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. James Rathman, Chihae Yang*, J. Vinicius Ribeiro, Aleksandra Mostrag, Shraddha Thakkar, Weida Tong, Bryan Hobocienski, Oliver Sacher, Tomasz Magdziarz, and Bruno Bienfait. 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.
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, Fernandez-Fuentes N, Furlong LI, Guney E, Oliva B. Biol Direct; 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., Callegaro G., Capella-Gutierrez S., Centeno E., Corvi J., Drew P., Drewe W.C., Fernández J.M., Furlong L., Guney M., Kors J.A., Mayer M.A., Pastor M., Piñero J., Ramírez-Anguita J.M., Ronzano F., Rowell P., Saüch-Pitarch J., Valencia A., van de Water B., van der Lei J., van Mulligen E. and Sanz F. Pharmaceuticals. 2021.
Guidelines for FAIR sharing of preclinical safety and off-target pharmacology data. Briggs K., Bosc N. Camara T., Diaz C., Drew P., Drewe W.C., Kors J., van Mulligen E., Pastor M. Pognan F., Quintana J.R., Sarntivijai S., Steger-Hartmann T. ALTEX. 2021.
Introducing the Concept of Virtual Control Groups into Preclinical Toxicology Testing. Steger-Hartmann T, Kreuchwig A, Vaas L, Wichard J, Bringezu F, Amberg A, Muster W, Pognan F, Barber C. 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
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. 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, Furlong LI. 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, Ravagli C, Marc P, Pastor M. 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 al. Nat Rev Drug Discov. 2017; 16, 811–812