Publications and preprints

2026

• Michoel, T. (2026). Fluctuation-dissipation relation in branching particle systems. arXiv.
• Bankier, S., Talukdar, H., Khan, M., Mocci, G., Sukhavasi, K., Hao, K., Ma, A., Ruusalepp, A., Schadt, E., Kovacic, J., Michoel, T., & Björkegren, J. (2026). Plasma proteins are integral to cross-tissue gene regulatory networks implicated in cardiometabolic disorders and coronary artery disease. Cell Systems.
• Mohammad, G., Björkegren, J., & Michoel, T. (2025). Mapping disease-regulatory flux through eQTL-based causal gene networks: A complex-trait framework applied to coronary artery disease. arXiv.
• Vandemoortele, B., Devlies, H., Michoel, T., Vanhaecke, L., Vandenbroucke, R. E., Laukens, D., & Vermeirssen, V. (2026). Lemonite: Identification of regulatory metabolites through data-driven, interpretable integration of transcriptomics and metabolomics data. bioRxiv.

2025

• Emilsson, V., Gudmundsdottir, V., Bankier, S., Frick, E. A., Jonmundsson, T., Arnarsson, K., Ingvarsdottir, H. K., Bjarnadottir, H., Loureiro, J., Jacobsen, E., Aspelund, T., Briem, E., Launer, L. K., Bastiaannet, E., Michoel, T., Haraldsdottir, S., Bodvarsdottir, S. K., Gudjonsson, T., Finkel, N., … Gudnasson, V. (2025). Mechanistic insights into tumorigenesis from serum proteins. medRxiv.
• Bankier, S., Gudmundsdottir, V., Jonmundsson, T., Bjarnadottir, H., Loureiro, J., Wang, L., Finkel, N., Orth, A. P., Aspelund, T., Launer, L. K., Björkegren, J. L., Jennings, L. L., Lamb, J. R., Gudnasson, V., Michoel, T., & Emilsson, V. (2025). Circulating causal protein networks linked to future risk of myocardial infarction. Nature Communications.

2024

• Mohammad, G., & Michoel, T. (2024). Predicting the genetic component of gene expression using gene regulatory networks. Bioinformatics Advances.
• Khan, M., Ludl, A., Bankier, S., Björkegren, J., & Michoel, T. (2024). Prediction of causal genes at GWAS loci with pleiotropic gene regulatory effects using sets of correlated instrumental variables. PLOS Genetics, 20, e1011473.
• Salami, D., Hasibi, R., Savazzi, S., Michoel, T., & Sigg, S. (2024). Angle-agnostic radio frequency sensing integrated into 5G-NR. IEEE Sensors Journal, 24, 36099–36114.
• Mocci, G., Sukhavasi, K., Örd, T., Bankier, S., Singha, P., Arasu, U. T., Agbabiaje, O. O., Mäkinen, P., Ma, L., Hodonsky, C. J., Aherrahrou, R., Muhl, L., Liu, J., Gustafsson, S., Byandelger, B., Wang, Y., Koplev, S., Lendahl, U., Owens, G. K., … Björkegren, J. L. (2024). Single-cell gene-regulatory networks of advanced symptomatic atherosclerosis. Circulation Research, 134(11), 1405–1423.
• Hasibi, R., Michoel, T., & Oyarzun, D. (2024). Integration of graph neural networks and genome-scale metabolic models for predicting gene essentiality. NPJ Systems Biology and Applications, 10, 24.

2023

• Malik, M., Faraone, S., Michoel, T., & Haavik, J. (2023). Use of big data and machine learning algorithms to extract possible treatment targets in neurodevelopmental disorders. Pharmacology & Therapeutics, 250, 108530.
• Michoel, T., & Zhang, J. (2023). Causal inference in drug discovery and development. Drug Discovery Today, 28(10), 103737.
• Bankier, S., Wang, L., Crawford, A., Morgan, R., Ruusalepp, A., Andrew, R., Björkegren, J., Walker, B., & Michoel, T. (2023). Plasma cortisol-linked gene networks in hepatic and adipose tissues implicate corticosteroid-binding globulin in modulating tissue glucocorticoid action and cardiovascular risk. Frontiers in Endocrinology, 14, 1186252.

