| Predicting treatment benefit in multiple myeloma through simulation of alternative treatment effects J Ubels, P Sonneveld, EH van Beers, A Broijl, MH van Vliet, J de Ridder Nature communications 9 (1), 2943, 2018 | 34 | 2018 |
| RAINFOREST: a random forest approach to predict treatment benefit in data from (failed) clinical drug trials J Ubels, T Schaefers, C Punt, HJ Guchelaar, J de Ridder Bioinformatics 36 (Supplement_2), i601-i609, 2020 | 25 | 2020 |
| A data-driven interactome of synergistic genes improves network-based cancer outcome prediction A Allahyar, J Ubels, J de Ridder PLOS Computational Biology 15 (2), e1006657, 2019 | 18 | 2019 |
| Mutation signatures of pediatric acute myeloid leukemia and normal blood progenitors associated with differential patient outcomes AM Brandsma, EJM Bertrums, MJ van Roosmalen, DA Hofman, R Oka, ... Blood cancer discovery 2 (5), 484-499, 2021 | 15 | 2021 |
| Gene networks constructed through simulated treatment learning can predict proteasome inhibitor benefit in multiple myeloma J Ubels, P Sonneveld, MH van Vliet, J de Ridder Clinical Cancer Research 26 (22), 5952-5961, 2020 | 11 | 2020 |
| Improved detection of colibactin-induced mutations by genotoxic E. coli in organoids and colorectal cancer AR Huber, C Pleguezuelos-Manzano, J Puschhof, J Ubels, C Boot, ... Cancer Cell 42 (3), 487-496. e6, 2024 | 8 | 2024 |
| The combination of SKY92 and ISS provides a powerful tool to identify both high risk and low risk multiple myeloma cases, validation in two independent cohorts M van Vliet, J Ubels, L de Best, E van Beers, P Sonneveld Blood 126 (23), 2970, 2015 | 8 | 2015 |
| Human induced pluripotent stem cells display a similar mutation burden as embryonic pluripotent cells in vivo KAL Hasaart, F Manders, J Ubels, M Verheul, MJ van Roosmalen, ... Iscience 25 (2), 2022 | 7 | 2022 |
| Mutation signatures of pediatric acute myeloid leukemia and normal blood progenitors associated with differential patient outcomes. Blood Cancer Discov 2021; 2 (9): 484-499 AM Brandsma, E Bertrums, MJ van Rooismalen, DA Hofman, R Oka, ... BCD-21-0010.[Europe PMC free article][Abstract][CrossRef][Google Scholar], 0 | 5 | |
| The SKY92 prognostic marker is validated in eight multiple myeloma clinical datasets M Van Vliet Duin, R Kuiper, J Ubels, B Dumee, L Bosman, E Van Beers, ... Haematologica 101, 83, 2016 | 3 | 2016 |
| A robust gene expression signature to predict proteasome inhibitor benefit in Multiple Myeloma J Ubels, P Sonneveld, MH van Vliet, J de Ridder medRxiv, 2019.12. 16.19015024, 2019 | 1 | 2019 |
| Method for identifying signatures for predicting treatment response J De Ridder, J Ubels US Patent App. 17/995,525, 2023 | | 2023 |
| Method for identifying gene expression signatures MH Van Vliet, J Ubels, J De Ridder US Patent App. 16/500,379, 2021 | | 2021 |
| The best treatment for every patient: New algorithms to predict treatment benefit in cancer using genomics and transcriptomics J Ubels | | 2020 |
| A data-driven interactome of synergistic genes improves network-based cancer outcome prediction J Ubels, ID Jeroen de Ridder | | 2019 |
| TOPSPIN: a novel algorithm to predict treatment specific survival in cancer J Ubels, EH van Beers, P Sonneveld, MH van Vliet, J de Ridder HAEMATOLOGICA 102, 524-525, 2017 | | 2017 |
| ROBUSTNESS OF THE PROGNOSTIC VALUE OF THE SKY92 MARKER VERSUS FISH MARKERS ACROSS NINE MULTIPLE MYELOMA COHORTS M Van Vliet, R Kuiper, J Ubels, L Bosman, B Dumee, E van Beers, ... HAEMATOLOGICA 101, 520-521, 2016 | | 2016 |
| Risk stratification by SKY92+ ISS outperforms ifish markers t (4; 14) and del (17p) in multiple myeloma M Van Vliet, R Kuiper, J Ubels, B Dumee, L Bosman, E Van Beers, ... Haematologica 101 (Supplement 1), 86, 2016 | | 2016 |
