| Physical and molecular bases of protein thermal stability and cold adaptation F Pucci, M Rooman Current Opinion in Structural Biology 42, 117-128, 2017 | 155 | 2017 |
| Quantification of biases in predictions of protein stability changes upon mutations F Pucci, KV Bernaerts, JM Kwasigroch, M Rooman Bioinformatics 34 (21), 3659-3665, 2018 | 130 | 2018 |
| Predicting protein thermal stability changes upon point mutations using statistical potentials: Introducing HoTMuSiC F Pucci, R Bourgeas, M Rooman Scientific Reports 6, 2016 | 121 | 2016 |
| SCooP: an accurate and fast predictor of protein stability curves as a function of temperature F Pucci, JM Kwasigroch, M Rooman Bioinformatics 33 (21), 3415-3422, 2017 | 95 | 2017 |
| Prediction and interpretation of deleterious coding variants in terms of protein structural stability F Ancien, F Pucci, M Godfroid, M Rooman Scientific Reports 8 (1), 4480, 2018 | 79 | 2018 |
| Computational analysis of the amino acid interactions that promote or decrease protein solubility Q Hou, R Bourgeas, F Pucci, M Rooman Scientific Reports 8 (1), 14661, 2018 | 64 | 2018 |
| Correlators of supersymmetric Wilson-loops, protected operators and matrix models in Script N= 4 SYM A Bassetto, L Griguolo, F Pucci, D Seminara, S Thambyahpillai, D Young Journal of High Energy Physics 2009 (08), 061, 2009 | 61 | 2009 |
| Supersymmetric Wilson loops at two loops A Bassetto, L Griguolo, F Pucci, D Seminara Journal of High Energy Physics 2008 (06), 083, 2008 | 61 | 2008 |
| Artificial intelligence challenges for predicting the impact of mutations on protein stability F Pucci, M Schwersensky, M Rooman Current Opinion in Structural Biology 72, 161-168, 2022 | 60 | 2022 |
| Protein thermostability prediction within homologous families using temperature-dependent statistical potentials F Pucci, M Dhanani, Y Dehouck, M Rooman PloS one 9 (3), e91659, 2014 | 58 | 2014 |
| SOLart: a structure-based method to predict protein solubility and aggregation Q Hou, JM Kwasigroch, M Rooman, F Pucci Bioinformatics 36 (5), 1445-1452, 2020 | 56 | 2020 |
| A comprehensive computational study of amino acid interactions in membrane proteins MN Mbaye, Q Hou, S Basu, F Teheux, F Pucci, M Rooman Scientific Reports 9, 12043, 2019 | 54 | 2019 |
| Correlators of supersymmetric Wilson loops at weak and strong coupling A Bassetto, L Griguolo, F Pucci, D Seminara, S Thambyahpillai, D Young Journal of High Energy Physics 2010 (3), 1-33, 2010 | 43 | 2010 |
| High-quality thermodynamic data on the stability changes of proteins upon single-site mutations F Pucci, R Bourgeas, M Rooman Journal of Physical and Chemical Reference Data 45 (2), 2016 | 42 | 2016 |
| Stability Curve Prediction of Homologous Proteins Using Temperature-Dependent Statistical Potentials F Pucci, M Rooman PLoS Comput Biol 10 (7), e1003689, 2014 | 40 | 2014 |
| pydca v1. 0: a comprehensive software for Direct Coupling Analysis of RNA and Protein Sequences MB Zerihun, F Pucci, EK Peter, A Schug Bioinformatics 36 (7), 2264-2265, 2020 | 38 | 2020 |
| Monopoles, abelian projection, and gauge invariance C Bonati, A Di Giacomo, L Lepori, F Pucci Physical Review D 81 (8), 085022, 2010 | 35 | 2010 |
| Improved insights into protein thermal stability: from the molecular to the structurome scale F Pucci, M Rooman Phil. Trans. R. Soc. A 374 (2080), 20160141, 2016 | 30 | 2016 |
| Symmetry Principles in Optimization Problems: an application to Protein Stability Prediction F Pucci, K Bernaerts, F Teheux, D Gilis, M Rooman IFAC-PapersOnLine 48 (1), 458-463, 2015 | 30 | 2015 |
| Prediction and evolution of the molecular fitness of SARS-CoV-2 variants: Introducing SpikePro F Pucci, M Rooman Viruses 13 (5), 935, 2021 | 28 | 2021 |
