Profil

Meyer Patrick

Département des sciences de la vie > Biologie des systèmes et bioinformatique

InBioS

See author's contact details
Main Referenced Co-authors
Bontempi, Gianluca (19)
Bellot, Pau (7)
Bernard, Claire  (5)
Hustinx, Roland  (5)
Lovinfosse, Pierre  (5)
Main Referenced Keywords
Machine Learning (2); Radiomics (2); 18F-FDG PET/CT (1); 3D printing (1); [18F]FDG PET/CT (1);
Main Referenced Unit & Research Centers
InBios - Integrative Biological Sciences - ULiège [BE] (1)
Main Referenced Disciplines
Engineering, computing & technology: Multidisciplinary, general & others (25)
Life sciences: Multidisciplinary, general & others (11)
Biotechnology (3)
Computer science (2)
Phytobiology (plant sciences, forestry, mycology...) (2)

Publications (total 43)

The most downloaded
138 downloads
Gervasi, A., Cardol, P., & Meyer, P. (April 2021). Open-hardware wireless controller and 3D-printed pumps for efficient liquid manipulation. HardwareX, 9. doi:10.1016/j.ohx.2021.e00199 https://hdl.handle.net/2268/261580

The most cited

972 citations (OpenCitations)

Roy, S., Ernst, J., Kharchenko, P. V., Kheradpour, P., Negre, N., Eaton, M. L., Landolin, J. M., Bristow, C. A., Ma, L., Lin, M. F., Washietl, S., Arshinoff, B. I., Ay, F., Meyer, P., Robine, N., Washington, N. L., Di Stefano, L., Berezikov, E., Brown, C. D., ... Kellis, M. (2010). Identification of functional elements and regulatory circuits by Drosophila modENCODE. Science, 330 (6012), 1787-97. doi:10.1126/science.1198374 https://hdl.handle.net/2268/163897

Gervasi, A., Cardol, P., & Meyer, P. (26 May 2022). Automated Open-Hardware Multiwell Imaging Station for Microorganisms Observation. Micromachines, 13 (6), 833. doi:10.3390/mi13060833
Peer Reviewed verified by ORBi

LOVINFOSSE, P., Ferreira, M., WITHOFS, N., JADOUL, A., Derwael, C., Frix, A.-N., GUIOT, J., BERNARD, C., Diep, A. N., Donneau, A.-F., LEJEUNE, M., BONNET, C., Vos, W., Meyer, P., & HUSTINX, R. (19 May 2022). Distinction of lymphoma from sarcoidosis at FDG PET/CT - evaluation of radiomic-feature guided machine learning versus human reader performance. Journal of Nuclear Medicine, 63, 1933-1940. doi:10.2967/jnumed.121.263598
Peer Reviewed verified by ORBi

Gervasi, A., Cardol, P., & Meyer, P. (April 2021). Open-hardware wireless controller and 3D-printed pumps for efficient liquid manipulation. HardwareX, 9. doi:10.1016/j.ohx.2021.e00199
Peer Reviewed verified by ORBi

Da Silva Ferreira, M., LOVINFOSSE, P., HERMESSE, J., DE CUYPERE, M., Rousseau, C., Lucia, F., Schick, U., Reinhold, C., Robin, P., Hatt, M., Visvikis, D., Bernard, C., Leijenaar, R. T. H., Kridelka, F., Lambin, P., Meyer, P., & Hustinx, R. (2021). [(18)F]FDG PET radiomics to predict disease-free survival in cervical cancer: a multi-scanner/center study with external validation. European Journal of Nuclear Medicine and Molecular Imaging. doi:10.1007/s00259-021-05303-5
Peer Reviewed verified by ORBi

Da Silva Ferreira, M., LOVINFOSSE, P., DE CUYPERE, M., Rovira, R., Lucia, F., Schick, U., Vallières, M., Bonaffini, P., Reinhold, C., Visvikis, D., Hatt, M., BERNARD, C., Leijenaar, R., Walsh, S., KRIDELKA, F., Meyer, P., & HUSTINX, R. (29 November 2019). FDG PET radiomics to predict disease free survival in Cervical Cancer [Paper presentation]. Bioforum Liege 2019.

Da Silva Ferreira, M., LOVINFOSSE, P., DE CUYPERE, M., Rovira, R. R., Lucia, F., Schick, U., Vallières, M., Bonaffini, P., Reinhold, C., Visvikis, D., Hatt, M., BERNARD, C., Leijenaar, R., Walsh, S., KRIDELKA, F., Meyer, P., & HUSTINX, R. (02 November 2019). FDG PET radiomics to predict disease free survival in Cervical Cancer [Paper presentation]. 2019 IEEE Nuclear Science Symposium & Medical Imaging Conference.

