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Using Data-Reduction Techniques to Analyze Biomolecular Trajectories

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Biomolecular Simulations

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2022))

Abstract

This chapter discusses the way in which dimensionality reduction algorithms such as diffusion maps and sketch-map can be used to analyze molecular dynamics trajectories. The first part discusses how these various algorithms function as well as practical issues such as landmark selection and how these algorithms can be used when the data to be analyzed comes from enhanced sampling trajectories. In the later part a comparison between the results obtained by applying various algorithms to two sets of sample data is performed and discussed. This section is then followed by a summary of how one algorithm in particular, sketch-map, has been applied to a range of problems. The chapter concludes with a discussion on the directions that we believe this field is currently moving.

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Author information

Authors and Affiliations

  1. Atomistic Simulation Centre, School of Mathematics and Physics, Queen’s University Belfast, Belfast, UK

    Gareth A. Tribello

  2. Laboratory of Computational Science and Modelling and National Centre for Computational Design and Discovery of Novel Materials MARVEL, IMX, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland

    Piero Gasparotto

Authors
  1. Gareth A. Tribello
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  2. Piero Gasparotto
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Correspondence to Gareth A. Tribello .

Editor information

Editors and Affiliations

  1. Structural Bioinformatics Unit, Institut Pasteur, CNRS UMR 3528, Paris, France

    Massimiliano Bonomi

  2. Dipartimento di Bioscienze, Università degli Studi di Milano, Milano, Italy

    Carlo Camilloni

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Tribello, G.A., Gasparotto, P. (2019). Using Data-Reduction Techniques to Analyze Biomolecular Trajectories. In: Bonomi, M., Camilloni, C. (eds) Biomolecular Simulations. Methods in Molecular Biology, vol 2022. Humana, New York, NY. https://doi.org/10.1007/978-1-4939-9608-7_19

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  • DOI: https://doi.org/10.1007/978-1-4939-9608-7_19

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-4939-9607-0

  • Online ISBN: 978-1-4939-9608-7

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