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Author

Sören Sonnenburg

Observed names: Sonnenburg, S, Sonnenburg, Sören, SonnenburgSören, Soren Sonnenburg
Institution: TomTom (Germany)
Observed institutions: Max Planck Society, University of Potsdam, Max Planck Institute for Biological Cybernetics, TomTom (Germany), Friedrich Miescher Laboratory, Technische Universität Berlin, Fraunhofer-Gesellschaft
OpenAlex ID: A5110197966
Large Scale Multiple Kernel Learning
2006 · Sören Sonnenburg, Gunnar Rätsch, et al. · MPG.PuRe (Max Planck Society) · 1,201
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Support Vector Machines and Kernels for Computational Biology
2008 · Asa Ben-Hur, Cheng Soon Ong, et al. · PLoS Computational Biology · 723
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The SHOGUN Machine Learning Toolbox
2010 · Sonnenburg, Sören, Rätsch, Gunnar, et al. · Max Planck Institute for Plasma Physics · 247
The Feature Importance Ranking Measure
2009 · Alexander Zien, Nicole Krämer, et al. · Lecture notes in computer science · 199
Accurate splice site prediction using support vector machines
2007 · Sören Sonnenburg, Gabriele Schweikert, et al. · BMC Bioinformatics · 182
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The Need for Open Source Software in Machine Learning
2007 · Sonnenburg, S, Braun, ML, et al. · Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft) · 178
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A general and efficient multiple kernel learning algorithm
2005 · Sonnenburg, Sören, Rätsch, Gunnar, et al. · Max Planck Institute for Plasma Physics · 149
ARTS: accurate recognition of transcription starts in human
2006 · Sören Sonnenburg, Alexander Zien, et al. · Bioinformatics · 131
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A New Discriminative Kernel from Probabilistic Models
2002 · Koji Tsuda, Motoaki Kawanabe, et al. · Neural Computation · 127
Learning Interpretable SVMs for Biological Sequence Classification
2006 · Gunnar Rätsch, Sören Sonnenburg, et al. · BMC Bioinformatics · 109
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mGene: Accurate SVM-based gene finding with an application to nematode genomes
2009 · Gabriele Schweikert, Alexander Zien, et al. · Genome Research · 101
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Classifying ‘Drug-likeness' with Kernel-Based Learning Methods
2005 · Klaus-Robert Müller, Gunnar Rätsch, et al. · Journal of Chemical Information and Modeling · 86
Combining Multiple Hypothesis Testing with Machine Learning Increases the Statistical Power of Genome-wide Association Studies
2016 · Bettina Mieth, Marius Kloft, et al. · Scientific Reports · 84
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Improving the Caenorhabditis elegans Genome Annotation Using Machine Learning
2007 · Gunnar Rätsch, Sören Sonnenburg, et al. · PLoS Computational Biology · 76
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Optimized Cutting Plane Algorithm for Large-Scale Risk Minimization
2009 · FrancVojtěch, SonnenburgSören · 71
New Methods for Splice Site Recognition
2002 · Sören Sonnenburg, Gunnar Rätsch, et al. · Lecture notes in computer science · 67
POIMs: positional oligomer importance matrices—understanding support vector machine-based signal detectors
2008 · Sören Sonnenburg, Alexander Zien, et al. · Bioinformatics · 62
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Accurate Splice Site Detection for Caenorhabditis elegans
2004 · Gunnar Rätsch, Sören Sonnenburg · The MIT Press eBooks · 60
Large-Scale Learning with String Kernels
2007 · Sören Sonnenburg, Gunnar Rätsch, et al. · The MIT Press eBooks · 48
Large scale genomic sequence SVM classifiers
2005 · Sören Sonnenburg, Gunnar Rätsch, et al. · International Conference on Machine Learning · 48
Support Vector Machines
2011 · Konrad Rieck, Sören Sonnenburg, et al. · Springer eBooks · 33
Non-Sparse Regularization and Efficient Training with Multiple Kernels
2010 · Marius Kloft, Ulf Brefeld, et al. · 33
Large Scale Hidden Semi-Markov SVMs
2007 · Gunnar Rätsch, Sören Sonnenburg · The MIT Press eBooks · 21
Computation of Similarity Measures for Sequential Data using Generalized Suffix Trees
2007 · Konrad Rieck, Pavel Laskov, et al. · The MIT Press eBooks · 16
A Scatter-Based Prototype Framework and Multi-Class Extension of Support Vector Machines
2012 · Robert Jenssen, Marius Kloft, et al. · PLoS ONE · 9
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Works count: 48
Citation count: 4,079
H-index: 22
I10-index: 24
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