Publications
Peer-reviewed publications from the MLCB lab.
Structure-Aware Transformer for Graph Representation Learning
Dexiong Chen*, Leslie O'Bray*, and Karsten Borgwardt
Proceedings of the 39th International Conference on Machine Learning (ICML 2022), 3469-3489
external pageOnline | external pageICML Presentation
Prediction of recovery from multiple organ dysfunction syndrome in pediatric sepsis patients
Bowen Fan, Juliane Klatt, Michael M. Moor, Latasha A. Daniels, Swiss Pediatric Sepsis Study, Lazaro N. Sanchez-Pinto, Philipp K. A. Agyeman, Luregn J. Schlapbach, and Karsten M. Borgwardt
International Conference on Intelligent Systems for Molecular Biology (ISMB 2022) and Bioinformatics 2022, 38 (Supplement_1): i101–i108
external pageOnline
Direct Antimicrobial Resistance Prediction from MALDI-TOF mass spectra profile in clinical isolates through Machine Learning
Caroline Weis, Aline Cuénod, Bastian Rieck, Olivier Dubuis, Susanne Graf, Claudia Lang, Michael Oberle, Kirstine K. Soegaard, Michael Osthoff, Karsten Borgwardt*, and Adrian Egli* (* = equal contribution)
Nature Medicine 2022, 28: 164–174
external pageOnline | external pagearXiv | ETH News
Determinants of SARS-CoV-2 transmission to guide vaccination strategy in a city
Sarah C. Brüningk*, Juliane Klatt*, Madlen Stange*, Alfredo Mari, Myrta Brunner, Tim-Christoph Roloff, Helena M. B. Seth-Smith, Michael Schweitzer, Karoline Leuzinger, Kirstine K. Søgaard, Diana Albertos Torres, Alexander Gensch, Ann-Kathrin Schlotterbeck, Christian H. Nickel, Nicole Ritz, Ulrich Heininger, Julia Bielicki, Katharina Rentsch, Simon Fuchs, Roland Bingisser, Martin Siegemund, Hans Pargger, Diana Ciardo, Olivier Dubuis, Andreas Buser, Sarah Tschudin-Sutter, Manuel Battegay, Rita Schneider-Sliwa, Karsten M. Borgwardt°, Hans H. Hirsch°, and Adrian Egli° (* = equal contribution, ° = joint supervision)
Virus Evolution 2022, 8 (1): veac002
external pageOnline
Evaluation Metrics for Graph Generative Models: Problems, Pitfalls, and Practical Solutions
Leslie O'Bray*, Max Horn*, Bastian Rieck*, and Karsten Borgwardt (* = equal contribution)
Tenth International Conference on Learning Representations (ICLR 2022)
external pageOpenReview | external pagearXiv
Topological Graph Neural Networks
Max Horn*, Edward De Brouwer*, Michael Moor, Yves Moreau, Bastian Rieck°, and Karsten Borgwardt° (* = equal contribution)
Tenth International Conference on Learning Representations (ICLR 2022)
external pageOpenReview | external pagearXiv
RNA atlas of human bacterial pathogens uncovers stress dynamics linked to infection
Kemal Avican, Jehad Aldahdooh, Matteo Togninalli, A. K. M. Firoj Mahmud, Jing Tang, Karsten M. Borgwardt, Mikael Rhen, and Maria Fällman
Nature Communications 2021, 12: 3282
external pageOnline
Filtration Curves for Graph Representation
Leslie O’Bray*, Bastian Rieck* and Karsten Borgwardt (* = equal contribution)
In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining (KDD '21). Association for Computing Machinery, New York, NY, USA, 1267–1275.
external pageOnline
Early Prediction of Sepsis in the ICU using Machine Learning: A Systematic Review
Michael Moor*, Bastian Rieck*, Max Horn, Catherine Jutzeler°, and Karsten Borgwardt° (* = equal contribution, ° = joint supervision)
Frontiers in Medicine 2021, 8:607952
external pageOnline | external pagemedRxiv
Biological network analysis with deep learning
Giulia Muzio*, Leslie O’Bray* and Karsten Borgwardt (* = equal contribution)
Briefings in Bioinformatics 2021, 22(2): 1515–1530
external pageOnline
Network-guided search for genetic heterogeneity between gene pairs
Anja C. Gumpinger, Bastian Rieck, Dominik G. Grimm, International Headache Genetics Consortium, and Karsten M. Borgwardt
Bioinformatics 2021, 37(1): 57–65
external pageOnline | external pageGitHub
Using routine MRI data of depressed patients to predict individual responses to electroconvulsive therapy
Matti Gärtner, Elisabetta Ghisu, Ana L. Herrera-Melendez, Michael Koslowski, Sabine Aust, Patrick Asbach, Christian Otte, Francesca Regen, Isabella Heuser, Karsten Borgwardt, Malek Bajbouj and Simone Grimm
Experimental Neurology 2021, 335: 113505.
external pageOnline | external pageFree version
Ethnicity-based bias in clinical severity scores
Thomas Gumbsch and Karsten Borgwardt
The Lancet Digital Health 2021, 3(4): E209-E210
external pageOnline
Enhancing statistical power in temporal biomarker discovery through representative shapelet mining
Thomas Gumbsch, Christian Bock, Michael Moor, Bastian Rieck, and Karsten Borgwardt
ECCB and Bioinformatics 2020, 36(Supplement_2): i840–i848
external pageOnline
Graph Kernels: State-of-the-Art and Future Challenges
Karsten Borgwardt, Elisabetta Ghisu, Felipe Llinares-López, Leslie O'Bray, and Bastian Rieck
Foundations and Trends® in Machine Learning 2020, 13 (5-6): 531-712.
