Gervasio, Francesco Luigi
University of Geneva · University College London
7 papers on CoChatORCID 0000-0003-4831-5039
Most cited papers
- Verified
Metadynamics: a method to simulate rare events and reconstruct the free energy in biophysics, chemistry and material science
Laio, A., & Gervasio, F. L. (2008) · Reports on Progress in Physics
Advanced Physical and Chemical Molecular InteractionsProtein Structure and Dynamics
Cited by 1,619
- Verified
Assessing the Accuracy of Metadynamics
Laio, A., Rodriguez-Fortea, A., Gervasio, F. L., Ceccarelli, M., & Parrinello, M. (2005) · The Journal of Physical Chemistry B
Advanced Physical and Chemical Molecular InteractionsAdvanced Chemical Physics Studies
Cited by 517
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Role of glutamine synthetase in angiogenesis beyond glutamine synthesis
Eelen, G., Dubois, C., Cantelmo, A. R., Goveia, J., Brüning, U., DeRan, M., Jarugumilli, G., van Rijssel, J., Saladino, G., Comitani, F., et al. (2018) · Nature
Angiogenesis and VEGF in CancerProtein Kinase Regulation and GTPase Signaling
Cited by 220
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The Unfolded Ensemble and Folding Mechanism of the C-Terminal GB1 β-Hairpin
Bonomi, M., Branduardi, D., Gervasio, F. L., & Parrinello, M. (2008) · Journal of the American Chemical Society
Protein Structure and DynamicsChemical Synthesis and Analysis
Cited by 97
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Revealing druggable cryptic pockets in the Nsp1 of SARS-CoV-2 and other β-coronaviruses by simulations and crystallography
Borsatto, A., Akkad, O., Galdadas, I., Ma, S., Damfo, S., Haider, S., Kozielski, F., Estarellas, C., & Gervasio, F. L. (2022) · eLife
SARS-CoV-2 and COVID-19 ResearchComputational Drug Discovery Methods
Cited by 32
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Addressing Suboptimal Poses in Nonequilibrium Alchemical Calculations
Karrenbrock, M., Rizzi, V., Procacci, P., & Gervasio, F. L. (2024) · The Journal of Physical Chemistry B
Computational Drug Discovery MethodsProtein Degradation and Inhibitors
Cited by 5
- Verified
Editorial: Machine Learning in Biomolecular Simulations
Verkhivker, G., Spiwok, V., & Gervasio, F. L. (2019) · Frontiers in Molecular Biosciences
Machine Learning in Materials ScienceProtein Structure and Dynamics
Cited by 4
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