| A tutorial on support vector machine-based methods for classification problems in chemometrics J Luts, F Ojeda, R Van de Plas, B De Moor, S Van Huffel, JAK Suykens Analytica chimica acta 665 (2), 129-145, 2010 | 422 | 2010 |
| LS-SVMlab toolbox user's guide: version 1.7 K De Brabanter, P Karsmakers, F Ojeda, C Alzate, J De Brabanter, ... Katholieke Universiteit Leuven, 2010 | 364 | 2010 |
| Candidate gene prioritization by network analysis of differential expression using machine learning approaches D Nitsch, JP Gonçalves, F Ojeda, B De Moor, Y Moreau BMC bioinformatics 11, 1-16, 2010 | 145 | 2010 |
| Combined mRNA microarray and proteomic analysis of eutopic endometrium of women with and without endometriosis A Fassbender, N Verbeeck, D Börnigen, CM Kyama, A Bokor, ... Human Reproduction 27 (7), 2020-2029, 2012 | 107 | 2012 |
| A kernel-based integration of genome-wide data for clinical decision support A Daemen, O Gevaert, F Ojeda, A Debucquoy, JAK Suykens, C Sempoux, ... Genome medicine 1, 1-17, 2009 | 103 | 2009 |
| Low rank updated LS-SVM classifiers for fast variable selection F Ojeda, JAK Suykens, B De Moor Neural Networks 21 (2-3), 437-449, 2008 | 82 | 2008 |
| Prospective exploration of biochemical tissue composition via imaging mass spectrometry guided by principal component analysis R Van de Plas, F Ojeda, M Dewil, L Van Den Bosch, B De Moor, ... Biocomputing 2007, 458-469, 2007 | 76 | 2007 |
| Proteomics analysis of plasma for early diagnosis of endometriosis A Fassbender, E Waelkens, N Verbeeck, CM Kyama, A Bokor, ... Obstetrics & Gynecology 119 (2 Part 1), 276-285, 2012 | 68 | 2012 |
| Extracción de características usando transformada wavelet en la identificación de voces patológicas F Ojeda, G Castellanos Trabajo de Grado, Universidad Nacional de Colombia, Sede Manizales, 2003 | 10 | 2003 |
| Polynomial componentwise LS-SVM: fast variable selection using low rank updates F Ojeda, T Falck, B De Moor, JAK Suykens The 2010 International Joint Conference on Neural Networks (IJCNN), 1-7, 2010 | 8 | 2010 |
| Semi-supervised learning of sparse linear models in mass spectral imaging F Ojeda, M Signoretto, R Van de Plas, E Waelkens, B De Moor, ... Pattern Recognition in Bioinformatics: 5th IAPR International Conference …, 2010 | 8 | 2010 |
| LS-SVMlab Toolbox User’s Guide J Suykens, KD Brabanter, P Karsmakers, F Ojeda, C Alzate, JD Brabanter, ... Technical report, Katholieke Universiteit Leuven, 2011 | 7 | 2011 |
| Predicting receptor-ligand pairs through kernel learning E Iacucci, F Ojeda, B De Moor, Y Moreau BMC bioinformatics 12, 1-8, 2011 | 6 | 2011 |
| Variable selection by rank-one updates for least squares support vector machines F Ojeda, JAK Suykens, B De Moor 2007 International Joint Conference on Neural Networks, 2283-2288, 2007 | 5 | 2007 |
| Kernel based methods for microarray and mass spectrometry data analysis F Ojeda PhD thesis, Faculty of Engineering, KU Leuven, Leuven, Belgium, 2011 | 4 | 2011 |
| Kernel Based Methods for Microarray and Mass Spectrometry Data Analysis (Kernel gebaseerde methoden voor gegevensanalyse van microroosters en massaspectrometrie) F Ojeda | | 2011 |
| Biomarkers in plasma or serum: Pitfalls in data processing A Fassbender, E Waelkens, C Kyama, A Bokor, A Vodolazakaia, ... Reproductive Sciences 18 (3), 191, 2011 | | 2011 |
| Entropy based selection for spectral clustering F Ojeda, C Alzate, B De Moor, JAK Suykens KU Leuven Technical report, 2011 | | 2011 |
| Learning gene networks with sparse inducing estimators F Ojeda, M Signoretto, J Suykens Machine Learning in Systems Biology, 167, 2009 | | 2009 |
| Clinical Microarray Data Analysis F Ojeda, F De Smet, T De Bie, JAK Suykens, BLR De Moor Kernel Methods in Bioengineering, Signal and Image Processing, 64, 2006 | | 2006 |
