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 & MPIIVerified email at tu-berlin.de
Soeren SonnenburgMachine Learning ResearcherVerified email at tomtom.com
Sebastian MikacomtravoVerified email at comtravo.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
Christian WidmerGoogleVerified email at google.com
Philipp Drewe-BossMax Delbrück Center for Molecular MedicineVerified email at mdc-berlin.de
Jonas BehrComputational Biology Group, ETH ZurichVerified email at sophiagenetics.com
Detlef WeigelMax Planck Institute for Developmental BiologyVerified email at weigelworld.org
Gabriele SchweikertPI, University of Dundee, UK and Universität Tübingen, GermanyVerified email at dundee.ac.uk
Vipin T. SreedharanPhD student at Memorial Sloan Kettering Cancer Center/ University of TübingenVerified email at cbio.mskcc.org
Cheng Soon OngData61, CSIRO, CanberraVerified email at anu.edu.au
Francesco LocatelloSenior Applied Scientist, Amazon AWSVerified email at amazon.com
Oliver StegleGerman Cancer Research Center (DKFZ) & EMBL HeidelbergVerified email at dkfz.de
Jason WestonFacebookVerified email at fb.com
Yi ZhongMemorial Sloan Kettering Cancer CenterVerified email at cbio.mskcc.org
Géraldine JeanAssociate Professor, Université of Nantes, LS2NVerified email at univ-nantes.fr

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	4520*	2001
The cancer genome atlas pan-cancer analysis project JN Weinstein, EA Collisson, GB Mills, KRM Shaw, BA Ozenberger, ... Nature genetics 45 (10), 1113-1120, 2013	4083	2013
Fisher discriminant analysis with kernels S Mika, G Raetsch, B Scholkopf, KR Muller Neural networks for signal processing IX, 1999	3494	1999
Large scale multiple kernel learning S Sonnenburg, G Rätsch, C Schäfer, B Schölkopf The Journal of Machine Learning Research 7, 1531-1565, 2006	1663	2006
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	1571	1999
Soft margins for AdaBoost G Rätsch, T Onoda, KR Müller Machine learning 42 (3), 287-320, 2001	1522	2001
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	1521	2015
Kernel PCA and De-noising in feature spaces. S Mika, B Schölkopf, AJ Smola, KR Müller, M Scholz, G Rätsch NIPS 11, 536-542, 1998	1236	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	1228	1997
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	1005	2014
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	965	2010
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	809	2007
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	640	2011
Support vector machines and kernels for computational biology A Ben-Hur, CS Ong, S Sonnenburg, B Schölkopf, G Rätsch PLoS Comput Biol 4 (10), e1000173, 2008	636	2008
Support vector machines and kernels for computational biology A Ben-Hur, CS Ong, S Sonnenburg, B Schölkopf, G Rätsch PLoS Comput Biol 4 (10), e1000173, 2008	636	2008
An introduction to boosting and leveraging R Meir, G Rätsch Advanced lectures on machine learning, 118-183, 2003	627	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	621	2000
Genomewide SNP variation reveals relationships among landraces and modern varieties of rice KL McNally, KL Childs, R Bohnert, RM Davidson, K Zhao, VJ Ulat, ...	598	2009
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	553	2013
Systematic evaluation of spliced alignment programs for RNA-seq data PG Engström, T Steijger, B Sipos, GR Grant, A Kahles, G Rätsch, ... Nature methods 10 (12), 1185-1191, 2013	477	2013

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