| Identification of Functional Elements and Regulatory Circuits by Drosophila modENCODE modENCODE Consortium, S Roy, J Ernst, PV Kharchenko, P Kheradpour, ... Science 330 (6012), 1787-1797, 2010 | 1105 | 2010 |
| minet: A R/Bioconductor Package for Inferring Large Transcriptional Networks Using Mutual Information PE Meyer, F Lafitte, G Bontempi BMC bioinformatics 9, 1-10, 2008 | 655 | 2008 |
| Information-theoretic inference of large transcriptional regulatory networks PE Meyer, K Kontos, F Lafitte, G Bontempi EURASIP journal on bioinformatics and systems biology 2007, 1-9, 2007 | 565 | 2007 |
| Information-theoretic feature selection in microarray data using variable complementarity PE Meyer, C Schretter, G Bontempi IEEE Journal of Selected Topics in Signal Processing 2 (3), 261-274, 2008 | 344 | 2008 |
| On the use of variable complementarity for feature selection in cancer classification PE Meyer, G Bontempi Applications of Evolutionary Computing, 91-102, 2006 | 231 | 2006 |
| Predictive regulatory models in Drosophila melanogaster by integrative inference of transcriptional networks D Marbach, S Roy, F Ay, PE Meyer, R Candeias, T Kahveci, CA Bristow, ... Genome research 22 (7), 1334-1349, 2012 | 146 | 2012 |
| On the impact of entropy estimation on transcriptional regulatory network inference based on mutual information C Olsen, PE Meyer, G Bontempi EURASIP Journal on Bioinformatics and Systems Biology 2009, 1-9, 2008 | 98 | 2008 |
| Infotheo: information-theoretic measures PE Meyer R package version 1 (0), 2014 | 78* | 2014 |
| Information-theoretic variable selection and network inference from microarray data PE Meyer Ph. D. Thesis. Université Libre de Bruxelles, 2008 | 76 | 2008 |
| Causal filter selection in microarray data G Bontempi, PE Meyer Proceedings of the 27th International Conference on Machine Learning (ICML …, 2010 | 66 | 2010 |
| Information-Theoretic Inference of Gene Networks Using Backward Elimination. P Meyer, D Marbach, S Roy, M Kellis BIOCOMP, 700-705, 2010 | 65 | 2010 |
| Using a Structural Root System Model to Evaluate and Improve the Accuracy of Root Image Analysis Pipelines G Lobet, IT Koevoets, M Noll, PE Meyer, P Tocquin, L Pagès, C Périlleux Frontiers in plant science 8, 2017 | 57 | 2017 |
| NetBenchmark: a bioconductor package for reproducible benchmarks of gene regulatory network inference P Bellot, C Olsen, P Salembier, A Oliveras-Vergés, PE Meyer BMC bioinformatics 16, 1-15, 2015 | 54 | 2015 |
| [18F] FDG PET radiomics to predict disease-free survival in cervical cancer: a multi-scanner/center study with external validation M Ferreira, P Lovinfosse, J Hermesse, M Decuypere, C Rousseau, ... European journal of nuclear medicine and molecular imaging 48 (11), 3432-3443, 2021 | 46 | 2021 |
| Combining semi-automated image analysis techniques with machine learning algorithms to accelerate large scale genetic studies. JA Atkinson, G Lobet, M Noll, PE Meyer, M Griffiths, DM Wells GigaScience, 2017 | 28 | 2017 |
| Distinction of lymphoma from sarcoidosis at FDG PET/CT-evaluation of radiomic-feature guided machine learning versus human reader performance P Lovinfosse, M Ferreira, N Withofs, A Jadoul, C Derwael, AN Frix, J Guiot, ... Journal of Nuclear Medicine, 2022 | 23 | 2022 |
| Open-hardware wireless controller and 3D-printed pumps for efficient liquid manipulation A Gervasi, P Cardol, PE Meyer HardwareX 9, e00199, 2021 | 19 | 2021 |
| Biological network inference using redundancy analysis PE Meyer, K Kontos, G Bontempi International Conference on Bioinformatics Research and Development, 16-27, 2007 | 17 | 2007 |
| Inferring causal relationships using informationtheoretic measures C Olsen, PE Meyer, G Bontempi Proceedings of the 5th Benelux Bioinformatics Conference (BBC09), 2009 | 10 | 2009 |
| Combining lazy learning, racing and subsampling for effective feature selection G Bontempi, M Birattari, PE Meyer Adaptive and Natural Computing Algorithms, 393-396, 2005 | 9 | 2005 |
