Patrick E. Meyer
Patrick E. Meyer
Associate Professor at Liège University
Verified email at - Homepage
Cited by
Cited by
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
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
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
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
On the use of variable complementarity for feature selection in cancer classification
PE Meyer, G Bontempi
Applications of Evolutionary Computing, 91-102, 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
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
Information-theoretic variable selection and network inference from microarray data
PE Meyer
Ph. D. Thesis. Université Libre de Bruxelles, 2008
Information-Theoretic Inference of Gene Networks Using Backward Elimination.
P Meyer, D Marbach, S Roy, M Kellis
BIOCOMP, 700-705, 2010
Causal filter selection in microarray data
G Bontempi, PE Meyer
Proceedings of the 27th International Conference on Machine Learning (ICML …, 2010
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
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
[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
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
Open-hardware wireless controller and 3D-printed pumps for efficient liquid manipulation
A Gervasi, P Cardol, PE Meyer
HardwareX 9, e00199, 2021
Biological network inference using redundancy analysis
PE Meyer, K Kontos, G Bontempi
International Conference on Bioinformatics Research and Development, 16-27, 2007
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
Combining lazy learning, racing and subsampling for effective feature selection
G Bontempi, M Birattari, PE Meyer
Adaptive and Natural Computing Algorithms, 393-396, 2005
Inferring causal relationships using informationtheoretic measures
C Olsen, PE Meyer, G Bontempi
Proceedings of the 5th Benelux Bioinformatics Conference (BBC09), 2009
Efficient combination of pairwise feature networks
P Bellot Pujalte, PE Meyer
Challenges in Machine Learning Volume 11: Connectomics, 93-100, 2014
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