Claes, Y., Huynh-Thu, V. A., & Geurts, P. (2023). Knowledge-Guided Additive Modeling for Supervised Regression. Lecture Notes in Computer Science. doi:10.1007/978-3-031-45275-8_5 |
Huynh-Thu, V. A., & Geurts, P. (2023). Optimizing model-agnostic random subspace ensembles. Machine Learning. doi:10.1007/s10994-023-06427-5 |
Pierre, N., Huynh-Thu, V. A., Marichal, T., Allez, M., Bouhnik, Y., Laharie, D., Bourreille, A., Colombel, J.-F., Meuwis, M.-A., Louis, E., & GETAID (Groupe d’Etude Thérapeutique des Affections Inflammatoires du tube Digestif). (2022). Distinct blood protein profiles associated with the risk of short-term and mid/long-term clinical relapse in patients with Crohn's disease stopping infliximab: when the remission state hides different types of residual disease activity. Gut, 2022-327321. doi:10.1136/gutjnl-2022-327321 |
Sutera, A., Louppe, G., Huynh-Thu, V. A., Wehenkel, L., & Geurts, P. (2021). From global to local MDI variable importances for random forests and when they are Shapley values. Advances in Neural Information Processing Systems. |
Pierre, N., Baiwir, D., Huynh-Thu, V. A., Mazzucchelli, G., Smargiasso, N., De Pauw, E., Bouhnik, Y., Laharie, D., Colombel, J.-F., Meuwis, M.-A., & Louis, E. (2021). Discovery of biomarker candidates associated with the risk of short-term and mid/long-term relapse after infliximab withdrawal in Crohn's patients: a proteomics-based study. Gut. doi:10.1136/gutjnl-2020-322100 |
Pierre, N., Huynh-Thu, V. A., Allez, M., Bouhnik, Y., Laharie, D., Bourreille, A., Colombel, J. F., Meuwis, M.-A., & Louis, E. (2021). Blood proteins related to immunoregulation or cellular junctions reveal distinct biological profiles associated with the risk of short-term versus mid/long-term relapse in Crohn’s Disease patients stopping infliximab. Journal of Crohn's and Colitis. doi:10.1093/ecco-jcc/jjab075.011 |
Pierre, N., Huynh-Thu, V. A., Matthieu, A., Yoram, B., David, L., Arnaud, B., Jean-Frédéric, C., Meuwis, M.-A., & Louis, E. (2021). Blood proteins linked to immune tolerance, inflammation and cellular junctions reveal a succession of pathophysiological events preceding the relapse in Crohn’s disease patients stopping infliximab [Paper presentation]. 33rd Belgian Week of Gastroenterology 2021, Belgium. |
Huynh-Thu, V. A., & Geurts, P. (2019). Unsupervised gene network inference with decision trees and Random forests. In G. Sanguinetti & V. A. Huynh-Thu (Eds.), Gene Regulatory Networks. New York, United States - New York: Humana Press. doi:10.1007/978-1-4939-8882-2_8 |
Huynh-Thu, V. A., & Sanguinetti, G. (2019). Tree-based learning of regulatory network topologies and dynamics with Jump3. In G. Sanguinetti & V. A. Huynh-Thu (Eds.), Gene Regulatory Networks. New York, United States - New York: Humana Press. doi:10.1007/978-1-4939-8882-2_9 |
Huynh-Thu, V. A., & Sanguinetti, G. (2019). Gene regulatory network inference: An Introductory Survey. In G. Sanguinetti & V. A. Huynh-Thu (Eds.), Gene Regulatory Networks. New York, United States - New York: Humana Press. doi:10.1007/978-1-4939-8882-2_1 |
Huynh-Thu, V. A., & Geurts, P. (21 February 2018). dynGENIE3: dynamical GENIE3 for the inference of gene networks from time series expression data. Scientific Reports, 8, 3384. doi:10.1038/s41598-018-21715-0 |
Vecoven, N., Begon, J.-M., Huynh-Thu, V. A., & Geurts, P. (2017). Nets versus trees for feature ranking and gene network inference. ORBi-University of Liège. https://orbi.uliege.be/handle/2268/231719. |
Aibar, S., González-Blas, C. B., Moerman, T., Huynh-Thu, V. A., Imrichova, H., Hulselmans, G., Rambow, F., Marine, J.-C., Geurts, P., Aerts, J., van den Oord, J., Atak, Z. K., Wouters, J., & Aerts, S. (09 October 2017). SCENIC: single-cell regulatory network inference and clustering. Nature Methods, 14, 1083–1086. doi:10.1038/nmeth.4463 |
Milligan, L., Huynh-Thu, V. A., Delan-Forino, C., Tuck, A., Petfalski, E., Lombraña, R., Sanguinetti, Kudla, G., & Tollervey, D. (June 2016). Strand-specific, high-resolution mapping of modified RNA polymerase II. Molecular Systems Biology, 12 (6), 874. doi:10.15252/msb.20166869 |
