Briefly, one considers a collection of supervectors formed by concatenating snapshots falling within a window moving over the data vectors. For this, we use an approach used in nonlinear Laplacian spectral analysis (NLSA) (25), a technique capable of performing SVD on nonlinear manifolds (nonlinear SVD for short) (SI Text). We solve this problem by mapping the manifold to another space, in which the eigenfunctions are known exactly. The absence of information on the metric precludes a consistent description of the conformational changes in terms of a known universal parameter. Describes the data in terms of the eigenfunctions of the Laplace-Beltrami operator with respect to an unknown metric (22).
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June 2023
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