What is he best known for?
The fields of study he is best known for:
- Enzyme
- Quantum mechanics
- DNA
His primary areas of investigation include Metadynamics, Computational chemistry, Molecular dynamics, Statistical physics and Protein structure.
His research in Metadynamics intersects with topics in Collective variables, Docking and Protein folding.
His work deals with themes such as Biomolecule, Potential energy surface, Time evolution and Closed conformation, which intersect with Computational chemistry.
Francesco Luigi Gervasio has included themes like Crystallography, Car–Parrinello molecular dynamics, Chemical physics and Systems biology in his Molecular dynamics study.
His Statistical physics study incorporates themes from Phase transition, Umbrella sampling and Local Elevation.
His biological study spans a wide range of topics, including Biophysics, Stereochemistry and Protein secondary structure.
His most cited work include:
- Metadynamics: a method to simulate rare events and reconstruct the free energy in biophysics, chemistry and material science (962 citations)
- Free-Energy Landscape for β Hairpin Folding from Combined Parallel Tempering and Metadynamics (338 citations)
- Assessing the accuracy of metadynamics. (334 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Metadynamics, Molecular dynamics, Biophysics, Allosteric regulation and Computational chemistry.
His Metadynamics research is multidisciplinary, relying on both Chemical physics, Statistical physics, Docking and Collective variables.
His studies in Statistical physics integrate themes in fields like Protein folding and Local Elevation.
His Molecular dynamics research incorporates elements of Plasma protein binding, Ab initio, Hydrogen bond, Protein structure and Binding site.
His study in Biophysics is interdisciplinary in nature, drawing from both Amino acid, Nanotechnology, Kinase and Phosphorylation.
His study on Allosteric regulation also encompasses disciplines like
- Mechanism that intertwine with fields like Coupling,
- Fibroblast growth factor most often made with reference to Cell biology.
He most often published in these fields:
- Metadynamics (28.10%)
- Molecular dynamics (28.10%)
- Biophysics (22.22%)
What were the highlights of his more recent work (between 2018-2021)?
- Biophysics (22.22%)
- Allosteric regulation (17.65%)
- Cell biology (13.73%)
In recent papers he was focusing on the following fields of study:
Francesco Luigi Gervasio spends much of his time researching Biophysics, Allosteric regulation, Cell biology, Molecular dynamics and Enzyme.
His studies deal with areas such as Agonist, Intracellular, G protein and Ternary complex as well as Biophysics.
Francesco Luigi Gervasio focuses mostly in the field of Allosteric regulation, narrowing it down to topics relating to G protein-coupled receptor and, in certain cases, Structural similarity, Binding pocket, Adenosine receptor and Ligand.
His Cell biology research integrates issues from Mode of action and Energy landscape.
Specifically, his work in Molecular dynamics is concerned with the study of Metadynamics.
In general Enzyme, his work in Active site is often linked to β lactamases and Shape change linking many areas of study.
Between 2018 and 2021, his most popular works were:
- Promoting transparency and reproducibility in enhanced molecular simulations (145 citations)
- Investigating Cryptic Binding Sites by Molecular Dynamics Simulations (18 citations)
- Investigating Cryptic Binding Sites by Molecular Dynamics Simulations (18 citations)
In his most recent research, the most cited papers focused on:
- Enzyme
- Quantum mechanics
- DNA
His scientific interests lie mostly in Molecular dynamics, Computational biology, Binding site, Metadynamics and State model.
The Molecular dynamics study combines topics in areas such as Statistical physics, Observable and Pathogenic mutation.
The concepts of his Computational biology study are interwoven with issues in G protein-coupled receptor, Ligand, Adenosine receptor, Binding pocket and Selectivity.
He combines subjects such as Protein dynamics and Drug discovery with his study of Binding site.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
