1. Wang L, Michoel T. Wisdom of the crowd from unsupervised dimension reduction. arXiv.
  2. Erola P, Bonnet E, Michoel T. Learning differential module networks across multiple experimental conditions. arXiv.
  3. Wang L, Michoel T. Whole-transcriptome causal network inference with genomic and transcriptomic data. bioRxiv.
  4. Michoel T. Analytic solution and stationary phase approximation for the Bayesian lasso and elastic net. arXiv.
  5. Wang L, Michoel T. Comparable variable selection with Lasso. arXiv

[2 0 1 7]

  1. 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, van der Laan S, Biegert C, Hamby S, Talukdar H, Foroughi Asl H, Pasterkamp G, Watkins H, Samani N, Wittenberger T, Erdmann J, Schunkert H, Asselbergs F, Björkegren J. Network analysis of coronary artery disease risk genes elucidates disease mechanisms and druggable targets. Scientific Reports.
  2. 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, Kenyon C, Hadoke P, Odermatt A, Keen J, Walker B. Carbonyl reductase 1 catalyzes 20β-reduction of glucocorticoids, modulating receptor activation and metabolic complications of obesity. Scientific Reports.
  3. Loren Reyes P, Michoel T, Joshi A, Devailly G. Meta-analysis of liver and heart transcriptomic data for functional annotation transfer in mammalian orthologs. Computational and Structural Biotechnology Journal
  4. Wang L, Michoel T. Efficient and accurate causal inference with hidden confounders from genome-transcriptome variation data. PLOS Computational Biology. [PDF] Methods Article

[2 0 1 6]

  1. Wang L, Michoel T. Detection of regulator genes and eQTLs in gene networks. Systems Biology in Animal Production and Health, Vol. 1. [PDF]
  2. 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, Skogsberg J, Ruusalepp A, Schadt E, Björkegren J. Cardiometabolic risk loci share downstream cis- and trans-gene regulation across tissues and diseases. Science. NIH blog
  3. Schnappauf O, Beyes S, Dertmann A, Freihen V, Frey P, Jägle S, Rose K, Michoel T, Grosschedl R, Hecht A. Enhancer decommissioning by Snail1-induced competitive displacement of TCF7L2 and down-regulation of transcriptional activators results in EPHB2 silencing. Biochimica et Biophysica Acta – Gene Regulatory Mechanisms.
  4. Pasterkamp G, van der Laan S, Haitjema S, Foroughi Asl H, Siemelink M, Bezemer T, van Setten J, Dichgans M, Malik R, Worrall B, Schunkert H, Samani N, de Kleijn D, Markus H, Hoefer I, Michoel T, de Jager S, Björkegren J, den Ruijter H, Asselbergs F. Human Validation of Genes Associated With a Murine Atherosclerotic Phenotype. Arteriosclerosis, Thrombosis and Vascular Biology.
  5. 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*. Cross-tissue regulatory gene networks in coronary artery disease. Cell Systems. (* Shared last authors) [PDF] Editorial Preview ECCB2016 Highlight
  6. Banks C, Joshi A*, Michoel T*. Functional transcription factor target discovery via compendia of binding and expression profiles. Scientific Reports. (* Shared last authors) [PDF]
  7. Melckenbeeck I, Audenaert P, Michoel T, Colle D, Pickavet M. An algorithm to automatically generate the combinatorial orbit counting equations. PLOS One. [PDF]
  8. Renault K, Michoel T, Karavalos M, Clohisey S, Baillie K, Stevens M, Freeman T, Summers K, McColll B. Microglial region-dependent transcriptome diversity in the healthy adult brain reveals heterogeneity in immune vigilance and energy metabolism. Nature Neuroscience.
  9. Michoel T. Natural coordinate descent algorithm for L1-penalised regression in generalised linear models. Computational Statistics & Data Analysis. [PDF]
  10. [2 0 1 5]

