  | Gervasi, A., Meyer, P., & Cardol, P. (14 March 2024). Modular device for simultaneous analysis of phototaxis and NPQ in photosynthetic organisms [Poster presentation]. Journées Françaises de la Photosynthèse, Paris, France.  Editorial reviewed |
  | Meyer, P.* , & Chaillot, P. (2023). All-cause Mortality During Covid-19 Vaccinations in European Active Populations. In ICCBB 2023 - Proceedings of the 2023 7th International Conference on Computational Biology and Bioinformatics. Association for Computing Machinery. doi:10.1145/3638569.3638583 Peer reviewed |
 | 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 |
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 |
 | 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. (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 |
 | 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 |
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., 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 |