external pageOnline | Project page | external pagearXiv
Uncovering the Topology of Time-Varying fMRI Data using Cubical Persistence
Bastian Rieck, Tristan Yates, Christian Bock, Karsten Borgwardt, Guy Wolf, Nicholas Turk-Browne, and Smita Krishnaswamy
Spotlight presentation at NeurIPS 2020 and Advances in Neural Information Processing Systems 33, 6900-6912
external pageOnline | external pagearXiv | external pageGitHub | external pageVideo
Comorbidities, clinical signs and symptoms, laboratory findings, imaging features, treatment strategies, and outcomes in adult and pediatric patients with COVID-19: A systematic review and meta-analysis
Catherine R. Jutzeler*, Lucie Bourguignon*, Caroline V. Weis, Bobo Tong, Cyrus Wong, Bastian Rieck, Hans Pargger, Sarah Tschudin-Sutter, Adrian Egli, Karsten Borgwardt° and Matthias Walter° (* = equal contribution, ° = joint supervision)
Travel Medicine and Infectious Disease 2020, 37: 101825
external pageOnline
Large-scale DNA-based phenotypic recording and deep learning enable highly accurate sequence-function mapping
Simon Höllerer*, Laetitia Papaxanthos*, Anja Cathrin Gumpinger, Katrin Fischer, Christian Beisel, Karsten Borgwardt°, Yaakov Benenson° & Markus Jeschek° (* = equal contribution, ° = joint supervision)
Nature Communications 2020, 11: 3551
external pageOnline | external pageCode (GitHub) | external pageData (GitHub)
SPHN/PHRT: Forming a Swiss-Wide Infrastructure for Data-Driven Sepsis Research
Adrian Egli, Manuel Battegay, Andrea C Büchler, Peter Bühlmann, Thierry Calandra, Philippe Eckert, Hansjakob Furrer, Gilbert Greub, Stephan M Jakob, Laurent Kaiser, Stephen L Leib, Stephan Marsch, Nicolai Meinshausen, Jean-Luc Pagani, Jerome Pugin, Gunnar Rätsch, Jacques Schrenzel, Reto Schüpbach, Martin Siegemund, Nicola Zamboni, Reinhard Zbinden, Annelies Zinkernagel, and Karsten Borgwardt
Studies in Health Technology and Informatics 2020, 270: 1163–1167
external pageOnline
Machine Learning for Biomedical Time Series Classification: From Shapelets to Deep Learning
Christian Bock*, Michael Moor*, Catherine Jutzeler, Karsten Borgwardt (*=equal contribution)
In "Artificial Neural Networks", volume 2190 of Methods in Molecular Biology, 33-71
external pageOnline
Set Functions for Time Series
Max Horn, Michael Moor, Christian Bock, Bastian Rieck and Karsten Borgwardt
Proceedings of the 37th International Conference on Machine Learning, PMLR 119:4353-4363, 2020.
external pageOnline | external pagearXiv
Topological Autoencoders
Michael Moor*, Max Horn*, Bastian Rieck° and Karsten Borgwardt° (*= equal contribution, °= equal contribution)
Proceedings of the 37th International Conference on Machine Learning, PMLR 119:7045-7054, 2020.
external pageOnline | external pagearXiv
Machine learning for microbial identification and antimicrobial susceptibility testing on MALDI-TOF mass spectra: a systematic review
Caroline Weis*, Catherine Jutzeler* and Karsten Borgwardt (* = equal contribution)
Clinical Microbiology and Infection 2020, 26 (10): 1310-1317
external pageOnline
Prediction of cancer driver genes through network-based moment propagation of mutation scores
Anja Gumpinger, Kasper Lage, Heiko Horn and Karsten Borgwardt
ISMB 2020 and Bioinformatics 2020, 36 (Supplement_1): i508–i515
external pageOnline
Topological and kernel-based microbial phenotype prediction from MALDI-TOF mass spectra
Caroline Weis, Max Horn, Bastian Rieck, Aline Cuenod, Adrian Egli and Karsten Borgwardt
ISMB 2020 and Bioinformatics 2020, 36 (Supplement_1): i30–i38
external pageOnline
Early prediction of circulatory failure in the intensive care unit using machine learning
Stephanie L. Hyland*, Martin Faltys*, Matthias Hüser*, Xinrui Lyu*, Thomas Gumbsch*, Cristóbal Esteban, Christian Bock, Max Horn, Michael Moor, Bastian Rieck, Marc Zimmermann, Dean Bodenham, Karsten Borgwardt°, Gunnar Rätsch°, and Tobias M. Merz° (* = equal contribution, ° = joint supervision)
Nature Medicine 2020, 26:364–373
external pageOnline | external pageFree, read-only version | ETH news | ETH Research Collection
AraPheno and the AraGWAS Catalog 2020: A major database update including RNA-Seq and knockout mutation data for Arabidopsis thaliana
Matteo Togninalli*, Ümit Seren*, Jan Freudenthal, J Grey Monroe, Meng Dazhe, Magnus Nordborg, Detlef Weigel, Karsten Borgwardt, Arthur Korte, Dominik Grimm (*=equal contributions)
Nucleic Acids Research 2020, 48 (D1): D1063–D1068
external pageOnline | ETH Research Collection | external pageAraPheno | external pageAraGWAS
Kernel Conditional Clustering and Kernel Conditional Semi-supervised Learning
Xiao He, Thomas Gumbsch, Damian Roqueiro and Karsten Borgwardt
Knowledge and Information Systems 2020, 62: 899–925.
