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 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) and of ELLIS Heidelberg.

Research

Our research is application-driven and tailored towards producing computational models that integrate diverse data sources to better understand and treat diseases. Because of this, we collaborate closely with experimental groups. A major emphasis is to build context-specific models that are both mechanistic (to provide understanding) and predictive (to generate novel hypotheses). To build these models, we combine existing biochemical knowledge with different types of large scale data. We believe that this biological knowledge can be instrumental to move from pure correlation to causation in large data sets, and thereby identify the molecular processes that underlie specific phenomena.
 
We develop and apply methods to extract mechanistic features from diverse omics data,  recently also for single-cell data. We then combine these multi-omics data sets into causal networks. Finally, we build dynamic models of specific subsystems using logic formalisms that we can analyze and simulate to predict the effect of new perturbations.
We apply these strategies in the context of many disease conditions. Particular areas of interest for us are cancer and fibrosis (in particular in kidney, heart, and liver). While our research is driven by applications, we develop open-source computational tools that share freely with the scientific community.
 
Finally, we support scientific crowdsourcing, specifically collaboratives competitions, through the DREAM challenges.

 

Check below the publications section to see some of our recent work.

Group Leader

Julio Saez-Rodriguez

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Secretaries

Erika Schulz

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Lydia Roeder

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Bioinformatician

Nicolàs Palacio

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Research Area Leaders

Attila Gabor

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Aurélien Dugourd

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Jovan Tanevski

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Martín Garrido Rodríguez-Córdoba

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Postdocs

Denes Turei

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Jan Lanzer

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Ricardo O. Ramirez-Flores

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Arezou Rahimi

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Sebastian Lobentanzer

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Ahmet Sureyya Rifaioglu

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Pablo Rodríguez Mier

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Ece Kartal

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Chang Lu

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Christina Schmidt

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José Liñares Blanco

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Maria Puschhof

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PhD Students

Olga Ivanova

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Daniel Dimitrov

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Pau Badia i Mompel

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Sophia Müller-Dott

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Robin Fallegger

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Charlotte Boys

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Leonie Küchenhoff

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Philipp Schaefer

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Bárbara Zita Peters Couto

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Miguel Hernandez

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Associated members

Rebecca Terrall Levinson

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Nadine Tüchler

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Mira Burtscher

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Lorna Wessels

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Tim Rose

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Loan Vulliard

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Remi Trimbour

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Chiara Schiller

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Jennifer Habbes

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The following people spent over 6 months with us:

Name Duration Position
Fabian Fröhlich 2022-2023 PostDoc
Katharina Zirngibl 2021-2023 PostDoc
Marzia Sidri 2021-2022 project manager
Bartosz Bartmanski 2021-2021 Postdoc
Hanna Schumacher 2021 - 2023 Bioinformatician
Eleanor Fewings 2020-2021 Bioinformatician
Rosa Hernansaiz Ballesteros 2019-2021 PostDoc
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
Javier Perales-Patón 2018-2022 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
Christian Holland 2017 -2021 PhD Student
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

Publications

Preprints

Spatial cell type mapping of multiple sclerosis lesions

Lerma-Martin, Badia-i-Mompel et al. bioRxiv, 2022

Birewire

R package for the randomisation of bipartite graphs.

More about Birewire

CARNIVAL

Find causal paths upstream of transcription factors in signaling networks from transcriptomics

More about CARNIVAL

CellNOpt

Create logic models of signaling networks and train them with perturbation data

More about CellNOpt

CORNETO

Unified framework for network inference problems

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COSMOS

Mechanistic integration of multi-omics with prior knowledge into causal networks

More about COSMOS

DOT

An optimization framework for transferring cell features from a reference data to spatial omics

More about DOT

DREAMTools

Code used in the scoring of DREAM challenges.

More about DREAMTools

DrugVsDisease

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

More about DrugVsDisease

GDSCTools

Python library dedicated to the study pharmacogenomic relationships.

