| Accurate models for P-gp drug recognition induced from a cancer cell line cytotoxicity screen J Levatic, J Curak, M Kralj, T Smuc, M Osmak, F Supek Journal of medicinal chemistry 56 (14), 5691-5708, 2013 | 64 | 2013 |
| Self-training for multi-target regression with tree ensembles J Levatić, M Ceci, D Kocev, S Džeroski Knowledge-based systems 123, 41-60, 2017 | 62 | 2017 |
| Semi-supervised classification trees J Levatić, M Ceci, D Kocev, S Džeroski Journal of Intelligent Information Systems 49, 461-486, 2017 | 59 | 2017 |
| Mutational signatures are markers of drug sensitivity of cancer cells J Levatić, M Salvadores, F Fuster-Tormo, F Supek Nature communications 13 (1), 2926, 2022 | 54 | 2022 |
| The importance of the label hierarchy in hierarchical multi-label classification J Levatić, D Kocev, S Džeroski Journal of Intelligent Information Systems 45, 247-271, 2015 | 53 | 2015 |
| Semi-supervised trees for multi-target regression J Levatić, D Kocev, M Ceci, S Džeroski Information Sciences 450, 109-127, 2018 | 52 | 2018 |
| Semi-supervised learning for multi-target regression J Levatic, M Ceci, D Kocev, S Dzeroski | 34 | 2014 |
| Semi-supervised learning for quantitative structure-activity modeling J Levatić, S Džeroski, F Supek, T Šmuc Informatica 37 (2), 2013 | 22 | 2013 |
| Semi-supervised regression trees with application to QSAR modelling J Levatić, M Ceci, T Stepišnik, S Džeroski, D Kocev Expert Systems with Applications 158, 113569, 2020 | 21 | 2020 |
| Predicting thermal power consumption of the Mars Express satellite with machine learning M Breskvar, D Kocev, J Levatić, A Osojnik, M Petković, N Simidjievski, ... 2017 6th International conference on space mission challenges for …, 2017 | 19 | 2017 |
| Machine learning for predicting thermal power consumption of the mars express spacecraft M Petković, R Boumghar, M Breskvar, S Džeroski, D Kocev, J Levatić, ... IEEE Aerospace and Electronic Systems Magazine 34 (7), 46-60, 2019 | 18 | 2019 |
| Machine learning prioritizes synthesis of primaquine ureidoamides with high antimalarial activity and attenuated cytotoxicity J Levatić, K Pavić, I Perković, L Uzelac, K Ester, M Kralj, M Kaiser, ... European journal of medicinal chemistry 146, 651-667, 2018 | 17 | 2018 |
| Community structure models are improved by exploiting taxonomic rank with predictive clustering trees J Levatić, D Kocev, M Debeljak, S Džeroski Ecological Modelling 306, 294-304, 2015 | 10 | 2015 |
| Exploiting partially-labeled data in learning predictive clustering trees for multi-target regression: A case study of water quality assessment in Ireland S Nikoloski, D Kocev, J Levatić, DP Wall, S Džeroski Ecological Informatics 61, 101161, 2021 | 9 | 2021 |
| Semi-Supervised Predictive Clustering Trees for (Hierarchical) Multi-Label Classification J Levatić, M Ceci, D Kocev, S Džeroski International Journal of Intelligent Systems, 2024 | 7 | 2024 |
| Semi-supervised learning for structured output prediction J Levatić Informatica 46 (4), 2022 | 6 | 2022 |
| Whole-genome Mutational Analysis for Tumor-informed Detection of Circulating Tumor DNA in Patients with Urothelial Carcinoma I Nordentoft, SV Lindskrog, K Birkenkamp-Demtröder, S Gonzalez, ... European Urology 86 (4), 301-311, 2024 | 5 | 2024 |
| CLUSplus: A decision tree-based framework for predicting structured outputs M Petković, J Levatić, D Kocev, M Breskvar, S Džeroski SoftwareX 24, 101526, 2023 | 5 | 2023 |
| A framework for mutational signature analysis based on DNA shape parameters A Karolak, J Levatić, F Supek Plos one 17 (1), e0262495, 2022 | 5 | 2022 |
| Machine-learning ready data on the thermal power consumption of the Mars Express Spacecraft M Petković, L Lucas, J Levatić, M Breskvar, T Stepišnik, A Kostovska, ... Scientific Data 9 (1), 229, 2022 | 3 | 2022 |
Saso DzeroskiJozef Stefan Institute, Dept. of Knowledge TechnologiesVerified email at ijs.si