  11. Devailly G, Mantsoki A, Michoel T, Joshi A. Variable reproducibility in genome-scale public data: A case study using ENCODE ChIP sequencing resource. FEBS Letters. [PDF]
  12. Auty H, Torr S, Michoel T, Jayaraman S, Morrison L. Cattle trypanosomosis: the diversity of trypanosomes and implications for disease epidemiology and control. Revue Scientifique et Technique de I’OIE.
  13. Eduati F, Mangravite L, …, The NIEHS-NCATS-UNC DREAM Toxicogenetics Collaboration,…, Saez-Rodriguez J. Prediction of human population responses to toxic compounds by a collaborative competition. Nature Biotechnology. (Demeyer S and Michoel T were part of the The NIEHS-NCATS-UNC DREAM Toxicogenetics Collaboration).
  14. 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. Transcription factor, promoter and enhancer utilisation in human myeloid cells. Journal of Leukocyte Biology. [PDF]
  15. van der Laan S, Foroughi Asl H, van den Borne P, van Setten J, van der Perk M, van de Weg S, Schoneveld A, de Kleijn D, Michoel T, Björkegren J, den Ruijter H, Asselbergs F, de Bakker P, Pasterkamp G. Variants in ALOX5, ALOX5AP and LTA4H are not associated with atherosclerotic plaque phenotypes: The Athero-Express Genomics Study. Atherosclerosis.
  16. 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, Michoel T*, Björkegren J*. Expression quantitative trait loci acting across multiple tissues are enriched in inherited risk of coronary artery disease. Circulation: Cardiovascular Genetics (* Shared last authors). [PDF]
  17. Joshi A, Beck Y, Michoel T. Multi-species network inference improves gene regulatory network reconstruction for early embryonic development in Drosophila. Journal of Computational Biology. [PDF] RECOMB-RSG Paper
  18. Bonnet E, Calzone L, Michoel T. Integrative multi-omics module network inference with Lemon-Tree. PLOS Computational Biology. [PDF] Software Article
  19. Rönsch K, Jägle S, Rose K, Seidl M, Baumgartner F, Freihen V, Yousaf A, Metzger E, Lassmann S, Schüle R, Zeiser R, Michoel T, Hecht A. SNAIL1 combines competitive displacement of ASCL2 and epigenetic mechanisms to rapidly silence the EPHB3 tumor suppressor in colorectal cancer. Molecular Oncology. [PDF]

[2 0 1 4]

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

[2 0 1 3]

  1. Bhosale R, Jewell J, Hollunder J, Koo A, Vuylsteke M, Michoel T, Hilson P, Goossens A, Howe G, Browse J, Maere S. Predicting gene function from uncontrolled expression variation among individual wild-type Arabidopsis plants. Plant Cell. [PDF]
  2. Demeyer S, Michoel T, Fostier J, Audenaert P, Pickavet M, Demeester P. The Index-Based Subgraph Matching Algorithm (ISMA): Fast subgraph enumeration in large networks using optimized search trees. PLoS One. [PDF]

[2 0 1 2]

  1. Michoel T, Nachtergaele B. Alignment and integration of complex networks by hypergraph-based spectral clustering. Physical Review E. [PDF]
  2. Qi J, Michoel T. Context-specific transcriptional regulatory network inference from global gene expression maps using double two-way t-tests. Bioinformatics. [PDF]
  3. Claeys M, Storms V, Sun H, Michoel T, Marchal K. MotifSuite: workflow for probabilistic motif detection and assessment. Bioinformatics. [PDF]
  4. Joshi A, Beck Y, Michoel T. Post-transcriptional regulatory networks play a key role in noise reduction that is conserved from micro-organisms to mammals. FEBS Journal. [PDF]
  5. Qi J, Michoel T, Butler G. An integrative approach to infer regulation programs in a transcription regulatory module network. Journal of Biomedicine and Biotechnology. [PDF]

[2 0 1 1]

  1. Joshi A, Van de Peer Y, Michoel T. Structural and functional organization of RNA regulons in the post-transcriptional regulatory network of yeast. Nucleic Acids Research. [PDF] Feature Article
  2. Michoel T, Joshi A, Nachtergaele B, Van de Peer Y. Enrichment and aggregation of topological motifs are independent organizational principles of integrated interaction networks. Molecular BioSystems. [PDF] Science News
  3. Audenaert P, Van Parys T, Brondel F, Pickavet M, Demeester P, Van de Peer Y, Michoel T. CyClus3D: a Cytoscape plugin for clustering network motifs in integrated networks. Bioinformatics. [PDF]
  4. Qi J, Michoel T, Butler G. Applying linear models to learn regulation programs in a transcription regulatory module network. Lecture Notes in Computer Science. [PDF]

