Publications 1

eTRANSAFE: Building a sustainable framework to share reproducible drug safety knowledge with the public domain. Sarntivijai S, Blomberg N, Lauer KB, Briggs K, Steger-Hartmann T, Van der Lei J, et al.  F1000Research. 2022;11(ELIXIR):287.

High-throughput confocal imaging of differentiated 3D liver-like spheroid cellular stress response reporters for identification of drug-induced liver injury liability.  Hiemstra S, Ramaiahgari S, Wink S, Callegaro G, Coonen M, Meerman J, et al. Arch Toxicol . 2019;93(10):2895-2911.

Mapping the cellular response to electron transport chain inhibitors reveals selective signaling networks triggered by mitochondrial perturbation. Van der Stel W, Yang H, Vrijenhoek N, Schimming J, Callegaro G, Carta G, et al. Arch Toxicol. 2022;96(1):259-285.

Ensemble Prediction of Mitochondrial Toxicity Using Machine Learning Technology.  Bringezu F, Gómez-Tamayo J, Pastor M. Computational Toxicology. 2021;20:100189.

The human hepatocyte TXG-MAPr: WGCNA transcriptomic modules to support mechanism-based risk assessment. Callegaro G, Kunnen S, Trairatphisan P, Grosdidier S, Niemeijer M, den Hollander W, et al. Arch Toxicol. 2021;95(12):3745-3775.

Characterisation of the NRF2 transcriptional network and its response to chemical insult in primary human hepatocytes: implications for prediction of drug-induced liver injury. Copple I, den Hollander W, Callegaro G, Mutter F, Maggs J, Schofield A, et al. Arch Toxicol. 2019;93(2):385-399.

PharmacoNER Tagger: a deep learning-based tool for automatically finding chemicals and drugs in Spanish medical texts. Armengol-Estapé J, Soares F, Marimon M, Krallinger M. Genomics & Informatics. 2019;17(2):e15.

The DisGeNET knowledge platform for disease genomics: 2019 update. Piñero P, Ramírez-Anguita J, Saüch-Pitarch J, Ronzano F, Centeno E, Sanz F, et al. Nucleic Acids Research. 2020;48(D1):D845–D855.

GUILDify v2. 0: a tool to identify molecular networks underlying human diseases, their comorbidities and their druggable targets. Aguirre-Plans J, Piñero P, Sanz F, Furlong L, Fernandez-Fuentes N, Oliva B, et al. Journal of Molecular Biology. 2019;431(13):2477-2484.

Large scale comparison of QSAR and conformal prediction methods and their applications in drug discovery. Bosc N, Atkinson F, Félix E, Gaulton A, Hersey A, Leach AR. Journal of Cheminformatics. 2019;11(1):4.

Reply to “Missed opportunities in large scale comparison of QSAR and conformal prediction methods and their applications in drug discovery”. Bosc N, Atkinson F, Félix E, Gaulton A, Hersey A, Leach AR. Journal of Cheminformatics. 2019;11(1):64.

In silico Toxicology: from structure-activity relationships towards deep learning and adverse outcome pathways.  Hemmerich J, Ecker G. WIREs Computational Molecular Science. 2020;10:e1475.

Using machine learning methods and structural alerts for prediction of mitochondrial toxicity. Hemmerich J, Troger F, Füzi B, Ecker G. Molecular Informatics. 2020;39:2000005.

Image based liver toxicity prediction. Asilar E, Hemmerich J, Ecker GF. J. Chem. Inf. Model. 2020;60(3):1111–1121.

Cover: Conformational Oversampling as Data Augmentation for Molecules. Hemmerich J, Asilar E, Ecker GF. Journal of Cheminformatics. 2020;12(1):18.

Beyond SEND: Leveraging non-clinical data to drive translational research forward. Briggs K, Friedman B, Ferrara K, Pinches M, Drewe W, Riel C, et al. DDW. 2018. 

Improving the Safety Assessment of Chemicals and Drug Candidates by the Integration of Bioinformatics and Chemoinformatics Data. Steger-Hartmann T, Pognan F. Basic & Clinical Pharmacology and Toxicology. 2018;123:29–36

The DisGeNET cytoscape app: Exploring and visualizing disease genomics data. Piñero J, Saüch J, Sanz F, Furlong L.  Comput. Struct. Biotechnol. J. 2021;19:2960-2967.

Development of a Battery of In Silico Prediction Tools for Drug-Induced Liver Injury from the Vantage Point of Translational Safety Assessment. Rathman J, Yang C, Ribeiro J, Mostrag A, Thakkar S, Tong W, et al. Chem. Res. Toxicol.  2021;34(2):601–615.

Flame: an open source framework for model development, hosting, and usage in production environments. Pastor M, Gómez-Tamayo JC, Sanz F. Journal of Cheminformatics. 2021;13:31.

An ensemble learning approach for modeling the systems biology of drug-induced injury. Aguirre-Plans J, Souza T, Piñero J, Callegaro G, Kunnen SJ, Sanz F, et al. Biol Direct. 2021;16:5.

The eTRANSAFE Project on Translational Safety Assessment through Integrative Knowledge Management: Achievements and Perspectives. Pognan F, Steger-Hartmann T, Díaz C, Blomberg N, Bringezu F, Briggs K, et al. Pharmaceuticals. 2021;14(3):237.

Guidelines for FAIR sharing of preclinical safety and off-target pharmacology data. Briggs K, Bosc N. Camara T, Diaz C, Drew P, Drewe W, et al.T. ALTEX. 2021;8(2):187-197.

Introducing the Concept of Virtual Control Groups into Preclinical Toxicology Testing. Steger-Hartmann T, Kreuchwig A, Vaas L, Wichard J, Bringezu F, Amberg A, et al. ALTEX. 2020;37(3):343-349.

Computational approaches for Drug-induced liver injury (DILI) prediction: state of the art and challenges. Béquignon O, Pawar G, van de Water B, Cronin M, van Westen G. BIOMED SCI. 2019;2:308-329.

In Silico Toxicology Data Resources to Support Read-Across and (Q)SAR. Pawar G, Madden J, Ebbrell D, Cronin M. Front. Pharmacol. 2019;10:561.

Curation and analysis of clinical pathology parameters and histopathologic findings from eTOXsys, a large database project (eTOX) for toxicologic studies. Pinches M, Thomas R, Porter R, Camidge L, Briggs K. REGUL TOXICOL PHARM. 2019;107:104396.

In Silico models in drug development: where we are. Piñero J, Furlong L, Sanz F. Curr Opin Pharmacol. 2018;42:111-121.

Development of an Infrastructure for the Prediction of Biological Endpoints in Industrial Environments. Lessons Learned at the eTOX Project. Pastor M, Quintana J, Sanz F. Front. Pharmacol. 2018;9:1147.

Network, Transcriptomic and Genomic Features Differentiate Genes Relevant for Drug Response Piñero J, Gonzalez-Perez A, Guney E, Aguirre-Plans J, Sanz F, Oliva B, et al. Front. Genet. 2018;9:412.

Generating modelling data from repeat-dose toxicity reports. López-Massaguer O, Pinto-Gil K, Sanz F, Amberg A, Anger L, Stolte M, et al.  TOXICOL SCI 2018;162(1):287-300.

Legacy data sharing to improve drug safety assessment: the eTOX project. Sanz F, Pognan F, Steger-Hartmann T, Díaz C, Cases M, Pastor M, et alNat Rev Drug Discov. 2017;16:811-812.


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