2022

• Malik, M., Lundervold, A., & Michoel, T. (2022). rfPhen2Gen: A machine learning based association study of brain imaging phenotypes to genotypes. arXiv, 2204.00067.
• Malik, M., Ludl, A., & Michoel, T. (2022). High-dimensional multi-trait GWAS by reverse prediction of genotypes. Lecture Notes in Computer Science, 13483, 79–93.
• Salami, D., Hasibi, R., Palipana, S., Popovski, P., Michoel, T., & Sigg, S. (2021). Tesla-rapture: A lightweight gesture recognition system from mmWave radar point clouds. IEEE Transactions on Mobile Computing, 1–1.
• Bankier, S., & Michoel, T. (2022). eQTLs as causal instruments for the reconstruction of hormone linked gene networks. Frontiers in Endocrinology, 13, 949061.
• Koplev, S., Seldin, M., Sukhavasi, K., Ermel, R., Pang, S., Zeng, L., Bankier, S., Di Narzo, A., Cheng, H., Meda, V., Ma, A., Talukdar, H., Cohain, A., Amadori, L., Argmann, C., Houten, S., Franzén, O., Mocci, G., Meelu, O., … Björkegren, J. (2022). A mechanistic framework for cardiometabolic and coronary artery diseases. Nature Cardiovascular Research, 1, 85–100.
• Malik, M., & Michoel, T. (2022). Restricted maximum-likelihood method for learning latent variance components in gene expression data with known and unknown confounders. G3, 12, 410.

2021

• Hasibi, R., & Michoel, T. (2021). A graph feature auto-encoder for the prediction of unobserved node features on biological networks. BMC Bioinformatics, 22, 525.
• Kogelman, L., Falkenberg, K., Buil, A., Erola, P., Courraud, J., Laursen, S., Michoel, T., Olesen, J., & Hansen, T. (2021). Changes in the gene expression profile during spontaneous migraine attacks. Scientific Reports, 11, 8294.
• Crawford, A., Bankier S., Altmaier, E., Barnes, C., Clark, D., Ermel, R., Friedrich, N., Harst, P. van der, Joshi, P., Karhunen, V., Lahti, J., Mahajan, A., Mangino, M., Neumann, M. N. A., Pietzner, M., Sukhavasi, K., Wang, C., Bakker, S., Björkegren, J., … Walker, B. (2021). Variation in the SERPINA6/SERPINA1 locus alters morning plasma cortisol, hepatic corticosteroid binding globulin expression, gene expression in peripheral tissues, and risk of cardiovascular disease. Journal of Human Genetics, 66, 625–636.
• Ludl, A., & Michoel, T. (2021). Comparison between instrumental variable and mediation-based methods for reconstructing causal gene networks in yeast. Molecular Omics, 17, 241–251.

2020

• Erola, P., Björkegren, J., & Michoel, T. (2020). Model-based clustering of multi-tissue gene expression data. Bioinformatics, 36, 1807–1813.

