Articles dans des revues avec comité de lecture (31)
  1. 1. Raimondi, D., Orlando, G., Pancsa, R., Khanna, T., & Vranken, W. (2017). Exploring the Sequence-based Prediction of Folding Initiation Sites in Proteins. Scientific reports, 7(1), 8826. doi:10.1038/s41598-017-08366-3
  2. 2. Rastogi, R., Chung, R., Li, S., Li, C., Lee, K., Woo, J., Kim, D. W., Keum, C., Babbi, G., Martelli, P. L., Savojardo, C., Casadio, R. R., Chennen, K., Weber, T. S., Poch, O., Ancien, F., Camperio Ciani, G., Pucci, F., Raimondi, D., Vranken, W., Rooman, M., Marquet, C., Olenyi, T., Rost, B., Andreoletti, G., Kamandula, A., Peng, Y., Bakolitsa, C., Mort, M., Cooper, D. N., Bergquist, T., Pejaver, V., Liu, X., Radivojac, P., Brenner, S. E., & Ioannidis, N. M. (2025). Critical assessment of missense variant effect predictors on disease-relevant variant data. Human genetics, 144(2-3), 281-293. doi:10.1007/s00439-025-02732-2
  3. 3. Van Scharen, A., Cruyt, K., Colon, J., De Sutter, S., Duerinck, J., Forsyth, R., Olsen, C., Quinn, P., Tzavella, K., Van Dooren, S., Waelput, W., Witdouck, A., Cornu, P., Vandemeulebroucke, J., & Vranken, W. (2025). Unlocking Health Data for Research: Legal, Technical, and Organisational Lessons from a Belgian Interdisciplinary Case Study. Journal of Healthcare Informatics Research. doi:10.1007/s41666-025-00220-w
  4. 4. Crauwels, C., Heidig, S.-L., Díaz, A., & Vranken, W. (2024). Large-scale structure-informed multiple sequence alignment of proteins with SIMSApiper. Bioinformatics, 40(5), btae276. doi:10.1093/bioinformatics/btae276
  5. 5. Kagami, L. P., Roca-Martínez, J., Gavaldá-García, J., Ramasamy, P., Feenstra, K. A., & Vranken, W. (2021). Online biophysical predictions for SARS-CoV-2 proteins. BMC Molecular and Cell Biology, 22(1), 23. doi:10.1186/s12860-021-00362-w
  6. 6. Kagami, L. P., Orlando, G., Raimondi, D., Ancien, F., Dixit, B., Gavaldá-García, J., Ramasamy, P., Roca-Martínez, J., Tzavella, K., & Vranken, W. (2021). B2bTools: Online predictions for protein biophysical features and their conservation. Nucleic acids research, 49(W1), W52-W59. doi:10.1093/nar/gkab425
  7. 7. Piovesan, D., Necci, M., Escobedo, N., Monzon, A. M., Hatos, A., Mičetić, I., Quaglia, F., Paladin, L., Ramasamy, P., Dosztányi, Z., Vranken, W., Davey, N. N., Parisi, G., Fuxreiter, M., & Tosatto, S. S. (2021). MobiDB: Intrinsically disordered proteins in 2021. Nucleic acids research, 49(D1), D361-D367. doi:10.1093/nar/gkaa1058
  8. 8. Orlando, G., Raimondi, D., Kagami, L. P., & Vranken, W. (2020). ShiftCrypt: a web server to understand and biophysically align proteins through their NMR chemical shift values. Nucleic acids research, 48(W1), W36-W40. doi:10.1093/nar/gkaa391
  9. 9. Raimondi, D., Orlando, G., Vranken, W., & Moreau, Y. (2019). Exploring the limitations of biophysical propensity scales coupled with machine learning for protein sequence analysis. Scientific reports, 9(1), 16932. doi:10.1038/s41598-019-53324-w
  10. 10. Loos, M. M., Ramakrishnan, R., Vranken, W., Tsirigotaki, A., Tsare, E. P., Zorzini, V., De Geyter, J., Yuan, B., Tsamardinos, I., Klappa, M., Schymkowitz, J. J., Rousseau, F., Karamanou, S., & Economou, A. (2019). Structural basis of the subcellular topology landscape of Escherichia coli. Frontiers in microbiology, 10, 1670, 1-22. doi:10.3389/fmicb.2019.01670
  11. 11. Brysbaert, G., Lorgouilloux, K., Vranken, W., & Lensink, M. (2018). RINspector: A Cytoscape app for centrality analyses and DynaMine flexibility prediction. Bioinformatics, 34(2), 294-296. doi:10.1093/bioinformatics/btx586
  12. 12. Piovesan, D., Monzon, A. M., Parisi, G., Schad, E., Sormanni, P., Tompa, P., Vendruscolo, M., Vranken, W., Tosatto, S. S., Tabaro, F., Paladin, L., Necci, M., Mieti, I., Camilloni, C., Davey, N. N., Dosztányi, Z., & Mészáros, B. (2018). MobiDB 3.0: More annotations for intrinsic disorder, conformational diversity and interactions in proteins. Nucleic acids research, 46(D1), D471-D476. doi:10.1093/nar/gkx1071
    13. << Précédent 1 2 3 4 Suivant >>