ArticleJournal of chemical information and modeling2021
CATBOSS: Cluster Analysis of Trajectories Based on Segment Splitting.
Article in Journal of chemical information and modeling, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
6 citing papers in PubMed.
- Unveiling hidden intermediate states in protein folding with AI-based conditional transition clustering.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Random Functions as Data Compressors for Machine Learning of Molecular Processes.Journal of chemical theory and computation · 2026Article
- The cluster analysis of traditional Chinese medicine authenticity identification technique assisted by chemometrics.Heliyon · 2024Article
- Article
- An Efficient Path Classification Algorithm Based on Variational Autoencoder to Identify Metastable Path Channels for Complex Conformational Changes.Journal of chemical theory and computation · 2023Article
- Size-and-Shape Space Gaussian Mixture Models for Structural Clustering of Molecular Dynamics Trajectories.Journal of chemical theory and computation · 2022Article
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Authors and funding
3 authors.
Funding
Abstract
Molecular dynamics (MD) simulations are an exceedingly and increasingly potent tool for molecular behavior prediction and analysis. However, the enormous wealth of data generated by these simulations can be difficult to process and render in a human-readable fashion. Cluster analysis is a commonly used way to partition data into structurally distinct states. We present a method that improves on the state of the art by taking advantage of the temporal information of MD trajectories to enable more accurate clustering at a lower memory cost. To date, cluster analysis of MD simulations has generally treated simulation snapshots as a mere collection of independent data points and attempted to separate them into different clusters based on structural similarity. This new method, cluster analysis of trajectories based on segment splitting (CATBOSS), applies density-peak-based clustering to classify
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Registered trials
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