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  • Serras, J. L., Vinga, S., & Carvalho, A. M. (2021). Outlier detection for multivariate time series using dynamic Bayesian networks. Applied Sciences, 11(4). doi:10.3390/app11041955
  • Lopes, M. B., Martins, E. P., Vinga, S., & Costa, B. M. (2021). The role of network science in Glioblastoma. Cancers, 13(5). doi:10.3390/cancers13051045
  • Barata, C., Rodrigues, A. M., Canhão, H., Vinga, S., Carvalho, A. M. (2021). Predicting biologic therapy outcome of Patients With Spondyloarthritis: Joint models for longitudinal and survival analysis. JMIR Medical Informatics, 9(7):e26823. doi: 10.2196/26823
  • Neto, J. P., Alho, I., Costa, L., Casimiro, S., Valério, D., & Vinga, S. (2021). Dynamic modeling of bone remodeling, osteolytic metastasis and PK/PD therapy: Introducing variable order derivatives as a simplification technique. Journal of Mathematical Biology, 83(4):39. doi: 10.1007/s00285-021-01666-3
  • Jensch, A., Lopes, M. B., Vinga, S., & Radde, N. (2022). ROSIE: RObust Sparse ensemble for outlIEr detection and gene selection in cancer omics data. Statistical Methods in Medical Research. doi: 10.1177/09622802211072456
  • Ferrarini, M. G., Ziska, I., Andrade, R., Julien-Laferrière, A., Duchemin, L., César, R.M., Mary, A., Vinga, S., Sagot, M.-F. (2022). Totoro: Identifying active reactions during the transient state for metabolic perturbations. Frontiers in Genetics, 13:1-12. doi: 10.3389/fgene.2022.815476

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