external pageOnline | ETH Research Collection
Pre-transplant kinetics of anti-HLA antibodies in patients on the waiting list for kidney transplantation
Matteo Togninalli, Daisuke Yoneoka, Antonios GA Kolios, Karsten Borgwardt and Jakob Nilsson
Journal of the American Society of Nephrology 2019, 30 (11) 2262-2274
external pageOnline | external pageGitHub | ETH Research Collection
Wasserstein Weisfeiler-Lehman Graph Kernels
Matteo Togninalli*, Elisabetta Ghisu*, Felipe Llinares-Lopez, Bastian Rieck, and Karsten Borgwardt (*=equal contributions)
Advances in Neural Information Processing Systems 32 (NeurIPS 2019). Spotlight talk.
external pageOnline | external pageGitHub | ETH Research Collection
A Wasserstein Subsequence Kernel for Time Series
Christian Bock*, Matteo Togninalli*, Elisabetta Ghisu, Thomas Gumbsch, Bastian Rieck, and Karsten Borgwardt (*=equal contributions)
Proceedings of the 2019 IEEE International Conference on Data Mining (ICDM 2019), pp. 964-969.
external pageOnline | external pageGitHub | ETH Research Collection
Early Recognition of Sepsis with Gaussian Process Temporal Convolutional Networks and Dynamic Time Warping
Michael Moor, Max Horn, Bastian Rieck, Damian Roqueiro and Karsten Borgwardt
Machine Learning for Healthcare Conference (MLHC) 2019 and Proceedings of Machine Learning Research 106:2–26, 2019
external pageOnline | external pageGitHub | ETH Research Collection
Finding Statistically Significant Interactions between Continuous Features
Mahito Sugiyama and Karsten Borgwardt
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence (IJCAI-19), 3490-3498.
external pageOnline | external pageGitHub | ETH Research Collection
A Persistent Weisfeiler–Lehman Procedure for Graph Classification
Bastian Rieck, Christian Bock and Karsten Borgwardt
Proceedings of the 36th International Conference on Machine Learning (ICML 2019), PMLR 97: 5448-5458.
external pageOnline | external pageGitHub | ETH Research Collection
Machine Learning for Biomarker Discovery: Significant Pattern Mining
Felipe Llinares-López and Karsten Borgwardt
In N. Pržulj (Ed.), Analyzing Network Data in Biology and Medicine: An Interdisciplinary Textbook for Biological, Medical and Computational Scientists, pp. 313-368. Cambridge University Press, 2019
external pageOnline | ETH Research Collection
Neural Persistence: A Complexity Measure for Deep Neural Networks Using Algebraic Topology
Bastian Rieck, Matteo Togninalli, Christian Bock, Michael Moor, Max Horn, Thomas Gumbsch and Karsten Borgwardt
International Conference on Learning Representations (ICLR) 2019.
external pageOpenReview | external pageGitHub | external pageETH Research Collection
CASMAP: Detection of statistically significant combinations of SNPs in association mapping
Felipe Llinares-Lopez*, Laetitia Papaxanthos*, Damian Roquiero, Dean Bodenham° and Karsten Borgwardt° (* = equal contribution, ° = joint supervision)
Bioinformatics 2019, 35 (15): 2680–2682
external pageOnline | external pageGithub | ETH Research Collection
Methods and Tools in Genome-wide Association Studies
Anja C. Gumpinger, Damian Roqueiro, Dominik G. Grimm and Karsten M. Borgwardt
In Computational Cell Biology, Editors Louise von Stechow L. and Alberto Santos Delgado, volume 1819 of Methods in Molecular Biology, pages 93-136. Humana Press, New York, NY, 2018.
