |
2014-2016 | Target identification and validation using pathway activities derived from functional genomics data |
Center for Therapeutic Target Validation |
2013-2014 | EU H2020 Health | |
2012-2015 | EU H2020 Health | |
2012-2014 | Understanding drug mode of action via statistical integration of functional genomic studies and literature-derived signalling networks |
Medical Research Council (UK) |
2011-2012 | Analysis of mass spectrometry phosphoproteomics data in the context of insulin signal processing and functional alterations thereof |
Sanofi |
For all positions, candidates should email their CV (including names of three references) and a letter of interest to jobs.saez {at} bioquant.uni-heidelberg.d
1. We have currently one PostDoctoral position in Machine Learning for Single-cell Genomics in Cancer.
2. We also welcome spontaneous applications for PostDoctoral and PhD positions.
3. 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.