| ResFinder–an open online resource for identification of antimicrobial resistance genes in next-generation sequencing data and prediction of phenotypes from genotypes AF Florensa, RS Kaas, PTLC Clausen, D Aytan-Aktug, FM Aarestrup Microbial genomics 8 (1), 000748, 2022 | 216 | 2022 |
| Understanding and predicting ciprofloxacin minimum inhibitory concentration in Escherichia coli with machine learning BÁ Pataki, S Matamoros, BCL van der Putten, D Remondini, E Giampieri, ... Scientific reports 10 (1), 15026, 2020 | 34 | 2020 |
| Prediction of acquired antimicrobial resistance for multiple bacterial species using neural networks D Aytan-Aktug, PTLC Clausen, V Bortolaia, FM Aarestrup, O Lund Msystems 5 (1), 10.1128/msystems. 00774-19, 2020 | 32 | 2020 |
| A genomic data resource for predicting antimicrobial resistance from laboratory-derived antimicrobial susceptibility phenotypes M VanOeffelen, M Nguyen, D Aytan-Aktug, T Brettin, EM Dietrich, ... Briefings in Bioinformatics 22 (6), bbab313, 2021 | 19 | 2021 |
| Data integration for prediction of weight loss in randomized controlled dietary trials RL Nielsen, M Helenius, SL Garcia, HM Roager, D Aytan-Aktug, ... Scientific Reports 10 (1), 20103, 2020 | 14 | 2020 |
| A roadmap for the generation of benchmarking resources for antimicrobial resistance detection using next generation sequencing M Petrillo, M Fabbri, DM Kagkli, M Querci, G Van den Eede, E Alm, ... F1000Research 10, 2021 | 11 | 2021 |
| Predicting antimicrobial resistance using partial genome alignments D Aytan-Aktug, M Nguyen, PTLC Clausen, RL Stevens, FM Aarestrup, ... Msystems 6 (3), 10.1128/msystems. 00185-21, 2021 | 10 | 2021 |
| PlasmidHostFinder: prediction of plasmid hosts using random forest D Aytan-Aktug, PTLC Clausen, J Szarvas, P Munk, S Otani, M Nguyen, ... Msystems 7 (2), e01180-21, 2022 | 9 | 2022 |
| SourceFinder: A machine-learning-based tool for identification of chromosomal, plasmid, and bacteriophage sequences from assemblies D Aytan-Aktug, V Grigorjev, J Szarvas, PTLC Clausen, P Munk, M Nguyen, ... Microbiology Spectrum 10 (6), e02641-22, 2022 | 4 | 2022 |
| Can machine learning models predict asparaginase-associated pancreatitis in childhood acute lymphoblastic leukemia RL Nielsen, BO Wolthers, M Helenius, BK Albertsen, L Clemmensen, ... Journal of pediatric hematology/oncology 44 (3), e628-e636, 2022 | 4 | 2022 |
| Machine learning of antimicrobial resistance D Aytan-Aktug DTU Food, 2021 | | 2021 |
Philip ClausenTechnical University of DenmarkVerified email at dtu.dk
