An introduction to kernel-based learning algorithms KR Muller, S Mika, G Rätsch, K Tsuda, B Scholkopf IEEE transactions on neural networks 12 (2), 181-201, 2001 | 4982* | 2001 |
Fisher discriminant analysis with kernels S Mika, G Raetsch, B Scholkopf, KR Muller Neural networks for signal processing IX, 1999 | 4205 | 1999 |
The molecular taxonomy of primary prostate cancer A Abeshouse, J Ahn, R Akbani, A Ally, S Amin, CD Andry, M Annala, ... Cell 163 (4), 1011-1025, 2015 | 2645 | 2015 |
Pan-cancer analysis of whole genomes Nature 578 (7793), 82-93, 2020 | 1802* | 2020 |
Determination and inference of eukaryotic transcription factor sequence specificity MT Weirauch, A Yang, M Albu, AG Cote, A Montenegro-Montero, P Drewe, ... Cell 158 (6), 1431-1443, 2014 | 1745 | 2014 |
Large scale multiple kernel learning S Sonnenburg, G Rätsch, C Schäfer, B Schölkopf The Journal of Machine Learning Research 7, 1531-1565, 2006 | 1738 | 2006 |
Soft margins for AdaBoost G Rätsch, T Onoda, KR Müller Machine learning 42, 287-320, 2001 | 1709 | 2001 |
Input space versus feature space in kernel-based methods B Scholkopf, S Mika, CJC Burges, P Knirsch, KR Muller, G Ratsch, ... IEEE transactions on neural networks 10 (5), 1000-1017, 1999 | 1695 | 1999 |
Challenging common assumptions in the unsupervised learning of disentangled representations F Locatello, S Bauer, M Lucic, G Raetsch, S Gelly, B Schölkopf, O Bachem international conference on machine learning, 4114-4124, 2019 | 1503 | 2019 |
Kernel PCA and de-noising in feature spaces S Mika, B Schölkopf, A Smola, KR Müller, M Scholz, G Rätsch Advances in neural information processing systems 11, 1998 | 1454 | 1998 |
Predicting time series with support vector machines KR Müller, AJ Smola, G Rätsch, B Schölkopf, J Kohlmorgen, V Vapnik International conference on artificial neural networks, 999-1004, 1997 | 1426 | 1997 |
Integrative Analysis of the Caenorhabditis elegans Genome by the modENCODE Project MB Gerstein, ZJ Lu, EL Van Nostrand, C Cheng, BI Arshinoff, T Liu, ... Science 330 (6012), 1775-1787, 2010 | 1116 | 2010 |
Real-valued (medical) time series generation with recurrent conditional gans C Esteban, SL Hyland, G Rätsch arXiv preprint arXiv:1706.02633, 2017 | 872 | 2017 |
Common Sequence Polymorphisms Shaping Genetic Diversity in Arabidopsis thaliana RM Clark, G Schweikert, C Toomajian, S Ossowski, G Zeller, P Shinn, ... science 317 (5836), 338-342, 2007 | 860 | 2007 |
Support vector machines and kernels for computational biology A Ben-Hur, CS Ong, S Sonnenburg, B Schölkopf, G Rätsch PLoS computational biology 4 (10), e1000173, 2008 | 816 | 2008 |
Assessment of transcript reconstruction methods for RNA-seq T Steijger, JF Abril, PG Engström, F Kokocinski, TJ Hubbard, R Guigó, ... Nature methods 10 (12), 1177-1184, 2013 | 770 | 2013 |
Multiple reference genomes and transcriptomes for Arabidopsis thaliana X Gan, O Stegle, J Behr, JG Steffen, P Drewe, KL Hildebrand, R Lyngsoe, ... Nature 477 (7365), 419-423, 2011 | 743 | 2011 |
Comprehensive analysis of alternative splicing across tumors from 8,705 patients A Kahles, KV Lehmann, NC Toussaint, M Hüser, SG Stark, ... Cancer cell 34 (2), 211-224. e6, 2018 | 732 | 2018 |
Genomewide SNP variation reveals relationships among landraces and modern varieties of rice KL McNally, KL Childs, R Bohnert, RM Davidson, K Zhao, VJ Ulat, ... | 703 | 2009 |
An introduction to boosting and leveraging R Meir, G Rätsch Advanced Lectures on Machine Learning: Machine Learning Summer School 2002 …, 2003 | 683 | 2003 |