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BioMathematics and BioInformatics

Organisational unit: Research Line

1 - 50 out of 162Page size: 50
  1. 2019
  2. Published
    Jiang, J., Pieterman, C. D., Ertaylan, G., Peeters, R. L. M., & de Kok, T. M. C. M. (2019). The application of omics-based human liver platforms for investigating the mechanism of drug-induced hepatotoxicity in vitro. Archives of Toxicology. https://doi.org/10.1007/s00204-019-02585-5
  3. Published
    O'Donovan, S. D., Lenz, M., Vink, R. G., Roumans, N. J. T., de Kok, T. M. C. M., Mariman, E. C. M., ... Arts, I. C. W. (2019). A computational model of postprandial adipose tissue lipid metabolism derived using human arteriovenous stable isotope tracer data. PLoS Computational Biology, 15(10), [e1007400]. https://doi.org/10.1371/journal.pcbi.1007400
  4. Published
    Slavchev, B., Masliankova, E., & Kelk, S. (2019). A Machine Learning Approach to Algorithm Selection for Exact Computation of Treewidth. Algorithms, 12(10), [200]. https://doi.org/10.3390/a12100200
  5. Published
    Van Iersel, L., Jones, M., & Kelk, S. (2019). A Third Strike Against Perfect Phylogeny. Systematic Biology, 68(5), 814-827. https://doi.org/10.1093/sysbio/syz009
  6. Published
    Jin, H., Goossens, P., Karel, J., Daemen, M., Sluimer, J., & Biessen, E. (2019). Integrative Multi-Omics Analysis Of Human Atherosclerosis Reveals An Intraplaque Bleeding Associated Network, Which Offers Better Prediction Of Disease Stage. Atherosclerosis, 287, e63-e63. [EAS19-0625]. https://doi.org/10.1016/j.atherosclerosis.2019.06.180
  7. Published
    Bonizzi, P., Peeters, R., Zeemering, S., van Hunnik, A., Meste, O., & Karel, J. (2019). Detection of Spatio-Temporal Recurrent Patterns in Dynamical Systems. Frontiers in Applied Mathematics and Statistics, 5(36). https://doi.org/10.3389/fams.2019.00036
  8. Published
    Karimian, M., Dibenedetto, D., Moerel, M., Burwick, T., Westra, R. L., De Weerd, P., & Senden, M. (2019). Effects of synaptic and myelin plasticity on learning in a network of Kuramoto phase oscillators. Chaos, 29(8), [083122]. https://doi.org/10.1063/1.5092786
  9. Published
    O'Donovan, S. D., Lenz, M., Goossens, G. H., van der Kallen, C. J. H., Eussen, S. J. M. P., Stehouwer, C. D. A., ... Arts, I. C. W. (2019). Improved quantification of muscle insulin sensitivity using oral glucose tolerance test data: the MISI Calculator. Scientific Reports, 9, [9388]. https://doi.org/10.1038/s41598-019-45858-w
  10. Published
    Cluitmans, M. J. M., Stoks, J., & Volders, P. G. A. (2019). To the Editor-Interpretation of electrograms is key to understand the clinical potential of ECGI. Heart Rhythm, 16(6), E51-E52. https://doi.org/10.1016/j.hrthm.2019.02.030
  11. Published
    Browne, C., Soemers, D., Piette, E., Stephenson, M., Conrad, M., Crist III, W., ... Winands, M. (2019). Foundations of Digital Archæoludology.