2019

• Wang, L., Audenaert, P., & Michoel, T. (2019). High-dimensional bayesian network inference from systems genetics data using genetic node ordering. Frontiers in Genetics, Special Topic Machine Learning and Network-Driven Integrative Genomics, 10, 1196.
• Eales, J., Maan, A., Xu, X., Michoel, T., Hallast, P., Batini, C., Zadik, D., Prestes, P., Molina, E., Denniff, M., Schroeder, J., Björkegren, J., Thompson, J., Maffia, P., Guzik, T., Keavney, B., Jobling, M., Samani, N., Charchar, F., & Tomaszewski, M. (2019). The human Y chromosome exerts pleiotropic effects on susceptibility to atherosclerosis. Arteriosclerosis, Thrombosis, and Vascular Biology, 39, 2386–2401.
• Zeng, L., Talukdar, H., Koplev, S., Giannarelli, C., Ivert, T., Gan, L.-M., Ruusalepp, A., Schadt, E., Kovacic, J., Lusis, A., Michoel, T., Schunkert, H., & Björkegren, J. (2019). Contribution of gene regulatory networks to heritability of coronary artery disease. Journal of the American College of Cardiology, 73(23), 2946–2957.
• Wang, L., & Michoel, T. (2019). Accurate wisdom of the crowd from unsupervised dimension reduction. Royal Society Open Science, 6, 181806.
• Jayaraman, S., Harris, C., Paxton, E., Donachie, A., Vaikkinen, H., McCulloch, R., Hall, J. P. J., Kenny, J., Lenzi, L., Hertz-Fowler, C., Cobbold, C., Reeve, R., Michoel, T., & Morrison, L. (2019). Application of long read sequencing to determine expressed antigen diversity in trypanosoma brucei infections. PLOS Neglected Tropical Diseases, 13(4), e0007262.
• Erola, P., Bonnet, E., & Michoel, T. (2019). Learning differential module networks across multiple experimental conditions. In G. Sanguinetti & V. Huynh-Thu (Eds.), Gene regulatory networks (Vol. 1883, pp. 303–321). Humana Press.
• Wang, L., & Michoel, T. (2019). Whole-transcriptome causal network inference with genomic and transcriptomic data. In G. Sanguinetti & V. Huynh-Thu (Eds.), Gene regulatory networks (Vol. 1883, pp. 95–109). Humana Press.

2018

• Michoel, T. (2018). Analytic solution and stationary phase approximation for the Bayesian lasso and elastic net. Advances in Neural Information Processing Systems 31, 2770–2780.
• Vipin, D., Wang, L., Devailly, G., Michoel, T., & Joshi, A. (2018). Causal transcriptional regulatory network inference using enhancer activity as a causal anchor. International Journal of Molecular Sciences, 19, 3609.
• Siemelink, M., Laan, S. van der, Koeverden, I. van, Schaap, J., Wesseling, M., Jager, S. de, Mokry, M., Iterson, M. van, Dekkers, K., Luijk, R., Foroughi Asl, H., Michoel, T., Björkegren, J., Aavik, E., Ylä-Herttuala, S., Borst, G. de, Asselbergs, F., Azzouzi, H. el, Ruijter, H. den, … Pasterkamp, G. (2018). Smoking is associated to DNA methylation in atherosclerotic carotid lesions. Circulation: Genomic and Precision Medicine, 11, e002030.
• Lempiäinen, H., Braene, I., Michoel, T., Tragante, V., Vilne, B., Webb, T., Kyriakou, T., Eichner, J., Zeng, L., Willenborg, C., Franzen, O., Ruusalepp, A., Goel, A., Laan, S. van der, Biegert, C., Hamby, S., Talukdar, H., Foroughi Asl, H., Pasterkamp, G., … Björkegren, J. (2018). Network analysis of coronary artery disease risk genes elucidates disease mechanisms and druggable. Scientific Reports, 8, 3434.

2017

• Wang, L., & Michoel, T. (2017). Controlling false discoveries in bayesian gene networks with lasso regression p-values. arXiv, 1701.07011.
• Morgan, R., Beck, K., Nixon, M., Homer, N., Crawford, A., Melchers, D., Houtman, R., Meijer, O., Stomby, A., Anderson, A., Upreti, R., Stimson, R., Olsson, T., Michoel, T., Cohain, A., Ruusalepp, A., Schadt, E., Björkegren, J., Andrew, R., … Walker, B. (2017). Carbonyl reductase 1 catalyzes 20\(\beta\)-reduction of glucocorticoids, modulating receptor activation and metabolic complications of obesity. Scientific Reports, 7, 10633.
• Loren Reyes, P., Michoel, T., Joshi, A., & Devailly, G. (2017). Meta-analysis of liver and hear transcriptomic data for functional annotation transfer in mammalian orthologs. Computational and Structural Biotechnology Journal, 15, 425–432.
• Wang, L., & Michoel, T. (2017). Efficient and accurate causal inference with hidden confounders from genome-transcriptome variation data. PLOS Computational Biology, 13, e1005703.

