Smajić, A, Grandits, M & Ecker, GF 2023, 'Privacy-preserving techniques for decentralized and secure machine learning in drug discovery', Drug Discovery Today, vol. 28, no. 12, pp. 103820. https://doi.org/10.1016/j.drudis.2023.103820

Grandits, M & Ecker, GF 2023, 'Ligand- and Structure-based Approaches for Transmembrane Transporter Modeling', Current drug research reviews. https://doi.org/10.2174/2589977515666230508123041

van der Noord, VE, van der Stel, W, Louwerens, G, Verhoeven, D, Kuiken, HJ, Lieftink, C, Grandits, M, Ecker, GF, Beijersbergen, RL, Bouwman, P, Le Dévédec, SE & van de Water, B 2023, 'Systematic screening identifies ABCG2 as critical factor underlying synergy of kinase inhibitors with transcriptional CDK inhibitors', Breast Cancer Research, vol. 25, no. 1, 51, pp. 51. https://doi.org/10.1186/s13058-023-01648-x

Smajic, A, Grandits, M & Ecker, GF 2022, 'Using Jupyter Notebooks for re-training machine learning models', Journal of Cheminformatics, vol. 14, no. 1, 54. https://doi.org/10.1186/s13321-022-00635-2

Brecklinghaus, T, Albrecht, W, Kappenberg, F, Duda, J, Vartak, N, Edlund, K, Marchan, R, Ghallab, A, Cadenas, C, Günther, G, Leist, M, Zhang, M, Gardner, I, Reinders, J, Russel, FGM, Foster, AJ, Williams, DP, Damle-Vartak, A, Grandits, M, Ecker, G, Kittana, N, Rahnenführer, J & Hengstler, JG 2022, 'The hepatocyte export carrier inhibition assay improves the separation of hepatotoxic from non-hepatotoxic compounds', Chemico-Biological Interactions, vol. 351, 109728. https://doi.org/10.1016/j.cbi.2021.109728

Superti-Furga, G, Lackner, D, Wiedmer, T, Ingles-Prieto, A, RESOLUTE consortium & Steppan, C 2020, 'The RESOLUTE consortium: unlocking SLC transporters for drug discovery', Nature Reviews. Drug Discovery, vol. 19, no. 7, pp. 429-430. https://doi.org/10.1038/d41573-020-00056-6

Montanari, F, Knasmüller, B, Kohlbacher, S, Hillisch, C, Baierová, C, Grandits, M & Ecker, GF 2020, 'Vienna LiverTox Workspace-A Set of Machine Learning Models for Prediction of Interactions Profiles of Small Molecules With Transporters Relevant for Regulatory Agencies', Frontiers in Chemistry, vol. 7, 899. https://doi.org/10.3389/fchem.2019.00899

Jain, S, Grandits, M & Ecker, GF 2018, 'Interspecies comparison of putative ligand binding sites of human, rat and mouse P-glycoprotein', European Journal of Pharmaceutical Sciences, vol. 122, pp. 134-143. https://doi.org/10.1016/j.ejps.2018.06.022

Ecker, G, Knasmueller, B, Neckam, B, Grandits, M & Dangl, A 2018, 'ToxPHACTS - Data driven decision support for toxicologists', American Chemical Society. Abstracts of Papers (at the National Meeting), vol. 256.

Schuetz, DA, Richter, L, Amaral, M, Grandits, M, Graedler, U, Musil, D, Buchstaller, H-P, Eggenweiler, H-M, Frech, M & Ecker, GF 2018, 'Ligand Desolvation steers on-rate and impacts Drug Residence Time of Heat shock protein 90 (Hsp90) Inhibitors', Journal of Medicinal Chemistry, vol. 61, no. 10, pp. 4397–4411. https://doi.org/10.1021/acs.jmedchem.8b00080

Jain, S, Grandits, M, Richter, L & Ecker, GF 2017, 'Structure based classification for bile salt export pump (BSEP) inhibitors using comparative structural modeling of human BSEP', Journal of Computer-Aided Molecular Design, vol. 31, no. 6, pp. 507-521. https://doi.org/10.1007/s10822-017-0021-x