[2 0 1 0]

  1. Bonnet E, Michoel T, Van de Peer Y. Prediction of a gene regulatory network linked to prostate cancer from gene expression, microRNA and clinical data. Bioinformatics. [PDF]
  2. Michoel T, Joshi A, Bonnet E, Vermeirssen V, Van de Peer Y. Towards system level modeling of functional modules and regulatory pathways using genome-scale data. Proceedings of the Seventh International Workshop on Computational Systems Biology. [PDF]
  3. Bonnet E, Tatari M, Joshi A, Michoel T, Marchal K, Berx G, Van de Peer Y. Module network inference from a cancer gene expression data set identifies microRNA regulated modules. PLoS One. [PDF]
  4. Joshi A, Van Parys T, Van de Peer Y, Michoel T. Characterizing regulatory path motifs in integrated networks using perturbational data. Genome Biology. [PDF]
  5. Qi J, Michoel T, Butler G. 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. [PDF]
  6. Michoel T, Mulherkar J, Nachtergaele B. Implementing quantum gates using the ferromagnetic spin-J XXZ chain with kink boundary conditions. New Journal of Physics. [PDF] IOP Select Article

[2 0 0 9]

  1. Vermeirssen V, Joshi A, Michoel T, Bonnet E, Casneuf T, Van de Peer Y. Transcription regulatory networks in Caenorhabditis elegans inferred through reverse-engineering of gene expression profiles constitute biological hypotheses for metazoan development. Molecular BioSystems. [PDF]
  2. Michoel T, De Smet R, Joshi A, Van de Peer Y, Marchal K. Comparative analysis of module-based versus direct methods for reverse-engineering transcriptional regulatory networks. BMC Systems Biology. [PDF] Highly accessed
  3. Joshi A, De Smet R, Marchal K, Van de Peer Y, Michoel T. Module networks revisited: computational assessment and prioritization of model predictions. Bioinformatics. [PDF] F1000
  4. Michoel T, De Smet R, Joshi A, Marchal K, Van de Peer Y. Reverse-engineering transcriptional modules from gene expression data. Annals of the New York Academy of Sciences. [PDF]

[2 0 0 8]

  1. Joshi A, Van de Peer Y, Michoel T. Analysis of a Gibbs sampler method for model based clustering of gene expression data. Bioinformatics. [PDF]
  2. Michoel T, Nachtergaele B, Spitzer W. Transport of interface states in the Heisenberg chain. Journal of Physics A: Mathematical and Theoretical. [PDF] FastTrack

[2 0 0 7]

  1. Michoel T, Maere S, Bonnet E, Joshi A, Saeys Y, Van den Bulcke T, Van Leemput K, van Remortel P, Kuiper M, Marchal K, Van de Peer Y. Validating module network learning algorithms using simulated data. BMC Bioinformatics. [PDF]

[2 0 0 6]

  1. Michoel T, Van de Peer Y. Helicoidal transfer matrix model for inhomogeneous DNA melting. Physical Review E. [PDF]

[2 0 0 5]

  1. Michoel T, Nachtergaele B. The large-spin asymptotics of the ferromagnetic XXZ chain. Markov Processes and Related Fields. [PDF]

[2 0 0 4]

  1. Michoel T, Nachtergaele B. Central limit theorems for the large-spin asymptotics of quantum spins. Probability Theory and Related Fields. [PDF]

[2 0 0 1]

  1. Michoel T, Verbeure A. Goldstone boson normal coordinates. Communications in Mathematical Physics. [PDF]
  2. Michoel T, Verbeure A. Interferencing in coupled Bose-Einstein condensates. Journal of Statistical Physics. [PDF]

[1 9 9 9]

  1. Michoel T, Verbeure A. Mathematical structure of magnons in quantum ferromagnets. Journal of Physics A. [PDF]
  2. Michoel T, Verbeure A. Goldstone boson normal coordinates in interacting Bose gases. Journal of Statistical Physics. [PDF]
  3. Michoel T, Verbeure A. Nonextensive Bose-Einstein condensation model. Journal of Mathematical Physics. [PDF]

[1 9 9 8]

  1. Michoel T, Momont B, Verbeure A. CCR-algebra structure of normal k-mode fluctuations. Reports in Mathematical Physics. [PDF]