2016

• Wang, L., & Michoel, T. (2016). Detection of regulator genes and eQTLs in gene networks (Vol. 1, pp. 1–23). Springer.
• Franzén, O., Ermel, R., Cohain, A., Akers, N., Di Narzo, A., Talukdar, H., Foroughi Asl, H., Giambartolomei, C., Fullard, J., Sukhavasi, K., Köks, S., Gan, L.-M., Giannarelli, C., Kovacic, J., Betsholtz, C., Losic, B., Michoel, T., Hao, K., Roussos, P., … Björkegren, J. (2016). Cardiometabolic risk loci share downstream cis-and trans-gene regulation across tissues and diseases. Science, 353, 827–830.
• Schnappauf, O., Beyes, S., Dertmann, A., Freihen, V., Frey, P., Jägle, S., Rose, K., Michoel, T., Grosschedl, R., & Hecht, A. (2016). Enhancer decommissioning by Snail1-induced competitive displacement of TCF7L2 and down-regulation of transcriptional activators results in EPHB2 silencing. Biochimica Et Biophysica Acta (BBA) – Gene Regulatory Mechanisms, 1859, 1353–1367.
• Pasterkamp, G., Laan, S. van der, Haitjema, S., Foroughi Asl, H., Siemelink, M., Bezemer, T., Setten, J. van, Dichgans, M., Malik, R., Worrall, B., Schunkert, H., N. Samani, and, Kleijn, P. de, Markus, H., Hoeferand, I., Michoel, T., Jager, S. de, Björkegren, J., Ruijter, H. den, & Asselbergs, F. (2016). Human validation of genes associated with a murine atherosclerotic phenotype. Arteriosclerosis, Thrombosis and Vascular Biology, 36, 1240–1246.
• Talukdar, H., Foroughi Asl, H., Jain, R., Ermel, R., Ruusalepp, A., Franzén, O., Kidd, B., Readhead, B., Giannarelli, C., Ivert, T., Dudley, J., Civelek, M., Lusis, A., Schadt, E., Skogsberg, J., Michoel, T., & Björkegren, J. (2016). Cross-tissue regulatory gene networks in coronary artery disease. Cell Systems, 2, 196–208.
• Banks, C., Joshi, A., & Michoel, T. (2016). Functional transcription factor target discovery via compendia of binding and expression profiles. Scientific Reports, 6, 20649.
• Renault, K., Michoel, T., Karavalos, M., Clohisey, S., Baillie, K., Stevens, M., Freeman, T., Summers, K., & McColll, B. (2016). Microglial region-dependent transcriptome diversity in the healthy adult brain reveals heterogeneity in immune vigilance and energy metabolism. Nature Neuroscience, 19, 504–516.
• Melckenbeeck, I., Audenaert, P., Michoel, T., Colle, D., & Pickavet, M. (2016). An algorithm to automatically generate the combinatorial orbit counting equations. PLOS One, 11, e0147078.
• Michoel, T. (2016). Natural coordinate descent algorithm for L1-penalised regression in generalised linear models. Computational Statistics & Data Analysis, 97, 60–70.

