Julio Saez-Rodriguez

Affiliations: 
2002-2007 Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Sachsen-Anhalt, Germany 
 2007-2010 Harvard Medical School 
 2010-2015 EMBL-European Bioinformatics Institute 
 2015-2018 University Hospital RWTH Aachen, Aachen, Nordrhein-Westfalen, Germany 
 2018- Heidelberg Universität 
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"Julio Saez-Rodriguez"
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Publications

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Wijaya LS, Gabor A, Pot IE, et al. (2023) A Network-based Transcriptomic Landscape of HepG2 cells Uncovering Causal Gene-Cytotoxicity Interactions Underlying Drug-Induced Liver Injury. Toxicological Sciences : An Official Journal of the Society of Toxicology
Kay EJ, Paterson K, Riera-Domingo C, et al. (2022) Author Correction: Cancer-associated fibroblasts require proline synthesis by PYCR1 for the deposition of pro-tumorigenic extracellular matrix. Nature Metabolism
Garrido-Rodriguez M, Zirngibl K, Ivanova O, et al. (2022) Integrating knowledge and omics to decipher mechanisms via large-scale models of signaling networks. Molecular Systems Biology. 18: e11036
Kay EJ, Paterson K, Riero-Domingo C, et al. (2022) Cancer-associated fibroblasts require proline synthesis by PYCR1 for the deposition of pro-tumorigenic extracellular matrix. Nature Metabolism. 4: 693-710
Hernansaiz-Ballesteros R, Holland CH, Dugourd A, et al. (2022) FUNKI: Interactive functional footprint-based analysis of omics data. Bioinformatics (Oxford, England)
Gabor A, Tognetti M, Driessen A, et al. (2021) Cell-to-cell and type-to-type heterogeneity of signaling networks: insights from the crowd. Molecular Systems Biology. 17: e10402
Lone AM, Giansanti P, Jørgensen MJ, et al. (2021) Systems approach reveals distinct and shared signaling networks of the four PGE receptors in T cells. Science Signaling. 14: eabc8579
Trairatphisan P, de Souza TM, Kleinjans J, et al. (2021) Contextualization of causal regulatory networks from toxicogenomics data applied to drug-induced liver injury. Toxicology Letters
Meyer P, Saez-Rodriguez J. (2021) Advances in systems biology modeling: 10 years of crowdsourcing DREAM challenges. Cell Systems. 12: 636-653
Tognetti M, Gabor A, Yang M, et al. (2021) Deciphering the signaling network of breast cancer improves drug sensitivity prediction. Cell Systems
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