Gunnar Rätsch - Google Scholar Citations

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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 MüllerGoogle Brain (on leave of Professor for Machine Learning, TU Berlin & Korea University, Seoul)Verified 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
Detlef WeigelMax Planck Institute for Developmental BiologyVerified email at weigelworld.org
Philipp Drewe-BossMax Delbrück Center for Molecular MedicineVerified email at mdc-berlin.de
Jonas BehrComputational Biology Group, ETH ZurichVerified email at sophiagenetics.com
Manfred K. WarmuthProfessor of Computer Science, University of California at Santa CruzVerified email at ucsc.edu
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
Oliver StegleGerman Cancer Research Center (DKFZ) & EMBL HeidelbergVerified email at dkfz.de
Jason WestonFacebookVerified email at fb.com
Sebastian J. Schultheisscomputomics.comVerified email at computomics.com
Géraldine JeanAssociate Professor, Université of Nantes, LINAVerified email at univ-nantes.fr
Yi ZhongMemorial Sloan Kettering Cancer CenterVerified email at cbio.mskcc.org

Gunnar Rätsch

Professor, ETH Zürich

Verified email at inf.ethz.ch - Homepage

Machine Learning Computational Biology Genetics Cancer Health Informatics


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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	4224	2001
Fisher discriminant analysis with kernels S Mika, G Raetsch, B Scholkopf, KR Muller Neural networks for signal processing IX, 1999	3165	1999
The cancer genome atlas pan-cancer analysis project JN Weinstein, EA Collisson, GB Mills, KRM Shaw, BA Ozenberger, ... Nature genetics 45 (10), 1113, 2013	2478	2013
Large scale multiple kernel learning S Sonnenburg, G Rätsch, C Schäfer, B Schölkopf Journal of Machine Learning Research 7 (Jul), 1531-1565, 2006	1545	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	1478	1999
Soft margins for AdaBoost G Rätsch, T Onoda, KR Müller Machine learning 42 (3), 287-320, 2001	1384	2001
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	1120	1997
Kernel PCA and de-noising in feature spaces S Mika, B Schölkopf, AJ Smola, KR Müller, M Scholz, G Rätsch Advances in neural information processing systems, 536-542, 1999	1100	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	1045	2015
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	872	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	764	2007
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	738	2014
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	595	2000
An introduction to boosting and leveraging R Meir, G Rätsch Advanced lectures on machine learning, 118-183, 2003	589	2003
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	570	2011
Support vector machines and kernels for computational biology A Ben-Hur, CS Ong, S Sonnenburg, B Schölkopf, G Rätsch PLoS computational biology 4 (10), 2008	554	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), 2008	554	2008
Genomewide SNP variation reveals relationships among landraces and modern varieties of rice KL McNally, KL Childs, R Bohnert, RM Davidson, K Zhao, VJ Ulat, ...	540	2009
Assessment of transcript reconstruction methods for RNA-seq T Steijger, JF Abril, PG Engström, F Kokocinski, M Akerman, T Alioto, ... Nature methods 10 (12), 1177-1184, 2013	437	2013
Systematic evaluation of spliced alignment programs for RNA-seq data PG Engström, T Steijger, B Sipos, GR Grant, A Kahles, T Alioto, J Behr, ... Nature methods 10 (12), 1185-1191, 2013	412	2013

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