| Fast neighborhood subgraph pairwise distance kernel F Costa, K De Grave Proceedings of the 26th International Conference on Machine Learning, 255-262, 2010 | 347 | 2010 |
| Predicting human olfactory perception from chemical features of odor molecules A Keller, RC Gerkin, Y Guan, A Dhurandhar, G Turu, B Szalai, ... Science 355 (6327), 820-826, 2017 | 318 | 2017 |
| Cheaper faster drug development validated by the repositioning of drugs against neglected tropical diseases K Williams, E Bilsland, A Sparkes, W Aubrey, M Young, LN Soldatova, ... Journal of the Royal society Interface 12 (104), 20141289, 2015 | 174 | 2015 |
| Machine learning applications in proteomics research: How the past can boost the future P Kelchtermans, W Bittremieux, K De Grave, S Degroeve, J Ramon, ... Proteomics 14 (4-5), 353-366, 2014 | 78 | 2014 |
| klog: A language for logical and relational learning with kernels P Frasconi, F Costa, L De Raedt, K De Grave Artificial Intelligence 217, 117-143, 2014 | 59 | 2014 |
| Optimization of cellulose acetate nanofiltration membranes for micropollutant removal via genetic algorithms and high throughput experimentation A Cano-Odena, M Spilliers, T Dedroog, K De Grave, J Ramon, ... Journal of Membrane Science 366 (1-2), 25-32, 2011 | 51 | 2011 |
| The dawn of software engineering: From Turing to Dijkstra EG Daylight, N Wirth, T Hoare, B Liskov, P Naur, KD Grave Lonely Scholar, 2012 | 44 | 2012 |
| Active learning for high throughput screening K De Grave, J Ramon, L De Raedt International Conference on Discovery Science, 185-196, 2008 | 29 | 2008 |
| Designing biomedical proteomics experiments: state-of-the-art and future perspectives E Maes, P Kelchtermans, W Bittremieux, K De Grave, S Degroeve, ... Expert review of proteomics 13 (5), 495-511, 2016 | 21 | 2016 |
| Molecular graph augmentation with rings and functional groups KD Grave, F Costa Journal of chemical information and modeling 50 (9), 1660-1668, 2010 | 20 | 2010 |
| On the complexity of haplotyping a microbial community SM Nicholls, W Aubrey, K De Grave, L Schietgat, CJ Creevey, A Clare Bioinformatics 37 (10), 1360-1366, 2021 | 18 | 2021 |
| Representation of probabilistic scientific knowledge LN Soldatova, A Rzhetsky, K De Grave, RD King Journal of biomedical semantics 4, 1-12, 2013 | 17 | 2013 |
| Multi-objective optimization with surrogate trees D Verbeeck, F Maes, K De Grave, H Blockeel Proceedings of the 15th annual conference on Genetic and evolutionary …, 2013 | 12 | 2013 |
| Integrating adaptation mechanisms using control theory centric architecture models: A case study F Křikava, P Collet, R Rouvoy 11th International Conference on Autonomic Computing (ICAC 14), 25-32, 2014 | 10 | 2014 |
| PIUS: peptide identification by unbiased search EP Costa, G Menschaert, W Luyten, K De Grave, J Ramon Bioinformatics 29 (15), 1913-1914, 2013 | 8* | 2013 |
| Active learning for primary drug screening K De Grave, J Ramon, L De Raedt Benelearn 08, The Annual Belgian-Dutch Machine Learning Conference 2008, 55-56, 2008 | 8 | 2008 |
| Recovery of gene haplotypes from a metagenome S Nicholls, W Aubrey, A Edwards, K de Grave, S Huws, S Leander, ... | 7 | 2018 |
| Eve: Integration of machine learning with compound testing in a robot scientist K Williams, E Bilsland, A Sparkes, W Aubrey, M Young, LN Soldatova, ... Antenna Live: Robot Scientist, Location: London, 2015 | 5 | 2015 |
| klognlp: Graph kernel–based relational learning of natural language M Verbeke, P Frasconi, K De Grave, F Costa, L De Raedt Proceedings of 52nd Annual Meeting of the Association for Computational …, 2014 | 5 | 2014 |
| Probabilistic recovery of cryptic haplotypes from metagenomic data SM Nicholls, W Aubrey, K De Grave, L Schietgat, CJ Creevey, A Clare bioRxiv, 117838, 2017 | 4 | 2017 |