2015

• Devailly, G., Mantsoki, A., Michoel, T., & Joshi, A. (2015). Variable reproducibility in genome-scale public data: A case study using ENCODE ChIP sequencing resource. FEBS Letters, 589, 3866–3870.
• Auty, H., Torr, S. J., Michoel, T., Jayaraman, S., & Morrison, L. J. (2015). Cattle trypanosomosis: The diversity of trypanosomes and implications for disease epidemiology and control. Rev. Sci. Tech. Off. Int. Epiz., 34.
• Eduati, F., Mangravite, L. M., …, Demeyer, S., T Michoel, …and, J. Saez-Rodriguez, …and, & (as part of The NIEHS-NCATS-UNC DREAM Toxicogenetics Collaboration) (2015). Prediction of human population responses to toxic compounds by a collaborative competition. Nature Biotechnology.
• Joshi, A., Pooley, C., Freeman, T., Lennnartsson, A., Babina, M., Schmidt, C., Geijtenbeck, T., the FANTOM consortium, Michoel, T., Severin, J., Itoh, M., Lassman, T., Kawaji, H., Hayashizaki, Y., Carninci, P., Forrest, A., Rehli, M., & Hume, D. (2015). Transcription factor, promoter and enhancer utilisation in human myeloid cells. Journal of Leukocyte Biology, 97, 985–995.
• Laan, S. van der, Foroughi Asl, H., Borne, P. van den, Setten, J. van, Perk, M. van der, Weg, S. van de, Schoneveld, A., Kleijn, P. de, Michoel, T., Björkegren, J., Ruijter, H. den, Asselbergs, F., Bakker, P. de, & Pasterkamp, G. (2015). Variants in ALOX5, ALOX5AP and LTA4H are not associated with atherosclerotic plaque phenotypes: The Athero-Express Genomics Study. Atherosclerosis, 239, 528–538.
• Foroughi Asl, H., Talukdar, H., Kindt, A., Jain, R., Ermel, R., Ruusalepp, A., Nguyen, K.-D., Dobrin, R., Reilly, D., CARDIoGRAM Consortium, Schunkert, H., Samani, N., Braenne, I., Erdmann, J., Melander, O., Qi, J., Ivert, T., Skogsberg, J., Schadt, E., … Björkegren, J. (2015). Expression quantitative trait loci acting across multiple tissues are enriched in inherited risk of coronary artery disease. Circulation: Cardiovascular Genetics, 8, 305–315.
• Joshi, A., Beck, Y., & Michoel, T. (2015). Multi-species network inference improves gene regulatory network reconstruction for early embryonic development in Drosophila. Journal of Computational Biology, 22, 253–265.
• Bonnet, E., Calzone, L., & Michoel, T. (2015). Integrative multi-omics module network inference with Lemon-Tree. PLOS Computational Biology, 11, e1003983.
• Rönsch, K., Jägle, S., Bruser, K., Freihen, V., Yousaf, A., Metzger, E., Schüle, R., Michoel, T., & Hecht, A. (2015). SNAIL1 combines competitive displacement of a transcriptional activator and epigenetic mechanisms to rapidly silence the EPHB3 tumour suppressor in colorectal cancer. Molecular Oncology, 9, 335–354.

2014

• Demeyer, S., & Michoel, T. (2014). Graph-based data integration predicts long-range regulatory interactions across the human genome.
• Shang, M., Talukdar, H., Hofmann, J., Niaudet, C., Foroughi Asl, H., Jain, R., Rossignoli, A., Cedergren, C., Silveira, A., Gigante, B., Leander, K., Faire, U. de, Hamsten, A., Ruusalepp, A., Melander, O., Yvert, T., Michoel, T., Schadt, E., Betsholtz, C., … Björkegren, J. (2014). Lim domain binding 2 – a key driver of transendothelial migration of leukocytes and atherosclerosis. Arteriosclerosis, Thrombosis, and Vascular Biology, 34, 2068–2077.
• Houbraken, M., Demeyer, S., Michoel, T., Audenaert, P., Colle, D., & Pickavet, M. (2014). The Index-Based Subgraph Matching Algorithm with General Symmetries (ISMAGS): Exploiting symmetry for faster subgraph enumeration. PLoS One, 9, e97896.
• Jägle, S., Rönsch, K., Timme, S., Andrlovà, H., Bertrand, M., Jäger, M., Proske, A., Schrempp, M., Yousaf, A., Michoel, T., Zeiser, R., Werner, M., Lassman, S., & Hecht, A. (2014). Silencing of the EPHB3 tumor suppressor gene in human colorectal cancer through decommissioning of a transcriptional enhancer. Proceedings of the National Academy of Sciences, 111, 4886–4891.
• Björkegren, J., Hägg, S., Talukdar, H., Foroughi Asl, H., Jain, R., Cedergren, C., Shang, M., Maleki, S., Takolander, R., Melander, O., Hamsten, A., Michoel, T., & Skogsberg, J. (2014). Plasma cholesterol-induced lesion networks activated before regression of early, mature and advanced atherosclerosis. PLoS Genetics, 10, e1004201.
• Qi, J., Foroughi Asl, H., Björkegren, J., & Michoel, T. (2014). kruX: Matrix-based non-parametric eQTL discovery. BMC Bioinformatics, 15, 11.

