# Using data-reduction techniques to analyse biomolecular trajectories

## TL;DR

This paper reviews how dimensionality reduction algorithms like diffusion maps and sketch-map are used to analyze complex molecular dynamics trajectories, highlighting their functions, practical issues, and applications.

## Contribution

It provides a comprehensive overview of dimensionality reduction techniques applied to biomolecular trajectories, including practical considerations and comparative analysis.

## Key findings

- Diffusion maps and sketch-map effectively analyze molecular trajectories.
- Practical issues like landmark selection impact analysis quality.
- Sketch-map has been successfully applied to various biomolecular problems.

## 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 parts, 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.