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Sampled Energy Landscapes: Analysis and Comparison

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This talk will discuss algorithms to analyze and compare sampled energy landscapes of (bio-)molecular systems.

In the first part, a generic algorithm to analyze a height field i.e. a collection of conformations each endowed with an elevation, will be presented. The algorithm allows identifying persistent local minima (or maxima), their attraction basins, and connexions across saddles. Two applications of the algorithm will be discussed, namely to study a sampled energy landscape (focus on local minima and index one saddles), and to perform density based clustering of conformations (focus on local maxima and index d-1 saddles).

In the second part, an algorithm to compare two (sampled) energy landscapes will be outlined. The strategy, based on optimal transportation theory, consists of computing a least cost mapping between the basins, compatible with the transition paths known on both landscapes.

Illustrations will be provided for a simplified protein model (a BLN69 model), whose landscape has been exhaustively studied in the literature.


F. Cazals and T. Dreyfus and D. Mazauric and A. Roth and C. H. Robert, Conformational Ensembles and Sampled Energy Landscapes: Analysis and Comparison, under revision, 2014. Preprint:

F. Cazals and D. Mazauric, Mass Transportation Problems with Connectivity Constraints, with Applications to Energy Landscape Comparison, submitted, 2014. Preprint:

This talk is part of the Theory - Chemistry Research Interest Group series.

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