  12. Published
    Döcker, J., Van Iersel, L., Kelk, S., & Linz, S. (2019). Deciding the existence of a cherry-picking sequence is hard on two trees. Discrete Applied Mathematics, 260, 131-143. https://doi.org/10.1016/j.dam.2019.01.031
  13. Published
    Kelk, S., & Stamoulis, G. (2019). Integrality gaps for colorful matchings. Discrete Optimization, 32, 73-92. https://doi.org/10.1016/j.disopt.2018.12.003
  14. Published
    Nguyen, U. C., Cluitmans, M. J. M., Strik, M., Luermans, J. G., Gommers, S., Wildberger, J. E., ... Vernooy, K. (2019). Integration of cardiac magnetic resonance imaging, electrocardiographic imaging, and coronary venous computed tomography angiography for guidance of left ventricular lead positioning. EP Europace, 21(4), 626-635. https://doi.org/10.1093/europace/euy292
  15. Published
    Davarzani, N., Golparvar, L., & Parsian, A. (2019). Inference on Marshall-Olkin Bivariate Exponential in the Presence of Dependent Left Censoring. Journal of Statistical Theory and Practice, 13(1), [21]. https://doi.org/10.1007/542519-018-0003-x
  16. Published
    Kelk, S., Pardi, F., Scornavacca, C., & Van Iersel, L. (2019). Finding a most parsimonious or likely tree in a network with respect to an alignment. Journal of Mathematical Biology, 78(1-2), 527-547. https://doi.org/10.1007/s00285-018-1282-2
  17. Published
    Kelk, S., & Linz, S. (2019). A Tight Kernel for Computing the Tree Bisection and Reconnection Distance between Two Phylogenetic Trees. Siam Journal on Discrete Mathematics, 33(3), 1556-1574. https://doi.org/10.1137/18M122724X
  18. Published
    Janssen, R., Jones, M., Kelk, S., Stamoulis, G., & Wu, T. (2019). Treewidth of display graphs: bounds, brambles and applications. Journal of Graph Algorithms and Applications, 23(4), 715-743. https://doi.org/10.7155/jgaa.00508
  19. 2018
  20. Published
    van Daalen, F., Smirnov, E., Davarzani, N., Peeters, R., Karel, J., & Brunner-La Rocca, H. (2018). An Ensemble Approach to Time Dependent Classification. In 17th IEEE International Conference on Machine Learning and Applications IEEE. https://doi.org/10.1109/ICMLA.2018.00164
  21. Published
    Nguyen, U. C., Cluitmans, M. J. M., Prinzen, F. W., Mihl, C., & Vernooy, K. (2018). Reply to the letter from Bhagirath etal. Imaging for cardiac resynchronisation therapy requires cardiac magnetic resonance. Netherlands Heart Journal, 26(12), 641-642. https://doi.org/10.1007/s12471-018-1196-z
  22. Published
    Briassouli, A. (2018). Unknown Crowd Event Detection from Phase-Based Statistics. In AVSS 2018: 15th IEEE International Conference on Advanced Video and Signal-based Surveillance
  23. Published
    Van Iersel, L., Kelk, S., Stamoulis, G., Stougie, L., & Boes, O. (2018). On Unrooted and Root-Uncertain Variants of Several Well-Known Phylogenetic Network Problems. Algorithmica, 80(11), 2993-3022. https://doi.org/10.1007/s00453-017-0366-5
  24. Published
    Cluitmans, M., Karel, J., Bonizzi, P., Volders, P., Westra, R., & Peeters, R. (2018). Wavelet-promoted sparsity for non-invasive reconstruction of electrical activity of the heart. Medical & Biological Engineering & Computing, 56(11), 2039-2050. https://doi.org/10.1007/s11517-018-1831-2
  25. E-pub ahead of print
    Ismailoglu, F., Cavill, R., Smirnov, E., Zhou, S., Collins, P., & Peeters, R. (2018). Heterogeneous Domain Adaptation for IHC Classification of Breast Cancer Subtypes. IEEE/ACM Transactions on Computational Biology and Bioinformatics. https://doi.org/10.1109/TCBB.2018.2877755
  26. Published
    Nairn, D., Bonizzi, P., Karel, J., & Aranda Hernandez, A. R. (2018). Performance Analysis of T-Wave-Offset Detection Algorithms on Patients With Cardiac Diseases. In Computing in Cardiology
  27. Published
    Aranda Hernandez, A. R., Bonizzi, P., Karel, J., & Peeters, R. (2018). Twelve Dimensional Vectorcardiography. Is More Better? In Computing in Cardiology
  28. Published
    Cluitmans, M., Brooks, D. H., MacLeod, R., Dossel, O., Guillem, M. S., van Dam, P. M., ... Bear, L. (2018). Validation and Opportunities of Electrocardiographic Imaging: From Technical Achievements to Clinical Applications. Frontiers in physiology, 9, [1305]. https://doi.org/10.3389/fphys.2018.01305
