Gunnar Rätsch

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Bernhard SchölkopfDirector, Max Planck Institute for Intelligent Systems; Professor at ETH Zürich, and DistinguishedVerified email at tuebingen.mpg.de
Klaus-Robert MüllerTU Berlin & Korea University & Google Brain & Max Planck Institute for InformaticsVerified email at tu-berlin.de
Sebastian MikacomtravoVerified email at comtravo.com
Soeren SonnenburgMachine Learning ResearcherVerified email at tomtom.com
Andre KahlesDepartment of Computer Science, ETH Zurich, SwitzerlandVerified email at inf.ethz.ch
Alex SmolaAmazon Web ServicesVerified email at smola.org
Georg ZellerEMBL, HeidelbergVerified email at embl.de
Koji TsudaProfessor, GSFS, The University of TokyoVerified email at k.u-tokyo.ac.jp
Jonas BehrSOPHiA GENETICS, St.-Sulpice, SwitzerlandVerified email at sophiagenetics.com
Christian WidmerGoogleVerified email at google.com
Detlef WeigelMax Planck Institute for Biology TübingenVerified email at weigelworld.org
Philipp Drewe-BossMax Delbrück Center for Molecular MedicineVerified email at mdc-berlin.de
Francesco LocatelloSenior Applied Scientist, Amazon AWSVerified email at amazon.com
Gabriele SchweikertPI, University of Dundee, UK and Universität Tübingen, GermanyVerified email at dundee.ac.uk
Cheng Soon OngData61, CSIRO, CanberraVerified email at anu.edu.au
Vipin T. SreedharanPhD student at Memorial Sloan Kettering Cancer Center/ University of TübingenVerified email at cbio.mskcc.org
Oliver StegleGerman Cancer Research Center (DKFZ) & EMBL HeidelbergVerified email at dkfz.de
Géraldine JeanAssociate Professor, Université of Nantes, LS2NVerified email at univ-nantes.fr
Stephanie L HylandMicrosoft Research CambridgeVerified email at microsoft.com
Jason WestonFacebookVerified email at fb.com

Gunnar Rätsch

Professor, ETH Zürich

Verified email at inf.ethz.ch - Homepage

Machine Learning Computational Biology Genetics Cancer Health Informatics


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
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	4765*	2001
Fisher discriminant analysis with kernels S Mika, G Raetsch, B Scholkopf, KR Muller Neural networks for signal processing IX, 1999	3742	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	2186	2015
Large scale multiple kernel learning S Sonnenburg, G Rätsch, C Schäfer, B Schölkopf The Journal of Machine Learning Research 7, 1531-1565, 2006	1678	2006
Soft margins for AdaBoost G Rätsch, T Onoda, KR Müller Machine learning 42, 287-320, 2001	1660	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	1648	1999
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	1362	2014
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	1340	1998
Predicting time series with support vector machines KR Müller, AJ Smola, G Rätsch, B Schölkopf, J Kohlmorgen, V Vapnik Artificial Neural Networks—ICANN'97: 7th International Conference Lausanne …, 2005	1310	2005
Pan-cancer analysis of whole genomes Nature 578 (7793), 82-93, 2020	1053	2020
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	1030	2010
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	1007	2019
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	823	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	717	2008
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	717	2008
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	704	2011
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	690	2013
Genomewide SNP variation reveals relationships among landraces and modern varieties of rice KL McNally, KL Childs, R Bohnert, RM Davidson, K Zhao, VJ Ulat, ...	669	2009
An introduction to boosting and leveraging R Meir, G Rätsch Advanced Lectures on Machine Learning: Machine Learning Summer School 2002 …, 2003	652	2003
Engineering support vector machine kernels that recognize translation initiation sites A Zien, G Rätsch, S Mika, B Schölkopf, T Lengauer, KR Müller Bioinformatics 16 (9), 799-807, 2000	631	2000

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