| Recent advances in scaffold hopping: miniperspective Y Hu, D Stumpfe, J Bajorath Journal of medicinal chemistry 60 (4), 1238-1246, 2017 | 234 | 2017 |
| Recent progress in understanding activity cliffs and their utility in medicinal chemistry: miniperspective D Stumpfe, Y Hu, D Dimova, J Bajorath Journal of medicinal chemistry 57 (1), 18-28, 2014 | 222 | 2014 |
| MMP-cliffs: systematic identification of activity cliffs on the basis of matched molecular pairs X Hu, Y Hu, M Vogt, D Stumpfe, J Bajorath Journal of chemical information and modeling 52 (5), 1138-1145, 2012 | 205 | 2012 |
| Compound promiscuity: what can we learn from current data? Y Hu, J Bajorath Drug discovery today 18 (13-14), 644-650, 2013 | 152 | 2013 |
| Computational exploration of molecular scaffolds in medicinal chemistry: Miniperspective Y Hu, D Stumpfe, J Bajorath Journal of medicinal chemistry 59 (9), 4062-4076, 2016 | 127 | 2016 |
| How frequently are pan-assay interference compounds active? Large-scale analysis of screening data reveals diverse activity profiles, low global hit frequency, and many … S Jasial, Y Hu, J Bajorath Journal of medicinal chemistry 60 (9), 3879-3886, 2017 | 124 | 2017 |
| Lessons learned from molecular scaffold analysis Y Hu, D Stumpfe, J Bajorath Journal of chemical information and modeling 51 (8), 1742-1753, 2011 | 91 | 2011 |
| Current compound coverage of the kinome: miniperspective Y Hu, N Furtmann, J Bajorath Journal of medicinal chemistry 58 (1), 30-40, 2015 | 82 | 2015 |
| Advancing the activity cliff concept Y Hu, D Stumpfe, J Bajorath F1000Research 2, 2013 | 79 | 2013 |
| Activity-relevant similarity values for fingerprints and implications for similarity searching S Jasial, Y Hu, M Vogt, J Bajorath F1000Research 5, 2016 | 73 | 2016 |
| Entering the ‘big data’era in medicinal chemistry: molecular promiscuity analysis revisited Y Hu, J Bajorath Future science OA 3 (2), FSO179, 2017 | 68 | 2017 |
| Extending the activity cliff concept: structural categorization of activity cliffs and systematic identification of different types of cliffs in the ChEMBL database Y Hu, J Bajorath Journal of chemical information and modeling 52 (7), 1806-1811, 2012 | 66 | 2012 |
| Polypharmacology directed compound data mining: identification of promiscuous chemotypes with different activity profiles and comparison to approved drugs Y Hu, J Bajorath Journal of chemical information and modeling 50 (12), 2112-2118, 2010 | 63 | 2010 |
| From structure–activity to structure–selectivity relationships: quantitative assessment, selectivity cliffs, and key compounds L Peltason, Y Hu, J Bajorath ChemMedChem: Chemistry Enabling Drug Discovery 4 (11), 1864-1873, 2009 | 61 | 2009 |
| Exploring compound promiscuity patterns and multi-target activity spaces Y Hu, D Gupta-Ostermann, J Bajorath Computational and structural biotechnology journal 9 (13), e201401003, 2014 | 58 | 2014 |
| Molecular scaffolds with high propensity to form multi-target activity cliffs Y Hu, J Bajorath Journal of chemical information and modeling 50 (4), 500-510, 2010 | 58 | 2010 |
| Improving the Search Performance of Extended Connectivity Fingerprints through Activity‐Oriented Feature Filtering and Application of a Bit‐Density‐Dependent Similarity Function Y Hu, E Lounkine, J Bajorath ChemMedChem: Chemistry Enabling Drug Discovery 4 (4), 540-548, 2009 | 56 | 2009 |
| Determining the degree of promiscuity of extensively assayed compounds S Jasial, Y Hu, J Bajorath PLoS One 11 (4), e0153873, 2016 | 50 | 2016 |
| Learning from ‘big data’: compounds and targets Y Hu, J Bajorath Drug Discovery Today 4 (19), 357-360, 2014 | 50 | 2014 |
| High-resolution view of compound promiscuity Y Hu, J Bajorath F1000Research 2, 2013 | 49 | 2013 |
