ArticleJournal of proteome research2018
Interactive Visual Exploration of 3D Mass Spectrometry Imaging Data Using Hierarchical Stochastic Neighbor Embedding Reveals Spatiomolecular Structures at Full Data Resolution.
Article in Journal of proteome research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 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
21 citing papers in PubMed.
- Innate and adaptive nasal mucosal immune responses following experimental human pneumococcal colonization.The Journal of clinical investigation · 2019Trial
- Towards precision oncology: unsupervised manifold learning for spatial molecular profiling in cancer tissues.BMC bioinformatics · 2026Article
- Topological segmentation of mass spectrometry imaging data.Journal of mass spectrometry and advances in the clinical lab · 2025Article
- A New Approach to Large Multiomics Data Integration.Analytical chemistry · 2025Article
- Unraveling Spatial Heterogeneity in Mass Spectrometry Imaging Data with GraphMSI.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Optimization of Mass Spectrometry Imaging for Drug Metabolism and Distribution Studies in the Zebrafish Larvae Model: A Case Study with the Opioid Antagonist Naloxone.International journal of molecular sciences · 2023Article
- Visinity: Visual Spatial Neighborhood Analysis for Multiplexed Tissue Imaging Data.IEEE transactions on visualization and computer graphics · 2023Article
- DiviK: divisive intelligent K-means for hands-free unsupervised clustering in big biological data.BMC bioinformatics · 2022Article
- Emerging Computational Methods in Mass Spectrometry Imaging.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2022Review
- Evaluation and comparison of unsupervised methods for the extraction of spatial patterns from mass spectrometry imaging data (MSI).Scientific reports · 2022Article
- ADVANCES IN HIGH-RESOLUTION MALDI MASS SPECTROMETRY FOR NEUROBIOLOGY.Mass spectrometry reviews · 2022Review
- Advanced applications of mass spectrometry imaging technology in quality control and safety assessments of traditional Chinese medicines.Journal of ethnopharmacology · 2022Review
- MALDI-MSI Towards Multimodal Imaging: Challenges and Perspectives.Frontiers in chemistry · 2022Review
- Peak learning of mass spectrometry imaging data using artificial neural networks.Nature communications · 2021Article
- M2aia-Interactive, fast, and memory-efficient analysis of 2D and 3D multi-modal mass spectrometry imaging data.GigaScience · 2021Article
- Three-dimensional (3D) imaging of lipids in skin tissues with infrared matrix-assisted laser desorption electrospray ionization (MALDESI) mass spectrometry.Analytical and bioanalytical chemistry · 2021Article
- Experimental and Data Analysis Considerations for Three-Dimensional Mass Spectrometry Imaging in Biomedical Research.Molecular imaging and biology · 2021Review
- Spatial Segmentation of Mass Spectrometry Imaging Data by Combining Multivariate Clustering and Univariate Thresholding.Analytical chemistry · 2021Article
- Unsupervised machine learning for exploratory data analysis in imaging mass spectrometry.Mass spectrometry reviews · 2020Review
- Chemometric Strategies for Sensitive Annotation and Validation of Anatomical Regions of Interest in Complex Imaging Mass Spectrometry Data.Journal of the American Society for Mass Spectrometry · 2019Article
Corrections and comments
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Authors and funding
7 authors.
Funding
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Abstract
Technological advances in mass spectrometry imaging (MSI) have contributed to growing interest in 3D MSI. However, the large size of 3D MSI data sets has made their efficient analysis and visualization and the identification of informative molecular patterns computationally challenging. Hierarchical stochastic neighbor embedding (HSNE), a nonlinear dimensionality reduction technique that aims at finding hierarchical and multiscale representations of large data sets, is a recent development that enables the analysis of millions of data points, with manageable time and memory complexities. We demonstrate that HSNE can be used to analyze large 3D MSI data sets at full mass spectral and spatial resolution. To benchmark the technique as well as demonstrate its broad applicability, we have analyzed a number of publicly available 3D MSI data sets, recorded from various biological systems and spanning different mass-spectrometry ionization techniques. We demonstrate that HSNE is able to rapidly identify regions of interest within these large high-dimensionality data sets as well as aid the identification of molecular ions that characterize these regions of interest; furthermore, through clearly separating measurement artifacts, the HSNE analysis exhibits a degree of robustness to measurement batch effects, spatially correlated noise, and mass spectral misalignment.
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Registered trials
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