external pageOnline | Project page | ETH Research Collection
Association Mapping in Biomedical Time Series via Statistically Significant Shapelet Mining
Christian Bock, Thomas Gumbsch, Michael Moor, Bastian Rieck, Damian Roquiero and Karsten Borgwardt
ISMB 2018 and Bioinformatics 2018, 43 (13): i438–i446
external pageOnline | external pageETH Research Collection
Accurate and Adaptive Imputation of Summary Statistics in Mixed-Ethnicity Cohorts
Matteo Togninalli, Damian Roqueiro, COPDGene Investigators and Karsten M. Borgwardt
ECCB 2018 and Bioinformatics 2018, 35 (17): i687-i696
external pageOnline | external pageETH Research Collection
Aberrant working memory processing in major depression: evidence from multivoxel pattern classification
Matti Gärtner*, Elisabetta M. Ghisu*, Milan Scheidegger, Luisa Bönke, Yan Fan, Anna Stippl, Ana-Lucia Herrera-Melendez, Sophie Metz, Emilia Winnebeck, Maria Fissler, Anke Henning, Malek Bajbouj, Karsten Borgwardt, Thorsten Barnhofer and Simone Grimm (*=equal contributions)
Neuropsychopharmacology 2018, 43: 1972-1979
external pageOnline | ETH Research Collection
Multi-target drug repositioning by bipartite block-wise sparse multi-task learning
Limin Li, Xiao He and Karsten Borgwardt
BMC Systems Biology 2018, 12 (Suppl 4): 55
external pageOnline | external pageETH Research Collection
Kernelized rank learning for personalized drug recommendation
Xiao He, Lukas Folkman and Karsten Borgwardt
Bioinformatics 2018, 34 (16): 2808-2816
external pageOnline | external pageETH Research Collection
The AraGWAS Catalog: A curated and standardized Arabidopsis thaliana GWAS catalog
Matteo Togninalli*, Ümit Seren*, Dazhe Meng, Joffrey Fitz, Magnus Nordborg, Detlef Weigel, Karsten Borgwardt, Arthur Korte, Dominik Grimm (*=equal contributions)
Nucleic Acids Research 2018, 46 (D1): D1150-D1156
external pageOnline | external pageETH Research Collection
graphkernels: R and Python packages for graph comparison
Mahito Sugiyama, Elisabetta Ghisu, Felipe Llinares-Lopez, Karsten Borgwardt
Bioinformatics 2018, 34 (3): 530-532
external pageOnline | ETH Reserach Collection | Project page
Kernel Conditional Clustering
Xiao He, Thomas Gumbsch, Damian Roqueiro and Karsten Borgwardt
IEEE International Conference on Data Mining (ICDM) 2017, 157-166
external pageOnline | ETH Research Collection | Project page | external pageGitHub
Multi-view Spectral Clustering on Conflicting Views
Xiao He, Limin Li, Damian Roqueiro and Karsten Borgwardt
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD) 2017, 826-842
external pageOnline | ETH Research Collection | Project page | external pageGitHub
Genome-wide genetic heterogeneity discovery with categorical covariates
Felipe Llinares-Lopez*, Laetitia Papaxanthos*, Dean Bodenham, Damian Roqueiro, COPDGene Investigators and Karsten Borgwardt (*=equal contributions)
Bioinformatics 2017, 33 (12): 1820-1828
external pageOnline | ETH Research Collection | Project page | external pageGitHub
AraPheno: a public database for Arabidopsis thaliana phenotypes
Ümit Seren*, Dominik G. Grimm*, Joffrey Fitz, Detlef Weigel, Magnus Nordborg, Karsten Borgwardt and Arthur Korte (*=equal contributions)
Nucleic Acids Research 2017, 45(D1): D1054-D1059
external pageOnline | ETH Research Collection
easyGWAS: A Cloud-based Platform for Comparing the Results of Genome-wide Association Studies
Dominik G. Grimm, Damian Roqueiro, Patrice Salome, Stefan Kleeberger, Bastian Greshake, Wangsheng Zhu, Chang Liu, Christoph Lippert, Oliver Stegle, Bernhard Schölkopf, Detlef Weigel and Karsten Borgwardt
The Plant Cell 2017. 29(1): 5-19
external pageOnline | ETH Research Collection | Project page | easygwas.org
The Genetic Architecture of Non-additive Inheritance in Arabidopsis thaliana Hybrids
Danelle Seymour*, Eunyoung Chae*, Dominik G. Grimm*, Carmen Martín, Anette Haring-Müller, François Vasseur, Barbara Rakitsch, Karsten M. Borgwardt, Daniel Koenig and Detlef Weigel (*=equal contributions)
Proceedings of the National Academy of Sciences (PNAS), 2016. 113(46): E7317-E7326
external pageOnline | ETH Research Collection
Finding significant combinations of features in the presence of categorical covariates
Laetitia Papaxanthos*, Felipe Llinares-López*, Dean Bodenham and Karsten Borgwardt (*=equal contributions)
Advances in Neural Information Processing Systems 29 (NIPS 2016), 2271-2279.
external pageOnline | ETH Research Collection | Project page | external pageGitHub
1,135 genomes reveal the global pattern of polymorphism in Arabidopsis thaliana
The 1001 Genomes Consortium*
Cell 2016, 166(2): 481-491
external pageOnline | ETH Research Collection
* Dominik G. Grimm and Karsten Borgwardt, as part of The 1001 Genomes Consortium
Genomic profiles of diversification and genotype-phenotype association in island nematode lineages,
Angela McGaughran, Christian Rödelsperger, Dominik G. Grimm, Jan Meyer, Katy Morgan, Mark Leaver, Vahan Serobyan, Barbara Rakitsch, Karsten Borgwardt and Ralf Sommer
