ArticleScientific reports2018
BASIS: High-performance bioinformatics platform for processing of large-scale mass spectrometry imaging data in chemically augmented histology.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed.
- Insights From Spatiality: Accelerating Pharmaceutical Research Using Mass Spectrometry Imaging.Medicinal research reviews · 2026Review
- Multimodal molecular mapping of the vasculature in human cortex reveals lipid markers of cerebral amyloid angiopathy.Acta neuropathologica communications · 2026Article
- Multimodal Molecular Mapping of the Vasculature in Human Cortex Reveals Lipid Markers of Cerebral Amyloid Angiopathy.bioRxiv : the preprint server for biology · 2026Article
- Article
- MSIght: A Modular Platform for Improved Confidence in Global, Untargeted Mass Spectrometry Imaging Annotation.Journal of proteome research · 2025Article
- msiFlow: automated workflows for reproducible and scalable multimodal mass spectrometry imaging and microscopy data analysis.Nature communications · 2025Article
- Enhancing mass spectrometry imaging accessibility using convolutional autoencoders for deriving hypoxia-associated peptides from tumors.NPJ systems biology and applications · 2024Article
- Review
- Cardinal v.3: a versatile open-source software for mass spectrometry imaging analysis.Nature methods · 2023Article
- Mass Spectrometry Imaging Reveals Abnormalities in Cardiolipin Composition and Distribution in Astrocytoma Tumor Tissues.Cancers · 2023Article
- Spatial Lipidomic Profiling of Mouse Joint Tissue Demonstrates the Essential Role of PHOSPHO1 in Growth Plate Homeostasis.Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research · 2023Article
- Spatial probabilistic mapping of metabolite ensembles in mass spectrometry imaging.Nature communications · 2023Article
- "What I wish I had known before starting my PhD".Analytical science advances · 2023Article
- Advancements in Oncoproteomics Technologies: Treading toward Translation into Clinical Practice.Proteomes · 2023Review
- Emerging Computational Methods in Mass Spectrometry Imaging.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2022Review
- Article
- Batch Effects in MALDI Mass Spectrometry Imaging.Journal of the American Society for Mass Spectrometry · 2021Article
- Unsupervised machine learning for exploratory data analysis in imaging mass spectrometry.Mass spectrometry reviews · 2020Review
- Article
- Mass spectrometry imaging to detect lipid biomarkers and disease signatures in cancer.Cancer reports (Hoboken, N.J.) · 2019Review
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Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Mass Spectrometry Imaging (MSI) holds significant promise in augmenting digital histopathologic analysis by generating highly robust big data about the metabolic, lipidomic and proteomic molecular content of the samples. In the process, a vast quantity of unrefined data, that can amount to several hundred gigabytes per tissue section, is produced. Managing, analysing and interpreting this data is a significant challenge and represents a major barrier to the translational application of MSI. Existing data analysis solutions for MSI rely on a set of heterogeneous bioinformatics packages that are not scalable for the reproducible processing of large-scale (hundreds to thousands) biological sample sets. Here, we present a computational platform (pyBASIS) capable of optimized and scalable processing of MSI data for improved information recovery and comparative analysis across tissue specimens using machine learning and related pattern recognition approaches. The proposed solution also provides a means of seamlessly integrating experimental laboratory data with downstream bioinformatics interpretation/analyses, resulting in a truly integrated system for translational MSI.
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Registered trials
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