| SIRIUS 4: a rapid tool for turning tandem mass spectra into metabolite structure information K Dührkop, M Fleischauer, M Ludwig, AA Aksenov, AV Melnik, M Meusel, ... Nature methods 16 (4), 299-302, 2019 | 1221 | 2019 |
| Searching molecular structure databases with tandem mass spectra using CSI: FingerID K Dührkop, H Shen, M Meusel, J Rousu, S Böcker Proceedings of the National Academy of Sciences 112 (41), 12580-12585, 2015 | 962 | 2015 |
| Systematic classification of unknown metabolites using high-resolution fragmentation mass spectra K Dührkop, LF Nothias, M Fleischauer, R Reher, M Ludwig, MA Hoffmann, ... Nature biotechnology 39 (4), 462-471, 2021 | 507 | 2021 |
| Kernel-based learning of hierarchical multilabel classification models J Rousu, C Saunders, S Szedmak, J Shawe-Taylor Journal of Machine Learning Research 7, 1601-1626, 2006 | 374 | 2006 |
| General and efficient multisplitting of numerical attributes T Elomaa, J Rousu Machine learning 36, 201-244, 1999 | 233 | 1999 |
| Metabolite identification and molecular fingerprint prediction through machine learning M Heinonen, H Shen, N Zamboni, J Rousu Bioinformatics 28 (18), 2333-2341, 2012 | 213 | 2012 |
| Critical assessment of small molecule identification 2016: automated methods EL Schymanski, C Ruttkies, M Krauss, C Brouard, T Kind, K Dührkop, ... Journal of cheminformatics 9, 1-21, 2017 | 198 | 2017 |
| Meat processing plant microbiome and contamination patterns of cold-tolerant bacteria causing food safety and spoilage risks in the manufacture of vacuum-packaged cooked sausages J Hultman, R Rahkila, J Ali, J Rousu, KJ Björkroth Applied and environmental microbiology 81 (20), 7088-7097, 2015 | 167 | 2015 |
| FiD: a software for ab initio structural identification of product ions from tandem mass spectrometric data M Heinonen, A Rantanen, T Mielikäinen, J Kokkonen, J Kiuru, RA Ketola, ... Rapid Communications in Mass Spectrometry: An International Journal Devoted …, 2008 | 165 | 2008 |
| Non-stationary gaussian process regression with hamiltonian monte carlo M Heinonen, H Mannerström, J Rousu, S Kaski, H Lähdesmäki Artificial Intelligence and Statistics, 732-740, 2016 | 143 | 2016 |
| A tutorial on canonical correlation methods V Uurtio, JM Monteiro, J Kandola, J Shawe-Taylor, D Fernandez-Reyes, ... ACM Computing Surveys (CSUR) 50 (6), 1-33, 2017 | 142 | 2017 |
| metaCCA: summary statistics-based multivariate meta-analysis of genome-wide association studies using canonical correlation analysis A Cichonska, J Rousu, P Marttinen, AJ Kangas, P Soininen, T Lehtimäki, ... Bioinformatics 32 (13), 1981-1989, 2016 | 141 | 2016 |
| Metabolite identification through multiple kernel learning on fragmentation trees H Shen, K Dührkop, S Böcker, J Rousu Bioinformatics 30 (12), i157-i164, 2014 | 127 | 2014 |
| Learning hierarchical multi-category text classification models J Rousu, C Saunders, S Szedmak, J Shawe-Taylor Proceedings of the 22nd international conference on Machine learning, 744-751, 2005 | 124 | 2005 |
| Computational-experimental approach to drug-target interaction mapping: a case study on kinase inhibitors A Cichonska, B Ravikumar, E Parri, S Timonen, T Pahikkala, A Airola, ... PLoS computational biology 13 (8), e1005678, 2017 | 118 | 2017 |
| Comparative genome-scale reconstruction of gapless metabolic networks for present and ancestral species E Pitkänen, P Jouhten, J Hou, MF Syed, P Blomberg, J Kludas, M Oja, ... PLoS computational biology 10 (2), e1003465, 2014 | 110 | 2014 |
| Fast metabolite identification with input output kernel regression C Brouard, H Shen, K Dührkop, F d'Alché-Buc, S Böcker, J Rousu Bioinformatics 32 (12), i28-i36, 2016 | 108 | 2016 |
| Leveraging multi-way interactions for systematic prediction of pre-clinical drug combination effects H Julkunen, A Cichonska, P Gautam, S Szedmak, J Douat, T Pahikkala, ... Nature communications 11 (1), 6136, 2020 | 93 | 2020 |
| Inferring branching pathways in genome-scale metabolic networks E Pitkänen, P Jouhten, J Rousu BMC systems biology 3, 1-22, 2009 | 91 | 2009 |
| Learning with multiple pairwise kernels for drug bioactivity prediction A Cichonska, T Pahikkala, S Szedmak, H Julkunen, A Airola, M Heinonen, ... Bioinformatics 34 (13), i509-i518, 2018 | 78 | 2018 |
Sebastian BöckerProfessor für Bioinformatik, FSU JenaVerified email at uni-jena.de