Molecular Biology and Evolution 2016, 33(9): 2257-2272
external pageOnline | ETH Research Collection
Prediction of human population responses to toxic compounds by a collaborative competition,
Federica Eduati, Lara M. Mangravite, Tao Wang, Hao Tang, J. Christopher Bare, Ruili Huang, Thea Norman, Mike Kellen, Michael P. Menden, Jichen Yang, Xiaowei Zhan, Rui Zhong, Guanghua Xiao, Menghang Xia, Nour Abdo, Oksana Kosyk, The NIEHS-NCATS-UNC DREAM Toxicogenetics Collaboration, Stephen Friend, Allen Dearry, Anton Simeonov, Raymond R. Tice, Ivan Rusyn, Fred A. Wright, Gustavo Stolovitzky and Yang Xie
Nature Biotechnology 2015 Sep, 33(9): 933-40
external pageOnline | external pageETH Research Collection
Halting in Random Walk Kernels
Mahito Sugiyama and Karsten Borgwardt
Advances in Neural Information Processing Systems 28 (NIPS 2015), 1639-1647
external pageOnline | ETH Research Collection | Project page | external pageGitHub
Fast and Memory-Efficient Significant Pattern Mining via Permutation Testing
Felipe Llinares-López, Mahito Sugiyama, Laetitia Papaxanthos and Karsten Borgwardt
Proceedings of the 21st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD2015), 2015, 725-734
external pageOnline | ETH Research Collection | Project page | external pageGitHub
In silico phenotyping via co-training for improved phenotype prediction from genotype
Damian Roqueiro, Menno Witteveen, Verneri Anttila, Gisela Terwindt, Arn van den Maagdenberg and Karsten Borgwardt
ISMB 2015 and Bioinformatics 2015, 31 (12): i303-i310
external pageOnline | ETH Research Collection | Project page with code
Genome-wide detection of intervals of genetic heterogeneity associated with complex traits
Felipe Llinares-López, Dominik G. Grimm, Dean A. Bodenham, Udo Gieraths, Mahito Sugiyama, Beth Rowan and Karsten Borgwardt
ISMB 2015 and Bioinformatics 2015, 31 (12): i240-i249
external pageOnline | ETH Research Collection | Project page | external pageGitHub
The Evaluation of Tools Used to Predict the Impact of Missense Variants is Hindered by Two Types of Circularity
Dominik G. Grimm, Chloé-Agathe Azencott, Fabian Aicheler, Udo Gieraths, Daniel G. MacArthur, Kaitlin E. Samocha, David N. Cooper, Peter D. Stenson, Mark J. Daly, Jordan W. Smoller, Laramie E. Duncan and Karsten Borgwardt
Human Mutation 2015, 36(5): 513-523
external pageOnline | ETH Research Collection | Project page | external pageGitHub
Significant Subgraph Mining with Multiple Testing Correction
Mahito Sugiyama, Felipe Llinares López, Niklas Kasenburg and Karsten Borgwardt
Proceedings of the 2015 SIAM International Conference on Data Mining 2015, 37-45
external pageOnline | ETH Research Collection
Century-scale Methylome Stability in a Recently Diverged Arabidopsis thaliana Lineage
Jörg Hagmann, Claude Becker, Jonas Müller, Oliver Stegle, R.C. Meyer, George Wang, Korbinian Schneeberger, Joffrey Fitz, T. Altmann, Joy Bergelson, Karsten Borgwardt and Detlef Weigel
PLoS Genetics 2015 Jan 8, 11(1): 1-18
external pageOnline | ETH Research Collection
Genome-wide analysis of local chromatin packing in Arabidopsis thaliana
Congmao Wang, Chang Liu, Damian Roqueiro, Dominik G. Grimm, Rebecca Schwab, Claude Becker, Christa Lanz and Detlef Weigel
Genome Research 2015, 25(2): 246-256
external pageOnline
Multi-Task Feature Selection on Multiple Networks via Maximum Flows
Mahito Sugiyama, Chloé-Agathe Azencott, Dominik G. Grimm, Yoshinobu Kawahara and Karsten Borgwardt
Proceedings of the 2014 SIAM International Conference on Data Mining 2014, 199-207
external pageOnline | ETH Research Collection | Project page | external pageGitHub | Supplement
Efficient network-guided multi-locus association mapping with graph cuts
Chloé-Agathe Azencott, Dominik G. Grimm, Mahito Sugiyama, Yoshinobu Kawahara and Karsten Borgwardt
ISMB 2013 and Bioinformatics 2013, 29 (13): i171-i179
external pageOnline | ETH Research Collection | Project page including code
A Lasso Multi-Marker Mixed Model for Association Mapping with Population Structure Correction
Barbara Rakitsch, Christoph Lippert, Oliver Stegle and Karsten Borgwardt
Bioinformatics 2013, 29(2): 206-214
external pageOnline | ETH Research Collection | Project page | external pageGitHub
Accurate indel prediction using paired-end short reads
Dominik G. Grimm, Jörg Hagmann, Daniel Koenig, Detlef Weigel and Karsten Borgwardt
BMC Genomics 2013, 14(1): 132-141
external pageOnline | external pageETH Research Collection | Project page | external pageGitHub
Accurate Detection of Differential RNA Processing
Philipp Drewe, Oliver Stegle, Lisa Hartmann, Andre Kahles, Regina Bohnert, Andreas Wachter, Karsten Borgwardt and Gunnar Rätsch
Nucleic Acids Research 2013, 41(10): 5189-5198
external pageOnline | ETH Research Collection
Geometric tree kernels: Classification of COPD from airway tree geometry
