• Loureiro, H., Carrasquinha, E., Alho, I., Ferreira, A., Costa, L., Carvalho, A.M.,  & Vinga S. (2019). Modelling cancer outcomes of bone metastatic patients : combining survival data with N-Telopeptide of Type I Collagen ( NTX ) dynamics through Joint Models.BMC Medical Informatics and Decision Making. (in press).


  • Lopes, M. B., Verissimo, A., Carrasquinha, E., Casimiro, S., Beerenwinkel, N., & Vinga, S. (2018). Ensemble outlier detection and gene selection in triple-negative breast cancer data. BMC Bioinformatics, 19. doi: 10.1186/s12859-018-2149-7
  • Carrasquinha, E., Verissimo, A., Lopes, M. B., & Vinga, S. (2018). Identification of influential observations in high-dimensional cancer survival data through the rank product test. Biodata Mining, 11. doi: 10.1186/s13040-018-0162-z
  • Costa, R.S. & Vinga S. (2018) Assessing Escherichia coli metabolism models and simulation approaches in phenotype predictions: validation against experimental data. Biotechnology Progress.
  • Segaert, P., Lopes, M. B., Casimiro, S., Vinga, S., & Rousseeuw, P. J. (2018). Robust identification of target genes and outliers in triple-negative breast cancer data. Stat Methods Med Res, 962280218794722. doi: 10.1177/0962280218794722
  • Miranda, R., Vinga S., & Valério, D. (2018) Studying Bone Remodelling and Tumour Growth for Therapy Predictive Control. Computers and Mathematics with Applications.
  • Neto, J. P., Coelho, R. M., Valério, D., Vinga, S., Sierociuk, D., Malesza, W., Macias, M., & Dzielinski, A. (2018). Simplifying biochemical tumorous bone remodeling models through variable order derivatives. Computers & Mathematics with Applications, 75(9), 3147-3157. doi: 10.1016/j.camwa.2018.01.037
  • Freitas, P. G., Elias, T. C., Pinto, I. A., Costa, L. T., Carvalho, P. V. S. D. D., Omote, D. D. Q.,,…,Silveira, N. J. F. (2018). Computational Approach to the Discovery of Phytochemical Molecules with Therapeutic Potential Targets to the PKCZ protein. Letters in Drug Design & Discovery, 15(5), 488-499. doi: 10.2174/1570180814666170810120150
  • Dudnik, A., Almeida, A. F., Andrade, R., Avila, B., Banados, P., Barbay, D., . . . Forster, J. (2018). BacHBerry: BACterial Hosts for production of Bioactive phenolics from bERRY fruits. Phytochemistry Reviews, 17(2), 291-326. doi: 10.1007/s11101-017-9532-2
  • Carvalho, S. M., Kloosterman, T. G., Manzoor, I., Caldas, J., Vinga, S., Martinussen, J., Saraiva, L. M. Kuipers, O. P., & Neves, A. P. (2018). Interplay Between Capsule Expression and Uracil Metabolism in Streptococcus pneumoniae D39. Frontiers in Microbiology, 9. doi: 10.3389/fmicb.2018.00321


  • Zielezinski, A., Vinga, S., Almeida, J., & Karlowski, W. M. (2017). Alignment-free sequence comparison: benefits, applications, and tools. Genome Biology, 18. doi: 10.1186/s13059-017-1319-7
  • Tomas, E., Vinga, S., & Carvalho, A. M. (2017). Unsupervised learning of pharmacokinetic responses. Computational Statistics, 32(2), 409-428. doi: 10.1007/s00180-016-0707-x
  • Neto, J. P., Coelho, R. M., Valerio, D., Vinga, S., Sierociuk, D., Malesza, W., Macias, M., & Dzielinski, A. (2017). Variable Order Differential Models of Bone Remodelling. Ifac Papersonline, 50(1), 8066-8071. doi: 10.1016/j.ifacol.2017.08.1233
  • Hartmann, A., Vila-Santa, A., Kallscheuer, N., Vogt, M., Julien-Laferriere, A., Sagot, M. F., . . . Vinga, S. (2017). OptPipe – a pipeline for optimizing metabolic engineering targets. BMC Systems Biology, 11. doi: 10.1186/s12918-017-0515-0


