| Prediction of human population responses to toxic compounds by a collaborative competition F Eduati, LM Mangravite, T Wang, H Tang, JC Bare, R Huang, T Norman, ... Nature biotechnology 33 (9), 933-940, 2015 | 98 | 2015 |
| Wasserstein weisfeiler-lehman graph kernels M Togninalli, E Ghisu, F Llinares-López, B Rieck, K Borgwardt arXiv preprint arXiv:1906.01277, 2019 | 69 | 2019 |
| Fast and memory-efficient significant pattern mining via permutation testing F Llinares-López, M Sugiyama, L Papaxanthos, K Borgwardt Proceedings of the 21th ACM SIGKDD international conference on knowledge …, 2015 | 58 | 2015 |
| graphkernels: R and Python packages for graph comparison M Sugiyama, ME Ghisu, F Llinares-López, K Borgwardt Bioinformatics 34 (3), 530-532, 2018 | 45 | 2018 |
| Significant subgraph mining with multiple testing correction M Sugiyama, FL López, N Kasenburg, KM Borgwardt Proceedings of the 2015 SIAM International Conference on Data Mining, 37-45, 2015 | 42* | 2015 |
| Genome-wide detection of intervals of genetic heterogeneity associated with complex traits F Llinares-López, DG Grimm, DA Bodenham, U Gieraths, M Sugiyama, ... Bioinformatics 31 (12), i240-i249, 2015 | 34 | 2015 |
| Finding significant combinations of features in the presence of categorical covariates L Papaxanthos, F Llinares-López, D Bodenham, K Borgwardt Advances in neural information processing systems, 2279-2287, 2016 | 28 | 2016 |
| Genome-wide genetic heterogeneity discovery with categorical covariates F Llinares-López, L Papaxanthos, D Bodenham, D Roqueiro, ... Bioinformatics 33 (12), 1820-1828, 2017 | 16 | 2017 |
| Graph kernels: State-of-the-art and future challenges K Borgwardt, E Ghisu, F Llinares-López, L O'Bray, B Rieck arXiv preprint arXiv:2011.03854, 2020 | 14 | 2020 |
| Network-assisted analysis of GWAS data identifies a functionally-relevant gene module for childhood-onset asthma Y Liu, M Brossard, C Sarnowski, A Vaysse, M Moffatt, ... Scientific reports 7 (1), 1-10, 2017 | 14 | 2017 |
| CASMAP: detection of statistically significant combinations of SNPs in association mapping F Llinares-López, L Papaxanthos, D Roqueiro, D Bodenham, K Borgwardt Bioinformatics 35 (15), 2680-2682, 2019 | 8 | 2019 |
| Machine learning for biomarker discovery: significant pattern mining F Llinares-López, K Borgwardt Analyzing Network Data in Biology and Medicine: An Interdisciplinary …, 2019 | 3 | 2019 |
| Efficient and Modular Implicit Differentiation M Blondel, Q Berthet, M Cuturi, R Frostig, S Hoyer, F Llinares-López, ... arXiv preprint arXiv:2105.15183, 2021 | 2 | 2021 |
| Significant Pattern Mining for Biomarker Discovery F Llinares-López ETH Zurich, 2018 | 2 | 2018 |
| Interference-aware MIMO precoder design with realistic power constraints F Llinares-López, M Sánchez-Fernández, E Parrado-Hernandez, ... 2013 IEEE International Conference on Communications Workshops (ICC), 164-168, 2013 | 1 | 2013 |
| DeepConsensus: Gap-Aware Sequence Transformers for Sequence Correction G Baid, DE Cook, K Shafin, T Yun, F Llinares-Lopez, Q Berthet, ... bioRxiv, 2021 | | 2021 |
| Direct Antimicrobial Resistance Prediction from clinical MALDI-TOF mass spectra using Machine Learning C Weis, A Cuénod, B Rieck, F Llinares-López, O Dubuis, S Graf, C Lang, ... bioRxiv, 2020.07. 30.228411, 2021 | | 2021 |
| Wasserstein Weisfeiler-Lehman Graph Kernels M Togninalli, E Ghisu, F Llinares-López, BA Rieck, K Borgwardt Advances in Neural Information Processing Systems 32 9, 6407-6417, 2020 | | 2020 |
| Network-based analysis of genome-wide association data identifies a gene sub-network underlying childhood-onset asthma Y Liu, M Brossard, C Sarnowski, P Margaritte-Jeannin, F Llinares-López, ... Genetic Epidemiology 39 (7), 565-566, 2015 | | 2015 |
| Clustering techniques for base station coordination in a wireless cellular system F Llinares López | | 2012 |
Karsten BorgwardtProfessor, ETH ZurichVerified email at bsse.ethz.ch
