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Marco Cecchini

Researcher at University of Strasbourg

Publications -  58
Citations -  2927

Marco Cecchini is an academic researcher from University of Strasbourg. The author has contributed to research in topics: Ion channel & Allosteric regulation. The author has an hindex of 25, co-authored 58 publications receiving 2532 citations. Previous affiliations of Marco Cecchini include Centre national de la recherche scientifique & University of Zurich.

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Adsorption of Aromatic and Anti-Aromatic Systems on Graphene through π−π Stacking

TL;DR: In this article, the adsorption of neutral (poly-aromatic, antiaromatic) and more generally π-conjugated systems on graphene is studied as a prototypical case of π−π stacking.
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Wordom: a program for efficient analysis of molecular dynamics simulations

TL;DR: Wordom as discussed by the authors is a versatile program for manipulation of molecular dynamics trajectories and efficient analysis of simulations, which includes a procedure to evaluate significance of sampling for principal component analysis as well as modules for clustering multiple conformations and evaluation of order parameters for folding and aggregation.
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Allostery in Its Many Disguises: From Theory to Applications

Shoshana J. Wodak, +41 more
- 02 Apr 2019 - 
TL;DR: An overview of the progress and remaining limitations in the understanding of the mechanistic foundations of allostery gained from computational and experimental analyses of real protein systems and model systems is provided.
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Replica exchange molecular dynamics simulations of amyloid peptide aggregation.

TL;DR: The replica exchange molecular dynamics (REMD) approach is applied to four oligomeric peptide systems in this paper, and two order parameters, borrowed from anisotropic fluid analysis, are used to monitor the aggregation process.
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Predicting self-assembly: from empirism to determinism

TL;DR: This framework endeavor to correlate state-of-the-art chemical design, programming and/or engineering of reversible (thermal and chemical equilibrium) self-assembly with knowledge of the underlying partition function landscape in a step towards quantitative predictions and ab initio molecular design.