  • Veríssimo A., Oliveira A. L., Sagot, M.-F., & Vinga, S. (2016) DegreeCox: a network-based regularization method for survival analysis. BMC Bioinformatics, 17(16), 109-121. DOI: 10.1186/s12859-016-1310-4
  • Hartmann, A., Neves, A. R., Lemos, J. M., & Vinga, S. (2016). Identification and automatic segmentation of multiphasic cell growth using a linear hybrid model. Mathematical Biosciences, 279, 83-89. DOI: 10.1016/j.mbs.2016.06.013
  • Lemos, J. M., Caiado, D. V., Coelho, R., & Vinga, S. (2016). Optimal and receding horizon control of tumor growth in myeloma bone disease. Biomedical Signal Processing and Control, 24, 128-134. DOI: 10.1016/j.bspc.2015.10.004
  • Julien-Laferriere, A., Bulteau, L., Parrot, D., Marchetti-Spaccamela, A., Stougie, L., Vinga, S., Mary, A. & Sagot, M. F. (2016). A Combinatorial Algorithm for Microbial Consortia Synthetic Design. Scientific Reports, 6, 12. DOI: 10.1038/srep29182
  • Coelho RM, Lemos JM, Alho I, Valério D, Ferreira AR, Costa L, Vinga S (2016) Dynamic modeling of bone metastasis, microenvironment and therapy Integrating parathyroid hormone (PTH) effect, anti-resorptive and anti-cancer therapy. Journal of Theoretical Biology. Volume 391, 21 February 2016, Pages 1–12. DOI:10.1016/j.jtbi.2015.11.024
  • Fernandes, A., & Vinga, S. (2016). Improving Protein Expression Prediction Using Extra Features and Ensemble Averaging. PLoS One, 11(3), 15. DOI: 10.1371/journal.pone.0150369
  • Costa, R. S., & Vinga, S. (2016). Control analysis of the impact of allosteric regulation mechanism in a Escherichia coli kinetic model: Application to serine production. Biochemical Engineering Journal, 110, 59-70. DOI: 10.1016/j.bej.2016.01.013
  • Costa, R. S., Hartmann, A., & Vinga, S. (2016). Kinetic modeling of cell metabolism for microbial production. Journal of Biotechnology, 219, 126-141. DOI: 10.1016/j.jbiotec.2015.12.023


  • Paixão, L., Caldas, J., Kloosterman, T. G., Kuipers, O. P., Vinga, S., & Neves, A. R. (2015). Transcriptional and metabolic effects of glucose on Streptococcus pneumoniae sugar metabolism. Frontiers in Microbiology, 6. DOI: 10.3389/fmicb.2015.01041
  • Hartmann, A., Lemos, J.M., Costa, R.S., Xavier, J. and Vinga, S. (2015) Identification of Switched ARX Models via Convex Optimization and Expectation Maximization. Journal of Process Control. Volume 28, April 2015, Pages 9-16. DOI: 10.1016/j.jprocont.2015.02.003
  • Paixão, L., Oliveira, J., Veríssimo, A., Vinga, S., Lourenço, E.C., Ventura, M.R., Kjos, M., Veening, J-W., Fernandes, V.E., Andrew, P.W., Yesilkaya, H. and Neves, A.R. (2015) Host glycan sugar-specific pathways in Streptococcus pneumoniae: galactose as a key sugar in colonisation and infection. PLoS One. 2015; 10(3): e0121042. Published online 2015 Mar 31. DOI10.1371/journal.pone.0121042
  • Hartmann, A., Lemos, J.M., Vinga, S. (2015) Modeling multiple experiments using regularized optimization: a case study on bacterial glucose utilization dynamics. Computers in Biology and Medicine, 63, 301-309. DOI:10.1016/j.compbiomed.2014.08.027.