Sergey Sosnin, PhD
Summer term 2024
Sosnin, S 2024, 'MolCompass: multi-tool for the navigation in chemical space and visual validation of QSAR/QSPR models', Journal of Cheminformatics, vol. 16, no. 1, 98. https://doi.org/10.1186/s13321-024-00888-z
Granulo, N, Sosnin, S, Digles, D & Ecker, GF 2024, 'The macrocycle inhibitor landscape of SLC‐transporter', Molecular Informatics, vol. 43, no. 5, e202300287. https://doi.org/10.1002/minf.202300287
Huang, J, Osthushenrich, T, MacNamara, A, Mälarstig, A, Brocchetti, S, Bradberry, S, Scarabottolo, L, Ferrada, E, Sosnin, S, Digles, D, Superti-Furga, G & Ecker, GF 2024, 'ProteoMutaMetrics: machine learning approaches for solute carrier family 6 mutation pathogenicity prediction', Rsc advances, vol. 14, no. 19, 00748, pp. 13083-13094. https://doi.org/10.1039/d4ra00748d
Smajić, A, Rami, I, Sosnin, S & Ecker, GF 2023, 'Identifying Differences in the Performance of Machine Learning Models for Off-Targets Trained on Publicly Available and Proprietary Data Sets', Chemical Research in Toxicology, vol. 36, no. 8, pp. 1300-1312. https://doi.org/10.1021/acs.chemrestox.3c00042
Sosnina, E, Sosnin, S & Fedorov, M 2023, 'Improvement of multi‑task learning by data enrichment: application for drug discovery', Journal of Computer-Aided Molecular Design, vol. 37, no. 4, pp. 183-200. https://doi.org/10.1007/s10822-023-00500-w
Practical Applications of Nonlinear Dimensionality Reduction Methods for Visualizing Chemical Space
Sergey Sosnin (Speaker)
14 Sep 2023
Activity: Talks and presentations › Talk or oral contribution › Science to Science
Deep learning for the exploration of chemical space and chemical data
Sergey Sosnin (Speaker)
2023
Activity: Talks and presentations › Talk or oral contribution › Science to Science
Department of Pharmaceutical Sciences
EDV-Beauftragter
Josef-Holaubek-Platz 2 (UZA II)
1090 Wien