2013

• Bhosale, R., Jewell, J., Hollunder, J., Koo, A., Vuylsteke, M., Michoel, T., Hilson, P., Goossens, A., Howe, G., Browse, J., & Maere, S. (2013). Predicting gene function from uncontrolled expression variation among individual wild-type arabidopsis plants. Plant Cell, 25, 2865.
• Demeyer, S., Michoel, T., Fostier, J., Audenaert, P., Pickavet, M., & Demeester, P. (2013). The Index-based Subgraph Matching Algorithm (ISMA): Fast subgraph enumeration in large networks using optimized search trees. PLoS One, 8, e61183.

2012

• Michoel, T., & Nachtergaele, B. (2012). Alignment and integration of complex networks by hypergraph-based spectral clustering. Physical Review E, 86, 056111.
• Qi, J., & Michoel, T. (2012). Context-specific transcriptional regulatory network inference from global gene expression maps using double two-way \(t\)-tests. Bioinformatics, 28, 2325–2332.
• Claeys, M., Storms, V., Sun, H., Michoel, T., & Marchal, K. (2012). MotifSuite: Workflow for regulatory motif detection with various motif assessment tools. Bioinformatics, 28, 1931–1932.
• Joshi, A., Beck, Y., & Michoel, T. (2012). Post-transcriptional regulatory networks play a key role in noise reduction which is conserved from micro-organisms to mammals. FEBS Journal, 279, 3501–3512.
• Qi, J., Michoel, T., & Butler, G. (2012). An integrative approach to infer regulation programs in a transcription regulatory module network. Journal of Biomedicine and Biotechnology, 2012, 245968.

2011

• Michoel, T., Joshi, A., Nachtergaele, B., & Van de Peer, Y. (2011). Enrichment and aggregation of topological motifs are independent organizational principles of integrated interaction networks. Molecular BioSystems, 7, 2769–2778.
• Joshi, A., Van de Peer, Y., & Michoel, T. (2011). Structural and functional organization of RNA regulons in the posttranscriptional regulatory network of yeast. Nucleic Acids Research, 39, 9108–9117.
• Audenaert, P., Van Parys, T., Brondel, F., Pickavet, M., Demeester, P., Van de Peer, Y., & Michoel, T. (2011). CyClus3D: A Cytoscape plugin for clustering network motifs in integrated networks. Bioinformatics, 27, 1587–1588.
• Qi, J., Michoel, T., & Butler, G. (2011). Applying linear models to learn regulation programs in a transcription regulatory module network. Lecture Notes in Computer Science, 6623/2011, 37–47.

2010

• Bonnet, E., Michoel, T., & Van de Peer, Y. (2010). Prediction of a gene regulatory network linked to prostate cancer from gene expression, microRNA and clinical data. Bioinformatics, 26, i683–i644.
• Michoel, T., Joshi, A., Bonnet, E., Vermeirssen, V., & Van de Peer, Y. (2010). Towards system level modeling of functional modules and regulatory pathways using genome-scale data. Proceedings of the Seventh International Workshop on Computational Systems Biology.
• Qi, J., Michoel, T., & Butler, G. (2010). A regression tree-based Gibbs sampler to learn the regulation programs in a transcription regulatory module network. Proceedings of the 2010 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB).
• Bonnet, E., Tatari, M., Joshi, A., Michoel, T., Marchal, K., Berx, G., & Van de Peer, Y. (2010). Module network inference from a cancer gene expression data set identifies microRNA regulated modules. PLoS One, 5, e10162.
• Joshi, A., Van Parys, T., Van de Peer, Y., & Michoel, T. (2010). Characterizing regulatory path motifs in integrated networks using perturbational data. Genome Biology, 11, R32.