  29. Published
    Nguyen, U. C., Cluitmans, M. J. M., Luermans, J. G. L. M., Strik, M., de Vos, C. B., Kietselaer, B. L. J. H., ... Vernooy, K. (2018). Visualisation of coronary venous anatomy by computed tomography angiography prior to cardiac resynchronisation therapy implantation. Netherlands Heart Journal, 26(9), 433-440. https://doi.org/10.1007/s12471-018-1132-2
  30. Published
    Clerx, M., Heijman, J., Collins, P., & Volders, P. G. A. (2018). Predicting changes to I-Na from missense mutations in human SCN5A. Scientific Reports, 8(1), [12797]. https://doi.org/10.1038/s41598-018-30577-5
  31. Published
    Karel, J., & Peeters, R. (2018). Orthogonal Matched Wavelets with Vanishing Moments: A Sparsity Design Approach. Circuits Systems and Signal Processing, 37(8), 3487-3514. https://doi.org/10.1007/s00034-017-0716-1
  32. Published
    Zeemering, S., Lankveld, T. A. R., Bonizzi, P., Limantoro, I., Bekkers, S. C. A. M., Crijns, H. J. G. M., & Schotten, U. (2018). The electrocardiogram as a predictor of successful pharmacological cardioversion and progression of atrial fibrillation. EP Europace, 20(7), E96-E104. https://doi.org/10.1093/europace/eux234
  33. Published
    Aranda Hernandez, A., Bonizzi, P., Karel, J., & Peeters, R. (2018). Myocardial Ischemia Diagnosis Using a Reduced Lead System. In IEEE Engineering in Medicine and Biology Society. 2018 (pp. 5302-5305) https://doi.org/10.1109/EMBC.2018.8513511
  34. Published
    Kelk, S., Stamoulis, G., & Wu, T. (2018). Treewidth distance on phylogenetic trees. Theoretical Computer Science, 731, 99-117. https://doi.org/10.1016/j.tcs.2018.04.004
  35. Published
    Goblet, A., Kelk, S., Mihalák, M., & Stamoulis, G. (2018). On a Fixed Haplotype Variant of the Minimum Error Correction Problem. In L. Wang, & D. Zhu (Eds.), Computing and Combinatorics. COCOON 2018 (pp. 554-566). (Lecture Notes in Computer Science; Vol. 10976). Springer Verlag. https://doi.org/10.1007/978-3-319-94776-1_46
  36. Published
    Ismailoglu, F., Smirnov, E., Peeters, R., Zhou, S., & Collins, P. (2018). Heterogeneous Domain Adaptation Based on Class Decomposition Schemes. In D. Phung, V. Tseng, G. Webb, B. Ho, M. Ganji, & L. Rashidi (Eds.), Advances in Knowledge Discovery and Data Mining: PAKDD 2018 (pp. 169-182). (Lecture Notes in Computer Science; Vol. 10937). Cham: Springer. https://doi.org/10.1007/978-3-319-93034-3_14
  37. Published
    Giannakeris, P., Kaltsa, V., Avgerinakis, K., Briassouli, A., Vrochidis, S., & Kompatsiaris, I. (2018). Speed Estimation and Abnormality Detection From Surveillance Cameras. In CVPR AIC 2018 - Computer Vision and Pattern Recognition Workshop NVIDIA AI City Challenge
  38. Published
    Davarzani, N., Sanders-van Wijk, S., Maeder, M. T., Rickenbacher, P., Smirnov, E., Karel, J., ... Brunner-La Rocca, H. (2018). Novel concept to guide systolic heart failure medication by repeated biomarker testing—results from TIME-CHF in context of predictive, preventive, and personalized medicine. The EPMA Journal, 9(2), 161-173. https://doi.org/10.1007/s13167-018-0137-7
  39. Published
    Davarzani, N., Hutchins, G. G. A., West, N. P., Hewitt, L. C., Nankivell, M., Cunningham, D., ... Grabsch, H. I. (2018). Prognostic value of pathological lymph node status and primary tumour regression grading following neoadjuvant chemotherapy - results from the MRC OE02 oesophageal cancer trial. Histopathology, 72(7), 1180-1188. https://doi.org/10.1111/his.13491
  40. Published
    Davarzani, N. (2018). Biomarker discovery in heart failure. Maastricht: Maastricht University. https://doi.org/10.26481/dis.20180702nd
  41. Published
    Zhou, S., Smirnov, E., Schoenmakers, G., Peeters, R., & Jiang, T. (2018). Conformal feature-selection wrappers for instance transfer. In Proceedings of the 7th Symposium on Conformal and Probabilistic Prediction and Applications, COPA 2018, 11-13 June 2018, Maastricht, The Netherlands. (Vol. 91, pp. 96-113). Proceedings of Machine Learning Research.