Aasa Feragen, Jens Petersen, Dominik G. Grimm, Asger Dirksen, Jesper Holst Pedersen, Karsten Borgwardt and Marleen de Bruijne
Lecture Notes in Computer Science, Volume 7917: Information Processing in Medical Imaging 2013, 171–183
external pageOnline | ETH Research Collection
Detecting regulatory gene-environment interactions with unmeasured environmental factors
Nicolo Fusi, Christoph Lippert, Karsten Borgwardt, Neil Lawrence and Oliver Stegle
Bioinformatics 2013, 29(11): 1382-9
external pageOnline | ETH Research Collection
Rapid Distance-Based Outlier Detection via Sampling
Mahito Sugiyama and Karsten Borgwardt
Advances in Neural Information Processing Systems 26 (NIPS 2013), 467-475
external pageOnline | ETH Research Collection | Project page including code
Scalable kernels for graphs with continuous attributes
Aasa Feragen, Niklas Kasenburg, Jens Petersen, Marleen de Bruijne and Karsten Borgwardt
Advances in Neural Information Processing Systems 26 (NIPS 2013), 216-224
external pageOnline | ETH Research Collection | Project page | external pageGitHub
It is all in the noise: Efficient multi-task Gaussian process inference with structured residuals
Barbara Rakitsch, Christoph Lippert, Karsten Borgwardt* and Oliver Stegle* (*=equal contributions)
Advances in Neural Information Processing Systems 26 (NIPS 2013), 1466-1474
external pageOnline | ETH Research Collection
Measuring Statistical Dependence via the Mutual Information Dimension
Mahito Sugiyama and Karsten Borgwardt
Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI 2013), 1692-1698
external pageOnline | ETH Research Collection | Project page | external pageGitHub
GLIDE: GPU-based linear regression for detection of epistasis
Tony Kam-Thong, Chloé-Agathe Azencott, Lawrence Cayton, Benno Pütz, Andre Altmann, Philipp G. Sämann, Bernhard Schölkopf, Bertram Müller-Myhsok, Karsten M. Borgwardt
Human Heredity 2012, 73: 220-236
external pageOnline | ETH Research Collection | Project page | external pageGitHub
Arabidopsis Defense against Botrytis cinerea: Chronology and Regulation Deciphered by High-Resolution Temporal Transcriptomic Analysis
Oliver Windram, Priyadharshini Madhou, Stuart McHattie, Claire Hill, Richard Hickman, Emma Cooke, Dafyd J. Jenkins, Christopher A. Penfold, Laura Baxter, Emily Breeze, Steven J. Kiddle, Johanna Rhodes, Susanna Atwell, Daniel J. Kliebenstein, Youn-sung Kima, Oliver Stegle, Karsten Borgwardt, Cunjin Zhang, Alex Tabrett, Roxane Legaie, Jonathan Moore, Bärbel Finkenstadt, David L. Wild, Andrew Mead, David Rand, Jim Beynon, Sascha Ott, Vicky Buchanan-Wollaston and Katherine J. Denby
Plant Cell 2012, 24(9): 3530-57
external pageOnline | ETH Research Collection
Feature Selection via Dependence Maximization
Le Song, Alex Smola, Arthur Gretton, Justin Bedo and Karsten Borgwardt
Journal of Machine Learning Research (JMLR) 2012, 13(1): 1393−1434
external pageOnline | ETH Research Collection
ShapePheno: Unsupervised extraction of shape phenotypes from biological image collections
Theofanis Karaletsos, Oliver Stegle, Christine Dreyer, John Winn and Karsten Borgwardt
Bioinformatics 2012, 28 (7): 1001-1008
external pageOnline | ETH Research Collection
A Kernel Two-Sample Test
Arthur Gretton, Karsten Borgwardt, Malte Rasch, Bernhard Schölkopf and Alexander Smola
Journal of Machine Learning Research (JMLR) 2012, 13:723−773
external pageOnline | ETH Research Collection
Spontaneous epigenetic variation in the Arabidopsis thaliana methylome
Claude Becker, Jörg Hagmann, Jonas Müller, Daniel Koenig, Oliver Stegle, Karsten Borgwardt and Detlef Weigel
Nature 2011, 480: 245–249
external pageOnline | ETH Research Collection
Kernel Methods in Bioinformatics
Karsten M. Borgwardt
In Handbook of Statistical Bioinformatics, Springer Handbooks of Computational Statistics. (Eds.) Henry Horng-Shing Lu, Bernhard Schölkopf and Hongyu Zhao. pp. 317–334. Springer Berlin Heidelberg, 2011.
Whole-genome sequencing of multiple Arabidopsis thaliana populations
Jun Cao, Korbinian Schneeberger, Stephan Ossowski, Torsten Günther, Sebastian Bender, Joffrey Fitz, Daniel Koenig, Christa Lanz, Oliver Ste- gle, Christoph Lippert, Xi Wang, Felix Ott, Jonas Müller, Carlos Alonso-Blanco, Karsten Borgwardt, Karl J Schmid and Detlef Weigel
Nature Genetics 2011, 43(10):956–963
external pageOnline | ETH Research Collection
Weisfeiler-Lehman Graph Kernels
Nino Shervashidze, Pascal Schweitzer, Erik Jan van Leeuwen, Kurt Mehlhorn and Karsten M. Borgwardt
Journal of Machine Learning Research (JMLR) 2011, 12: 2539−2561
external pageOnline | ETH Research Collection | Project page including code
Efficient inference in matrix-variate Gaussian models with iid observation noise
Oliver Stegle, Christoph Lippert, Joris Mooij, Neil Lawrence and Karsten Borgwardt
Advances in Neural Information Processing Systems 24 (NIPS 2011), 630-638
external pageOnline | ETH Research Collection
ccSVM: Correcting Support Vector Machines for confounding factors in biological data classification