Sutera, A., Louppe, G., Huynh-Thu, V. A., Wehenkel, L., & Geurts, P. (2016). Context-dependent feature analysis with random forests. In Uncertainty In Artificial Intelligence: Proceedings of the Thirty-Two Conference (2016). |
Huynh-Thu, V. A., & Sanguinetti, G. (2016). Combining tree-based and dynamical systems for the inference of gene regulatory networks [Paper presentation]. Workshop on Network inference: New methods and new data. |
Huynh-Thu, V. A., & Sanguinetti, G. (2015). Combining tree-based and dynamical systems for the inference of gene regulatory networks. Bioinformatics, 31 (10), 1614-1622. doi:10.1093/bioinformatics/btu863 |
Potier, D., Davie, K., Hulselmans, G., Naval Sanchez, M., Haagen, L., Huynh-Thu, V. A., Koldere, D., Celik, A., Geurts, P., Christiaens, V., & Aerts, S. (18 December 2014). Mapping Gene Regulatory Networks in Drosophila Eye Development by Large-Scale Transcriptome Perturbations and Motif Inference. Cell Reports, 9 (6), 2290-2303. doi:10.1016/j.celrep.2014.11.038 |
Ruyssinck, J., Huynh-Thu, V. A., Geurts, P., Dhaene, T., Demeester, P., & Saeys, Y. (25 March 2014). NIMEFI: Gene Regulatory Network Inference using Multiple Ensemble Feature Importance Algorithms. PLoS ONE, 9 (3), 92709. doi:10.1371/journal.pone.0092709 |
Marchand, G., Huynh-Thu, V. A., Kane, N. C., Arribat, S., Vares, D., Rengel, D., Balzergue, S., Rieseberg, L. H., Vincourt, P., Geurts, P., Vignes, M., & Langlade, N. B. (2014). Bridging physiological and evolutionary time-scales in a gene regulatory network. New Phytologist, 203 (2), 685-696. doi:10.1111/nph.12818 |
Huynh-Thu, V. A., & Geurts, P. (2013). Gene regulatory network inference from expression and genetic data using tree-based methods [Paper presentation]. STATSEQ meeting on Gene Network Inference with Systems genetic data and beyond, Paris, France. |
Huynh-Thu, V. A., Wehenkel, L., & Geurts, P. (2013). Gene regulatory network inference from systems genetics data using tree-based methods. In A. de la Fuente (Ed.), Gene Network Inference - Verification of Methods for Systems Genetics Data (pp. 63-85). Springer. doi:10.1007/978-3-642-45161-4_5 |
Bogie, J. F. J., Timmermans, S., Huynh-Thu, V. A., Irrthum, A., Smeets, H. J. M., Gustafsson, J.-A., Steffensen, K. R., Mulder, M., Stinissen, P., Hellings, N., & Hendriks, J. J. A. (12 September 2012). Myelin-Derived Lipids Modulate Macrophage Activity by Liver X Receptor Activation. PLoS ONE, 7 (9), 44998. doi:10.1371/journal.pone.0044998 |
Huynh-Thu, V. A., Saeys, Y., Wehenkel, L., & Geurts, P. (25 April 2012). Statistical interpretation of machine learning-based feature importance scores for biomarker discovery. Bioinformatics, 28 (13), 1766-1774. doi:10.1093/bioinformatics/bts238 |
Huynh-Thu, V. A. (2012). Machine learning-based feature ranking: Statistical interpretation and gene network inference [Doctoral thesis, ULiège - Université de Liège]. ORBi-University of Liège. https://orbi.uliege.be/handle/2268/108611 |
Garbacki, N., Di Valentin, E., Huynh-Thu, V. A., Geurts, P., Irrthum, A., Crahay, C., Arnould, T., Deroanne, C., Piette, J., Cataldo, D., & Colige, A. (2011). MicroRNAs Profiling in Murine Models of Acute and Chronic Asthma: A Relationship with mRNAs Targets. PLoS ONE. doi:10.1371/journal.pone.0016509 |
Huynh-Thu, V. A., Irrthum, A., Wehenkel, L., & Geurts, P. (28 September 2010). Inferring Regulatory Networks from Expression Data Using Tree-Based Methods. PLoS ONE, 5 (9), 12776. doi:10.1371/journal.pone.0012776 |
Huynh-Thu, V. A., Wehenkel, L., & Geurts, P. (2008). Exploiting tree-based variable importances to selectively identify relevant variables [Paper presentation]. Third Workshop on New Challenges for Feature Selection in Data Mining and Knowledge Discovery (FSDM 2008). |
Huynh-Thu, V. A., Wehenkel, L., & Geurts, P. (2008). Exploiting tree-based variable importances to selectively identify relevant variables. Proceedings of Machine Learning Research, 4, 60-73. |