  42. Published
    Gammerman, A., Vovk, V., Luo, Z., Smirnov, E., & Peeters, R. (Eds.) (2018). Proceedings of the 7th Symposium on Conformal and Probabilistic Prediction and Applications, COPA 2018, 11-13 June 2018, Maastricht, The Netherlands. Proceedings of Machine Learning Research.
  43. 2017
  44. Published
    Kelk, S., & Fischer, M. (2017). On the Complexity of Computing MP Distance Between Binary Phylogenetic Trees. Annals of Combinatorics, 21(4), 573-604. https://doi.org/10.1007/s00026-017-0361-1
  45. Published
    Zhou, S., Smirnov, E., Schoenmakers, G., & Peeters, R. (2017). Conformity-Based Source Subset Selection for Instance Transfer. Neurocomputing, 258, 41-51. https://doi.org/10.1016/j.neucom.2016.11.071
  46. Published
    Zhou, S., Smirnov, E., Schoenmakers, G., & Peeters, R. (2017). Conformal Decision-tree Approach to Instance Transfer. Annals of Mathematics and Artificial Intelligence, 81(1-2), 85-104. https://doi.org/10.1007/s10472-017-9554-x
  47. Published
    Bonizzi, P., Driessens, K., & Karel, J. (2017). Detection of Atrial Fibrillation Episodes from short single lead recordings by means of ensemble learning. In Computing in Cardiology Rennes, France.
  48. Published
    Bonizzi, P., Zeemering, S., Karel, J., azman, M. H., Lankveld, T. A. R., Schotten, U., ... Meste, O. (2017). Noninvasive Characterisation of Short-and Long-Term Recurrence of Atrial Signals During Persistent Atrial Fibrillation. In Computing in Cardiology Rennes, France.
  49. Published
    Slaney, H. L., Hewitt, L. C., Silva, A., Wickstone, C., Davarzani, N., Quirke, P., ... Grabsch, H. I. (2017). Comparing Gene Copy Number Status of Receptor Tyrosine Kinase and Downstream Signalling Genes Between Oesophageal and Gastric Cancer. Journal of Pathology, 243, S30-S30.
  50. Published
    Davarzani, N., Hale, M. D., Jolani, S., Hewitt, L. C., Fazzi, G., Hutchins, G. A., & Grabsch, H. I. (2017). Optimising the Sampling Strategy to Determine the Tumour Proportion in the Diagnostic Endoscopic Biopsy in Oesophageal Cancer. Journal of Pathology, 243, S29-S29.
  51. Published
    Karimian, M., Dibenedetto, M., Moerel, M., De Weerd, P., Burwick, T., & Westra, R. (2017). Effects of Hebbian learning on networks of Kuramoto phase oscillators with time delay. In BMC Neurosci 2017, 18(Suppl 1):60 (Vol. 18, pp. 164-165). BioMed Central. https://doi.org/10.1186/s12868-017-0372-1
  52. Published
    Cluitmans, M. J. M., Clerx, M., Vandersickel, N., Peeters, R. L. M., Volders, P. G. A., & Westra, R. L. (2017). Physiology-based regularization of the electrocardiographic inverse problem. Medical & Biological Engineering & Computing, 55(8), 1353-1365. https://doi.org/10.1007/s11517-016-1595-5
  53. Published
    Mes, J., Stienstra, E., You, X., Kumar, S., Zjajo, A., Galuzzi, C., & van Leuken, R. (2017). Neuromorphic Self-Organizing Map Design for Classification of Bioelectric-Timescale Signals. 113. Paper presented at International Conference on Systems, Architectures, MOdeling and Simulation, Greece.
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