| The SHOGUN machine learning toolbox S Sonnenburg, G Rätsch, S Henschel, C Widmer, J Behr, A Zien, F Bona, ... The Journal of Machine Learning Research 11, 1799-1802, 2010 | 388 | 2010 |
| Stress‐induced changes in the Arabidopsis thaliana transcriptome analyzed using whole‐genome tiling arrays G Zeller, SR Henz, CK Widmer, T Sachsenberg, G Rätsch, D Weigel, ... The Plant Journal 58 (6), 1068-1082, 2009 | 375 | 2009 |
| A spatial and temporal map of C. elegans gene expression WC Spencer, G Zeller, JD Watson, SR Henz, KL Watkins, RD McWhirter, ... Genome research 21 (2), 325-341, 2011 | 348 | 2011 |
| An empirical analysis of domain adaptation algorithms for genomic sequence analysis G Schweikert, G Rätsch, C Widmer, B Schölkopf Advances in neural information processing systems 21, 2008 | 198 | 2008 |
| Prediction of potent shRNAs with a sequential classification algorithm R Pelossof, L Fairchild, CH Huang, C Widmer, VT Sreedharan, N Sinha, ... Nature biotechnology 35 (4), 350-353, 2017 | 180 | 2017 |
| Determinants of robustness in spindle assembly checkpoint signalling S Heinrich, EM Geissen, J Kamenz, S Trautmann, C Widmer, P Drewe, ... Nature cell biology 15 (11), 1328-1339, 2013 | 136 | 2013 |
| At-TAX: a whole genome tiling array resource for developmental expression analysis and transcript identification in Arabidopsis thaliana S Laubinger, G Zeller, SR Henz, T Sachsenberg, CK Widmer, N Naouar, ... Genome biology 9, 1-16, 2008 | 114 | 2008 |
| Further improvements to linear mixed models for genome-wide association studies C Widmer, C Lippert, O Weissbrod, N Fusi, C Kadie, R Davidson, ... Scientific reports 4 (1), 6874, 2014 | 88 | 2014 |
| Linear mixed model for heritability estimation that explicitly addresses environmental variation D Heckerman, D Gurdasani, C Kadie, C Pomilla, T Carstensen, H Martin, ... Proceedings of the National Academy of Sciences 113 (27), 7377-7382, 2016 | 86 | 2016 |
| Inferring latent task structure for multitask learning by multiple kernel learning C Widmer, NC Toussaint, Y Altun, G Rätsch BMC bioinformatics 11, 1-8, 2010 | 69 | 2010 |
| Multitask Learning in Computational Biology C Widmer, G Rätsch JMLR W&CP. ICML 2011 Unsupervised and Transfer Learning Workshop. 27, 207-216, 2012 | 68 | 2012 |
| Leveraging sequence classification by taxonomy-based multitask learning C Widmer, J Leiva, Y Altun, G Rätsch Research in Computational Molecular Biology: 14th Annual International …, 2010 | 67 | 2010 |
| Greater power and computational efficiency for kernel-based association testing of sets of genetic variants C Lippert, J Xiang, D Horta, C Widmer, C Kadie, D Heckerman, ... Bioinformatics 30 (22), 3206-3214, 2014 | 54 | 2014 |
| Hierarchical Multitask Structured Output Learning for Large-Scale Sequence Segmentation N Görnitz, C Widmer, G Zeller, A Kahles, S Sonnenburg, G Rätsch | 40 | 2011 |
| Exploiting physico-chemical properties in string kernels NC Toussaint, C Widmer, O Kohlbacher, G Rätsch BMC bioinformatics 11, 1-9, 2010 | 38 | 2010 |
| Efficient Training of Graph-Regularized Multitask SVMs C Widmer, M Kloft, N Görnitz, G Rätsch ECML 2012, 2012 | 23 | 2012 |
| Tapkee: An efficient dimension reduction library S Lisitsyn, C Widmer, FJI Garcia The Journal of Machine Learning Research 14 (1), 2355-2359, 2013 | 21 | 2013 |
| Novel machine learning methods for MHC class I binding prediction C Widmer, NC Toussaint, Y Altun, O Kohlbacher, G Rätsch Pattern Recognition in Bioinformatics: 5th IAPR International Conference …, 2010 | 15 | 2010 |
| Regularization-based multitask learning with applications to genome biology and biological imaging C Widmer, M Kloft, X Lou, G Rätsch KI-Künstliche Intelligenz 28, 29-33, 2014 | 10 | 2014 |
| Domain adaptation in sequence analysis C Widmer Diplom thesis at University Tübingen, Germany, 2008 | 6 | 2008 |
Gunnar RätschProfessor, ETH ZürichE-mail megerősítve itt: inf.ethz.ch