Gervasi, A., Cardol, P., & Meyer, P. (2019). Designing an Open-hardware Remotely Controllable Phototurbidostat for Studying Algal Growth. In 3rd International Conference on Computational Biology and Bioinformatics (pp. 13-19). doi:10.1145/3365966.3365969
Peer reviewed

Da Silva Ferreira, M., LOVINFOSSE, P., DE CUYPERE, M., Rovira, R., Lucia, F., Schick, U., Vallières, M., Bonaffini, P., Reinhold, C., Visvikis, D., Hatt, M., BERNARD, C., Leijenaar, R., Walsh, S., KRIDELKA, F., Meyer, P., & HUSTINX, R. (September 2019). Radiomics for Disease Free Survival prediction using pre-treatment FDG PET images [Paper presentation]. "Imaging of diagnostic and therapeutic biomarkers in Oncology“ workshop Manoir de Kerdréan, Le Bono, France, September 25th- 28th, 2019.

Atkinson, J., Lobet, G., Noll, M., Meyer, P., Griffiths, M., & Wells, D. (2017). Combining semi-automated image analysis techniques with machine learning algorithms to accelerate large scale genetic studies. GigaScience. doi:10.1093/gigascience/gix084
Peer Reviewed verified by ORBi

Noll, M., Lété, J., & Meyer, P. (2017). Gene Entity Recognition of Full Text Articles. In ICBBS '17 Proceedings of the 6th International Conference on Bioinformatics and Biomedical Science (pp. 162-167). New York, United States: ACM. doi:10.1145/3121138.3121167
Peer reviewed

Pham, C. N., Haibe-Kains, Bellot, P., Bontempi, G., & Meyer, P. (2017). Study of Meta-analysis strategies for network inference using information-theoretic approaches. BioData Mining. doi:10.1186/s13040-017-0136-6
Peer Reviewed verified by ORBi

Pham, C. N., Haibe-Kains, Bellot, P., Bontempi, G., & Meyer, P. (2017). Study of Meta-Analysis Strategies for Network Inference using Information-Theoretic Approaches. In IEEE Dexa workshops 2016. doi:10.1109/DEXA.2016.030
Peer reviewed

Lobet, G., Koevoets, I., Noll, M., Meyer, P., Tocquin, P., Pagès, L., & Périlleux, C. (2017). Using a Structural Root System Model to Evaluate and Improve the Accuracy of Root Image Analysis Pipelines. Frontiers in Plant Science, 8, 447. doi:10.3389/fpls.2017.00447
Peer Reviewed verified by ORBi

Bellot, P., & Meyer, P. (2017). Efficient Combination of Pairwise Feature Networks. In Neural Connectomics Challenge. Springer International Publishing. doi:10.1007/978-3-319-53070-3_7
Peer reviewed

Bellot, P., & Meyer, P. (2016). Efficient combination of feature networks. In Challenge in Machine Learning Volume 11. Springer.
Peer reviewed

Bellot, P., Olsen, C., Salembier, P., Oliveras-Vergés, A., & Meyer, P. (2015). NetBenchmark: a bioconductor package for reproducible benchmarks of gene regulatory network inference. BMC Bioinformatics. doi:10.1186/s12859-015-0728-4
Peer Reviewed verified by ORBi

Bellot, P., Salembier, P., Oliveras-Verges, A., & Meyer, P. (2015). Study of Normalization and Aggregation Approaches for Consensus Network Estimation. In 2015 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE. doi:10.1109/SSCI.2015.155
Peer reviewed

Bellot, P., & Meyer, P. (2014). Efficient combination of pairwise feature networks. Proceedings of Machine Learning Research.
Peer Reviewed verified by ORBi

Meyer, P. (2014). The Rank Minrelation Coefficient. Quality Technology and Quantitative Management, 11. doi:10.1080/16843703.2014.11673325
Peer reviewed

Meyer, P., & Bontempi, G. (2013). Information-Theoretic Gene Selection In Expression Data. In Biological Knowledge Discovery Handbook: Preprocessing, Mining, and Postprocessing of Biological Data (pp. 399-420). John Wiley Sons, Inc.
Peer reviewed

Lopes, M., Meyer, P., & Bontempi, G. (2012). Estimation of temporal lags for the inference of gene regulatory networks from time series (inproceedings) Author. In In proceedings of BENELEARN'12.
Peer reviewed

Marbach, D., Roy, S., Ay, F., Meyer, P., Candeias, R., Kahveci, T., Bristow, C. A., & Kellis, M. (2012). Predictive regulatory models in Drosophila melanogaster by integrative inference of transcriptional networks. Genome Research, 22 (7), 1334-1349. doi:10.1101/gr.127191.111
Peer Reviewed verified by ORBi

Meyer, P., Olsen, C., & Bontempi, G. (2011). Transcriptional Network Inference Based on Information Theory. In Applied Statistics for Network Biology: Methods in Systems Biology (pp. 67-89). Wiley-VCH Verlag GmbH Co. KGaA. doi:10.1002/9783527638079.ch4
Peer reviewed