Limin Li, Barbara Rakitsch and Karsten Borgwardt
ISMB 2011 and Bioinformatics 2011, 27 (13): i342-i348
external pageOnline | ETH Research Collection | Project page | external pageGitHub
Epistasis detection on quantitative phenotypes by exhaustive enumeration using GPUs
Tony Kam-Thong, Benno Pütz, Nazanin Karbalai, Bertram Müller-Myhsok and Karsten Borgwardt
ISMB 2011 and Bioinformatics 2011, 27 (13): i214-i221
external pageOnline | ETH Research Collection
Two-locus association mapping in subquadratic runtime
Panagiotis Achlioptas, Bernhard Schölkopf and Karsten Borgwardt
Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2011), 727-734
external pageOnline | ETH Research Collection | Project page | external pageGitHub
EPIBLASTER-Fast exhaustive two-locus epistasis detection strategy using graphical processing units
Tony Kam-Thong, Darina Czamara, Koji Tsuda, Karsten Borgwardt, Cathryn M. Lewis, Angelika Erhardt-Lehmann, Bernhard Hemmer, Peter Rieckmann, Markus Daake, Frank Weber, Christiane Wolf, Andreas Ziegler, Benno Pütz, Florian Holsboer, Bernhard Schölkopf and Bertram Müller-Myhsok
European Journal of Human Genetics 2011, 19: 465–471
external pageOnline | ETH Research Collection
Spatio-spectral remote sensing image classification with graph kernels
Gustavo Camps-Valls, Nino Shervashidze and Karsten Borgwardt
IEEE Geoscience and Remote Sensing Letters 2010, 99: 741-745
external pageOnline | ETH Research Collection
Discriminative frequent subgraph mining with optimality guarantees
Marisa Thoma, Hong Cheng, Arthur Gretton, Jiawei Han, Hans-Peter Kriegel, Alexander J. Smola, Le Song, Philip S. Yu, Xifeng Yan and Karsten M. Borgwardt
Journal of Statistical Analysis and Data Mining 2010, 3(5): 302–318
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A Robust Bayesian Two-Sample Test for Detecting Intervals of Differential Gene Expression in Microarray Time Series
Oliver Stegle, Katherine Denby, Emma Cooke, David Wild, Zoubin Ghahramani and Karsten Borgwardt
Journal of Computational Biology 2010, 17(3): 355-367
external pageOnline | ETH Research Collection
Gene function prediction from synthetic lethality networks via ranking on demand
Christoph Lippert, Zoubin Ghahramani and Karsten Borgwardt
Bioinformatics 2010, 26(7): 912-918
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Graph Kernels
SVN Vishwanathan, Nic Schraudolph, Risi Kondor and Karsten M. Borgwardt
Journal of Machine Learning Research (JMLR) 2010, 11: 1201−1242
external pageOnline | ETH Research Collection | Project page including code
Fast subtree kernels on graphs
Nino Shervashidze and Karsten M. Borgwardt
Advances in Neural Information Processing Systems 22 (NIPS 2009), 1660-1668
NIPS Outstanding Student Paper Award Winner
external pageOnline | ETH Research Collection
A Robust Bayesian Two-Sample Test for Detecting Intervals of Differential Gene Expression in Microarray Time Series
Oliver Stegle, Katherine Denby, David L. Wild, Zoubin Ghahramani and Karsten Borgwardt
In Lecture Notes in Computer Science 5541 "Research in Computational Molecular Biology. RECOMB 2009" , 201-216
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Discovering temporal patterns of differential gene expression in microarray time series
Oliver Stegle, Katherine Denby, David Wild, Stuart McHattie, Andrew Mead, Zoubin Ghahramani and Karsten Borgwardt
In Lecture Notes in Informatics 157 "German Conference on Bioinformatics 2009", 133-142
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The Graphlet Spectrum
Risi Kondor, Nino Shervashidze and Karsten M. Borgwardt
Proceedings of the 26th Annual International Conference on Machine Learning (ICML 2009), 529-536
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A kernel method for unsupervised structured network inference
Christoph Lippert, Oliver Stegle, Zoubin Ghahramani, Karsten Borgwardt
Artificial Intelligence and Statistics (AISTATS) 2009, 5: 368-375
Full oral presentation
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Efficient Graphlet Kernels for Large Graph Comparison
Nino Shervashidze, SVN Vishwanathan, Tobias Petri, Kurt Mehlhorn, Karsten Borgwardt
Artificial Intelligence and Statistics (AISTATS) 2009, 5: 488-495
external pageOnline | ETH Research Collection
Near-optimal supervised feature selection among frequent subgraphs
Marisa Thoma, Hong Cheng, Arthur Gretton, Jiawei Han, Hans-Peter Kriegel, Alexander J. Smola, Le Song, Philip S. Yu, Xifeng Yan and Karsten M. Borgwardt
SIAM Data Mining (SDM) 2009, 1076-1087
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Covariate Shift and Local Learning by Distribution Matching
Arthur Gretton, Alexander Smola, Jiayuan Huang, Marcel Schmittfull, Karsten Borgwardt and Bernhard Schölkopf
In Dataset Shift in Machine Learning. (Eds.) Joaquin Quiñonero-Candela, Masashi Sugiyama, Anton Schwaighofer and Neil D. Lawrence. MIT Press, Cambridge, MA, USA, 2008.
