Diffusion map master thesis

Abstract Using the helix-coil transitions of alanine pentapeptide as an illustrative example, we demonstrate the use of diffusion maps in the analysis of molecular dynamics simulation trajectories. In: 2nd HLT conf.

diffusion map matlab

We also chose this system because it has been studied in detail by Buchete and Hummer BH16 who used informed intuition to partition conformation space and to formulate a master-equation model that describes its dynamics.

However, the energy landscape of bio polymers and the corresponding structure of populated regions in conformation space are often quite complex. While significant work has been done on to perform this clustering algorithm, it has not been studied in a reduced dimension space, typically in online processing scenarios.

manifold learning diffusion maps

The resulting pretreated data are then used in a clustering step. Following an initial, data-mining based dimensionality reduction step, we identify possible metastable states within the new, reduced space. This is a preview of subscription content, log in to check access.

Diffusion map master thesis

IS Conf. This is a preview of subscription content, log in to check access. Munkres, J. In poor representations we expect large hysteresis effects because distant, slowly equilibrating regions of conformation space are erroneously not separated in projection. Allan, J. Wong, W. In: 25th ECIR, pp. Brown, R. Coarse master equations and Markov state models have attracted much attention because they can be constructed directly from molecular dynamics simulations, 15—21 with the aim to capture the dynamics of most interest, occurring over long time scales. Such projections onto discrete sets of states naturally lead to descriptions of the dynamics in terms of Markov state models 14 or coarse master equations 15,16 with discrete time-stepping or continuous dynamics, respectively. Jain, A.

We deliberately chose a force field 35 that over-emphasizes the helix content of Ala5 to obtain a minimal model of the helix-coil transition. Lafon, S.

Manifold learning diffusion maps

Part A to Appear Google Scholar 6. Coarse master equations and Markov state models have attracted much attention because they can be constructed directly from molecular dynamics simulations, 15—21 with the aim to capture the dynamics of most interest, occurring over long time scales. This article has been cited by other articles in PMC. Electronic addresses: ude. Chen, F. The competing requirements to include large numbers of degrees of freedom, to resolve even the finest time scales of covalent bond motions and atomic collisions, and to overcome high enthalpic barriers between large conformational basins stand in the way of proper sampling with direct molecular simulations. The system thus provides a useful benchmark sharing much of the complexity of larger-scale molecular simulation problems. Hammouda, K.

Abstract Using the helix-coil transitions of alanine pentapeptide as an illustrative example, we demonstrate the use of diffusion maps in the analysis of molecular dynamics simulation trajectories. Chen, M. To illustrate and test this two-step approach we studied the conformational changes of the small molecule alanine pentapeptide Ala5 see Fig.

Manifold learning diffusion maps

The success of such models, however, strongly depends on the ability to decompose conformation space into a set of meaningful metastable states, associated with low free energy meta basins. In this work, we illustrate the construction of a link between the global and local approaches to dimensionality reduction. In a comparison with previous work, we demonstrate how manifold learning techniques may complement and enhance informed intuition commonly used to construct reduced descriptions of the dynamics in molecular conformation space. As a result, we expect that linear projection methods will not necessarily provide us with the optimal lowest-dimensional representations that reliably separate conformational basins in a clear and useful form. Belkin, N. The success of such models, however, strongly depends on the ability to decompose conformation space into a set of meaningful metastable states, associated with low free energy meta basins. However, the energy landscape of bio polymers and the corresponding structure of populated regions in conformation space are often quite complex. Received Jun 14; Accepted Aug 4.

Chen, C.

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Diffusion maps, clustering and fuzzy Markov modeling in peptide folding transitions