More about GDSCTools

LIANA

Estimate ligand-receptor interactions from single-cell transcriptomics using a variety of resources and methods

More about LIANA

LIANA+

Framework to infer inter- and intra-cellular signalling from single-cell and spatial omics

More about LIANA+

lipyd

Python module for lipidomics LC MS/MS data analysis

More about lipyd

MEIGO

Global optimization toolbox including metaheuristic and Bayesian methods.

More about MEIGO

ocEAn

Metabolic enzyme enrichment analysis

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PHONEMeS

Build causal signaling networks from untargeted mass-spectrometry Phosphoproteomics and prior knowledge

More about PHONEMeS

SLAPenrich

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

More about SLAPenrich

BioChatter

A platform for the biomedical application of Large Language Models

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BioCypher

A unifying framework for biomedical research knowledge graphs

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BioServices

Python package to access Bioinformatics Web Services.

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CollecTRI

Collection of Transcriptional Regulatory Interactions

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DoRothEA

Manually curated human regulons of genes downstream of Transcription Factors

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MetalinksDB

Database of protein-metabolite and small molecule ligand-receptor interactions

More about MetalinksDB

OmniPath

Molecular prior knowledge from more than 170 databases. Pathways, intercellular communication and more.

More about OmniPath

PROGENy

Collection of target genes (footprints) of signaling pathways

More about PROGENy

 

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):

  • Ruedi Aebersold, ETH Zurich
  • Leonidas G. Alexopoulos, National Technical University of Athens
  • Eduardo Villablanca, Karolinska Institute
  • 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
  • Christian Frezza, MRC – Cambridge
  • DREAM Challenges, in particular Gustavo Stolovitzky
  • Mathew Garnett and Ultan McDermott, Sanger Institute
  • 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 / EPFL
  • Alexander Mitsos, RTWH Aachen, Germany
  • Rainer Pepperkok, EMBL
  • Miguel Rocha, University of Minho
  • Anne Siegel, INRIA/IRISA
  • Peter K. Sorger, Harvard Medical School
  • Oliver Stegle, EMBL / DKFZ
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
2021-2024

LiSyM-Krebs: Mechanism-based Multiscale Model to Dissect the Tipping Point from Liver Cirrhosis to Hepatocellular Carcinoma

German Ministry of Education and Research (BMBF)
2021-2024

DeepSC2: Deep learning for single-cell genomics in cancer

German Ministry of Education and Research (BMBF)
2021-2023

Changes in the microbiome in PsA patients undergoing biologics therapy

Centers for Personalized Medicine Baden-Württemberg
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

CombiMS: a novel drug discovery method based on systems biology: combination therapy and biomarkers for Multiple Sclerosis

EU H2020 Health
2012-2015

BioPreDyn: New Bioinformatics Methods and Tools for Data-Driven Predictive Dynamic Modelling in Biotechnological Applications

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

Jobs

For all positions, candidates should email their CV and a letter of interest to jobs.saez {at} uni-heidelberg.de, including names of (ideally 3) references.  The letter of interest has to be tailored to our group, mentioning projects or articles of our group that you find interesting, and explaining how you would fit in our group. Please also provide a pointer to a code repository if possible.  Non-specific applications without this tailored expression of interest or sent to a different address will not be considered.

  • We are continuously looking for postdoctoral fellows, PhD students, and staff scientists to better understand and treat diseases including cancer and heart disease by analyzing multi-omics data sets, including single-cell and spatially resolved data. Candidates interested in using bioinformatics, machine learning, and mathematical modeling to analyze big data to advance personalized medicine are encouraged to contact us. Current post are available here, and we also welcome spontaneous applications.
  • We have opportunities for student assistants (HiWi), master/bachelor theses, and internships. In general, these are for a period of six months or longer, although shorter internships of 3-4 months are possible, in particular for local students. Besides the general information above, please include information on the lectures you have attended in your bachelor and (if already there) master courses.