Meyer, P., Marbach, D., Roy, S., & Kellis, M. (2010). Information-Theoretic Inference of Gene Networks Using Backward Elimination. In BIOCOMP'10.
Peer reviewed

Bontempi, G., & Meyer, P. (2010). Causal filter selection in microarray data. In Proceedings of the 27th International Conference on Machine Learning (ICML-10).
Peer reviewed

Meyer, P., Lafitte, F., & Bontempi, G. (2010). Package ‘minet’. In Bioconductor Packages. Bioconductor.
Peer reviewed

Roy, S., Ernst, J., Kharchenko, P. V., Kheradpour, P., Negre, N., Eaton, M. L., Landolin, J. M., Bristow, C. A., Ma, L., Lin, M. F., Washietl, S., Arshinoff, B. I., Ay, F., Meyer, P., Robine, N., Washington, N. L., Di Stefano, L., Berezikov, E., Brown, C. D., ... Kellis, M. (2010). Identification of functional elements and regulatory circuits by Drosophila modENCODE. Science, 330 (6012), 1787-97. doi:10.1126/science.1198374
Peer Reviewed verified by ORBi

Meyer, P., Haibe-Kains, B., & Bontempi, G. (2009). Meta-Analysis in Transcriptional Network Inference. In Recomb Satellite 09.

Olsen, C., Meyer, P., & Bontempi, G. (2009). Inferring causal relationships using information-theoretic measures [Paper presentation]. Benelux Bioinformatics Conference (BBC09).

Olsen, C., Meyer, P., & Bontempi, G. (2009). On the impact of entropy estimation on transcriptional regulatory network inference based on mutual information. EURASIP Journal on Bioinformatics and Systems Biology, 2009 (1), 308959. doi:10.1155/2009/308959
Peer Reviewed verified by ORBi

Olsen, C., Meyer, P., & Bontempi, G. (2008). Fact sheet: Using mutual information to infer causal relationships Catharina. In JMLR: Workshop and Conference Proceedings-NIPS 2008 workshop on causality.

Meyer, P. (2008). Information-Theoretic Variable Selection and Network Inference from Microarray Data [Doctoral thesis, ULB - Université Libre de Bruxelles]. ORBi-University of Liège. https://orbi.uliege.be/handle/2268/163904

Bontempi, G., & Meyer, P. (2008). A model-based relevance estimation approach for feature selection in microarray datasets. In Artificial Neural Networks-ICANN 2008. Springer.
Peer reviewed

Meyer, P., Schretter, C., & Bontempi, G. (2008). Information-theoretic feature selection in microarray data using variable complementarity. IEEE Journal of Selected Topics in Signal Processing, 2 (3), 261-274. doi:10.1109/JSTSP.2008.923858
Peer Reviewed verified by ORBi

Meyer, P., Lafitte, F., & Bontempi, G. (2008). minet: A R/Bioconductor package for inferring large transcriptional networks using mutual information. BMC Bioinformatics, 9 (1), 461. doi:10.1186/1471-2105-9-461
Peer Reviewed verified by ORBi

Meyer, P., Kontos, K., Lafitte, F., & Bontempi, G. (2007). Information-theoretic inference of large transcriptional regulatory networks. EURASIP Journal on Bioinformatics and Systems Biology, 2007. doi:10.1155/2007/79879
Peer Reviewed verified by ORBi

Meyer, P., Kontos, K., & Bontempi, G. (2007). Biological network inference using redundancy analysis. In Bioinformatics Research and Development. Springer.
Peer reviewed

Meyer, P., & Bontempi, G. (2006). On the use of variable complementarity for feature selection in cancer classification. In Applications of Evolutionary Computing. Springer.
Peer reviewed

Meyer, P., Caelen, O., & Bontempi, G. (2005). Speeding up Feature Selection by Using an Information Theoretic Bound. In BNAIC.
Peer reviewed

Bontempi, G., Birattari, M., & Meyer, P. (2005). Combining lazy learning, racing and subsampling for effective feature selection. In Adaptive and Natural Computing Algorithms. Springer.
Peer reviewed

Meyer, P. (2004). Feature Subset Selection in Regression with High Feature-to-Sample Ratio Datasets [Master’s dissertation, Computer Science Department of the Universite Libre de Bruxelles]. ORBi-University of Liège. https://orbi.uliege.be/handle/2268/163908

Meyer, P. (2004). Collective Retrieval hy Autonomous Rohots [Paper presentation]. STAIRS.

Meyer, P. (2003). Experiences sur le comportement collectif et social des robots [Master’s dissertation, ULB - Université Libre de Bruxelles]. ORBi-University of Liège. https://orbi.uliege.be/handle/2268/163907

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