The genome of the simian and human malaria parasite Plasmodium knowlesi
A. Pain, U. Böhme, A.E. Berry, K. Mungall, R.D. Finn, A.P. Jackson, T. Mourier, J. Mistry, E.M. Pasini, M.A. Aslett, S. Balasubrammaniam, K. Borgwardt, K. Brooks, C. Carret, T.J. Carver, I. Cherevach, T. Chillingworth, T. Clarke, M.R. Galinski, N. Hall, D. Harper, D. Harris, H. Hauser, A. Ivens, C.S. Janssen, T. Keane, N. Larke, S. Lapp , M. Marti, S. Moule, I.M. Meyer, D. Ormond, N. Peters, M. Sanders, S. Sanders, T.J. Sergeant, M. Simmonds, F. Smith, R. Squares, S. Thurston, A.R. Tivey, D. Walker, B. White, E. Zuiderwijk, C. Churcher, M.A. Quail, A.F. Cowman, C.M.R. Turner, M.A. Rajandream , C.H.M. Kocken, A.W. Thomas, C. Newbold, B.G. Barrell and M. Berriman
Nature 2008, 455: 799-803
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Predicting phenotypic effects of gene perturbations in C.elegans using an integrated network model
Karsten Borgwardt
Bioessays 2008, 30(8): 707-710
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Metropolis Algorithms for Representative Subgraph Sampling
Christian Hübler, Karsten Borgwardt, Hans-Peter Kriegel and Zoubin Ghahramani
Eighth IEEE International Conference on Data Mining (ICDM) 2008, 283-292
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The skew spectrum of graphs
Risi Kondor and Karsten Borgwardt
Proceedings of the 25th International Conference on Machine Learning (ICML 2008), 496-503
external pageOnline | ETH Research Collection | external pagePDF
Future trends in data mining
Hans-Peter Kriegel, Karsten M. Borgwardt, Peer Kröger, Alexey Pryakhin, Matthias Schubert and Arthur Zimek
Data Mining and Knowledge Discorvery 2007, 15 (1): 87-97
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Gene Selection via the BAHSIC Family of Algorithms
Le Song, Justin Bedo, Karsten Borgwardt, Arthur Gretton and Alexander Smola
ISMB 2007 and Bioinformatics 2007, 23(13): i490-i498
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Colored Maximum Variance Unfolding
Le Song, Alexander Smola, Karsten Borgwardt and Arthur Gretton
Advances in Neural Information Processing Systems 20 (NIPS 2007), 1385-1392
Full oral presentation
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A Kernel Approach to Comparing Distributions
Arthur Gretton, Karsten Borgwardt, Malte Rasch, Bernhard Schölkopf and Alexander Smola
Proceedings of the 22nd National Conference on Artificial Intelligence (AAAI 2007), 2: 1637-1641
Highlights Track
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A Dependence Maximization View of Clustering
Le Song, Alexander Smola, Arthur Gretton and Karsten Borgwardt
Proceedings of the 24th International Conference on Machine Learning (ICML 2007), 815-822
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Supervised Feature Selection via Dependence Estimation
Le Song, Arthur Gretton, Alexander Smola, Karsten Borgwardt and Justin Bedo
Proceedings of the 24th International Conference on Machine Learning (ICML 2007), 823-830
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Graph kernels for disease outcome prediction from protein-protein interaction networks
Karsten Borgwardt, S.V.N. Vishwanathan, Nicol Schraudolph and Hans-Peter Kriegel
In Biocomputing 2007: Proceedings of the Pacific Symposium (PSB 2007), 12: 4-15
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Integrating structured biological data by Kernel Maximum Mean Discrepancy
Karsten Borgwardt, Arthur Gretton, Malte Rasch, Hans-Peter Kriegel, Bernhard Schölkopf and Alexander Smola
ISMB 2006 and Bioinformatics 2006, 22(14): e49-e57
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Kernel Extrapolation
S.V.N. Vishwanathan, Karsten Borgwardt, Omri Guttman and Alexander Smola
Neurocomputing 2006, 69(7-9): 721-729
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Pattern Mining in Frequent Dynamic Subgraphs
Karsten Borgwardt, Hans-Peter Kriegel and Peter Wackersreuther
In Proceedings of 6th International Conference on Data Mining (ICDM '06), 818-822
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Correcting Sample Selection Bias by Unlabeled Data
Jiayuan Huang, Alexander Smola, Arthur Gretton, Karsten Borgwardt and Bernhard Schölkopf
Advances in Neural Information Processing Systems 20 (NIPS 2006), 601-608
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A Kernel Method for the Two-Sample-Problem
Arthur Gretton, Karsten Borgwardt, Malte Rasch, Bernhard Schölkopf and Alexander Smola
Advances in Neural Information Processing Systems 19 (NIPS 2006), 513-520
Full oral presentation
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Fast Computation of Graph Kernels
S.V.N. Vishwanathan, Karsten Borgwardt, Nicol Schraudolph
Advances in Neural Information Processing Systems 19 (NIPS 2006), 1449-1456
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3DString: A Feature String Kernel for 3D Object Classification on Voxelized Data
Johannes Aßfalg, Karsten Borgwardt and Hans-Peter Kriegel
Proceedings of the 15th ACM International Conference on Information and Knowledge Management (CIKM 2006), 198-207
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Class prediction from time series gene expression profiles using dynamical systems kernels
Karsten Borgwardt, S.V.N. Vishwanathan and Hans-Peter Kriegel
Biocomputing 2006: Proceedings of the Pacific Symposium (PSB 2006), 547-558
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Protein Function Prediction via Graph Kernels
Karsten Borgwardt, Cheng S. Ong, Stefan Schönauer, S.V.N. Vishwanathan, Alexander Smola and Hans-Peter Kriegel
ISMB 2005 and Bioinformatics 2005, 21(suppl_1): i47-i56
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Shortest-path kernels on graphs
Karsten Borgwardt and Hans-Peter Kriegel
Proceedings of the 5th IEEE International Conference on Data Mining (ICDM 2005)
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Joint Regularization
Karsten Borgwardt, Omri Guttman, S.V.N. Vishwanathan and Alexander Smola
Proceedings of the 13th European Symposium on Artificial Neural Networks (ESANN 2005), 455-460
ETH Research Collection | DownloadDownload (PDF, 298 KB)