ArticleAnalytical chemistry2025
Framework for Accurate Single-Molecule Spectroscopic Imaging Analyses Using Monte Carlo Simulation and Deep Learning.
Article in Analytical chemistry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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Who cites it
5 citing papers in PubMed.
- Organic Chemistry as a Catalyst for AI Innovation: Challenges, Methods, and Emerging Paradigms.Chemical reviews · 2026Review
- Solvatochromic BODIPYs with Polarity-Independent Absorption for Functional Super-resolution Imaging of Live Cell Membranes.Chemical & biomedical imaging · 2026Article
- SIMBA: an agentic AI platform for single-molecule multidimensional imaging.bioRxiv : the preprint server for biology · 2026Article
- Functional super-resolution microscopy of fibers and polymers: convergence of artificial and biological systems at the nanoscale.Nanoscale horizons · 2026Review
- Orthogonally Dispersed Spectroscopic Single-Molecule Localization Microscopy.Nanophotonics (Berlin, Germany) · 2026Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
Accurate single-molecule spectral imaging denoising and analysis are essential for advancing high-throughput single-molecule spectroscopy and spectrally resolved super-resolution microscopy. However, a standardized framework for guiding the accurate analysis of single-molecule spectral data remains unavailable. To address this, we developed an analysis framework that generates ground truth (GT) single-molecule spectral imaging data using Monte Carlo simulations, enabling the first supervised learning-based imaging denoising method (referred to as SpecUNet) for single-molecule spectral images. Within this framework, we established eight comprehensive evaluation metrics to systematically compare the performance of SpecUNet against existing imaging analytics using synthetic GT data. We further validated SpecUNet's performance experimentally and demonstrated its capability in accurately characterizing the single-molecule fluorescence spectral heterogeneity of Janelia Fluors. Additionally, we explored its ability to decode the spectral responses of the polarity-sensitive probe Nile Red under varying nanoscale chemical polarities and heterogeneities.
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.