2009

• Michoel, T., Mulherkar, J., & Nachtergaele, B. (2010). Implementing quantum gates using the ferromagnetic spin-J XXZ chain with kink boundary conditions. New Journal of Physics, 12, 025003.
• Vermeirssen, V., Joshi, A., Michoel, T., Bonnet, E., Casneuf, T., & Van de Peer, Y. (2009). Transcription regulatory networks in caenorhabditis elegans inferred through reverse-engineering of gene expression profiles constitute biological hypotheses for metazoan development. Molecular BioSystems, 5, 1817–1830.
• Michoel, T., De Smet, R., Joshi, A., Van de Peer, Y., & Marchal, K. (2009). Comparative analysis of module-based versus direct methods for reverse-engineering transcriptional regulatory networks. BMC Systems Biology, 3, 49.
• Michoel, T., De Smet, R., Joshi, A., Marchal, K., & Van de Peer, Y. (2009). Reverse-engineering transcriptional modules from gene expression data. Annals of the New York Academy of Sciences, 1158, 36–43.
• Joshi, A., De Smet, R., Marchal, K., Van de Peer, Y., & Michoel, T. (2009). Module networks revisited: Computational assessment and prioritization of model predictions. Bioinformatics, 25, 490–496.

2008

• Joshi, A., Van de Peer, Y., & Michoel, T. (2008). Analysis of a Gibbs sampler method for model based clustering of gene expression data. Bioinformatics, 24, 176–183.
• Michoel, T., Nachtergaele, B., & Spitzer, W. (2008). Transport of one-dimensional interfaces in the Heisenberg model. Journal of Physics A: Mathematical and Theoretical, 41, 492001.

2007

• Michoel, T., Maere, S., Bonnet, E., Joshi, A., Saeys, Y., Van den Bulcke, T., Van Leemput, K., Remortel, P. van, Kuiper, M., Marchal, K., & Van de Peer, Y. (2007). Validating module networks learning algorithms using simulated data. BMC Bioinformatics, 8, S5.

2006

• Michoel, T., & Van de Peer, Y. (2006). Helicoidal transfer matrix model for inhomogeneous DNA melting. Physical Review E, 73, 011908.

2005

• Michoel, T., & Nachtergaele, B. (2005). The large-spin asymptotics of the ferromagnetic XXZ chain. Markov Processes and Related Fields, 11, 237–266.

2004

• Michoel, T., & Nachtergaele, B. (2004). Central limit theorems for the large-spin asymptotics of quantum spins. Probability Theory and Related Fields, 130, 493–517.

2001

• Michoel, T., & Verbeure, A. (2001). Goldstone boson normal coordinates. Communications in Mathematical Physics, 216, 461–490.
• Michoel, T., & Verbeure, A. (2001). Interferencing in coupled Bose-Einstein condensates. Journal of Statistical Physics, 102, 1383–1405.

1999

• Michoel, T., & Verbeure, A. (1999). Mathematical structure of magnons in quantum ferromagnets. Journal of Physics A: Mathematical and General, 32, 5875–5883.
• Michoel, T., & Verbeure, A. (1999). Goldstone boson normal coordinates in interacting Bose gases. Journal of Statistical Physics, 96, 1125–1162.
• Michoel, T., & Verbeure, A. (1999). Nonextensive Bose-Einstein condensation model. Journal of Mathematical Physics, 40, 1268–1279.

1998

• Michoel, T., Momont, B., & Verbeure, A. (1998). CCR-algebra structure of normal k-mode fluctuations. Reports on Mathematical Physics, 41, 361–395.