| Predicting the early risk of chronic kidney disease in patients with diabetes using real-world data S Ravizza, T Huschto, A Adamov, L Böhm, A Büsser, FF Flöther, ... Nature medicine 25 (1), 57-59, 2019 | 149 | 2019 |
| Multi-omics data integration reveals metabolome as the top predictor of the cervicovaginal microenvironment NA Bokulich, P Łaniewski, A Adamov, DM Chase, JG Caporaso, ... PLOS Computational Biology 18 (2), e1009876, 2022 | 31 | 2022 |
| Experiences and lessons learned from two virtual, hands-on microbiome bioinformatics workshops MR Dillon, E Bolyen, A Adamov, A Belk, E Borsom, Z Burcham, ... PLoS computational biology 17 (6), e1009056, 2021 | 5 | 2021 |
| Reproducible acquisition, management and meta-analysis of nucleotide sequence (meta) data using q2-fondue M Ziemski, A Adamov, L Kim, L Flörl, NA Bokulich Bioinformatics 38 (22), 5081-5091, 2022 | 4 | 2022 |
| Supervised Machine Learning with q2-sample-classifier A Adamov Workshop on Microbiome Bioinformatics with QIIME2, 2021 | | 2021 |
| PREDICTING THE EARLY RISK OF CHRONIC KIDNEY DISEASE IN PEOPLE WITH DIABETES USING REAL WORLD DATA W Petrich, S Ravizza, T Huschto, A Adamov, L Bohm, A Busser, F Floether, ... DIABETES TECHNOLOGY & THERAPEUTICS 21, A76-A77, 2019 | | 2019 |
