Use Kluster
Official Neurosnap webserver for accessing Kluster online.
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 Use and Privacy Policy.
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.
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Citations
Please cite the original work when using Kluster in publications or research outputs.
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Amani, K., Shivnauth, V., & Castroverde, C. D. M. (2023). CBP60-DB: An AlphaFold-predicted plant kingdom-wide database of the CALMODULIN-BINDING PROTEIN 60 protein family with a novel structural clustering algorithm. Plant Direct, 7(7), e509. https://doi.org/10.1002/pld3.509 |
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Y. Zhang, J. Skolnick, TM-align: A protein structure alignment algorithm based on TM-score, Nucleic Acids Research, 33: 2302-2309 (2005) |
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Chengxin Zhang, Morgan Shine, Anna Marie Pyle, Yang Zhang. US-align: Universal Structure Alignment of Proteins, Nucleic Acids and Macromolecular Complexes. Nature Methods, 19: 1109-1115 (2022) |
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Zhang, Y., & Skolnick, J. (2005). TM-align: a protein structure alignment algorithm based on the TM-score. Nucleic Acids Research, 33(7), 2302-2309. |
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McInnes et al., (2018). UMAP: Uniform Manifold Approximation and Projection. Journal of Open Source Software, 3(29), 861, https://doi.org/10.21105/joss.00861 |
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van der Maaten, L., & Hinton, G. (2008). Visualizing Data using t-SNE. Journal of Machine Learning Research, 9(86), 2579–2605. Retrieved from http://jmlr.org/papers/v9/vandermaaten08a.html |
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Karl Pearson F.R.S. . (1901). LIII. On lines and planes of closest fit to systems of points in space. The London, Edinburgh, and Dublin Philosophical Magazine and Journal of Science, 2(11), 559–572. https://doi.org/10.1080/14786440109462720 |
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Ester, M., Kriegel, H.-P., Sander, J., Xu, X., & others. (1996). A density-based algorithm for discovering clusters in large spatial databases with noise. In kdd (Vol. 96, pp. 226–231). |
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Neurosnap Inc. (2022). Neurosnap: An online platform for computational biology and chemistry. Available at: https://neurosnap.ai/ |
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