Use Kluster

Official Neurosnap webserver for accessing Kluster online.

BETA - MAY CONTAIN BUGS Protein Clustering

Overview

Kluster clusters and analyzes protein structures by their structural similarities. The tool integrates TM-align/US-align for structural alignment with modern dimensionality reduction methods (UMAP, t-SNE, or PCA) and DBSCAN clustering. It calculates pairwise structural similarities using TM-score and RMSD metrics, providing insightful visualizations of protein structure relationships through combined clustering and dimensionality reduction workflows.

Neurosnap Overview

The Kluster online webserver allows anybody with a Neurosnap account to run and access Kluster, no downloads required. Information submitted through this webserver is kept confidential and never sold to third parties as detailed by our strong terms of service and privacy policy.

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Features

  • Supports multiple structural comparison metrics (TM-score, RMSD) with both TMalign and USalign alignment tools.
  • Implements dimensionality reduction using UMAP, t-SNE, or PCA for intuitive visualization.
  • Performs clustering using DBSCAN to identify structural similarity groups.
  • Provides interactive 2D/3D visualization with cluster-based coloring.
  • Enables parallel processing for efficient analysis of large protein structure datasets.

Statistics

Neurosnap periodically calculates runtime statistics based on job execution data. These estimates provide a general guideline for how long your job may take, but actual runtimes can vary significantly depending on factors like input size or settings used.

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API Request

Access Kluster using the Neurosnap API by sending a request using any programming language with HTTP support. To safely generate an API key, visit the API tab of your overview page.

Job Note

Provide a name or description for your job to help you organize and track its results. This input is solely for organizational purposes and does not impact the outcome of the job.

Configuration & Options

Service Inputs

Input protein structures to cluster. Proteins should be monomeric and have a single chain.

The tool used to align the input structures.

Features to be utilized for clustering the input structures. Options include metrics like TM-score, RMSD, and both, which assess structural similarity.

Dimensionality reduction method used to reduce the dimensionality of the features.

Advanced Settings

Final dimensionality of the reduced features. Select 2D for a 2D projection, or 3D for a 3D projection.

The algorithm used to project the data into a 1d space for animation.

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