ReviewNature protocols2021
Chemometric analysis in Raman spectroscopy from experimental design to machine learning-based modeling.
Review in Nature protocols, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 135 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
135 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Raman Spectroscopy and Machine Learning in the Diagnosis of Breast Cancer.Lasers in medical science · 2025Pooled it
- Recent advances in surface enhanced Raman spectroscopy for bacterial pathogen identifications.Journal of advanced research · 2023Pooled it
- Multitechnique Physicochemical Characterization of Horse Hoof Trimmings as Sustainable and Untapped Keratin Source.ChemistryOpen · 2026Article
- Limits and benefits of unsupervised transfer learning for Raman spectroscopy-based bioprocess monitoring.Bioprocess and biosystems engineering · 2026Article
- Raman-guided sample subset selection for cost-efficient offline calibration in bioprocesses.Bioprocess and biosystems engineering · 2026Article
- Rice straw sample preparation protocol for cell wall major constituent analysis via Raman spectroscopy.STAR protocols · 2026Article
- Rapid serum-based differentiation of ovarian tumors and assessment of post-treatment disease-free status using portable Raman spectroscopy and machine learning.Analytical and bioanalytical chemistry · 2026Article
- Towards the digital analytical sciences in chemistry and biochemistry: from FAIR data ecosystems to artificial intelligence.Analytical and bioanalytical chemistry · 2026Review
- All-optical multimodal mapping of single-cell-type-specific metabolic activities via REDCAT.Nature methods · 2026Article
- Raman spectral unmixing for quantitative analysis of multicomponent amino acid mixtures.Analytical and bioanalytical chemistry · 2026Article
- Variable-specific preprocessing enables cross-scale transferable Raman models from high-throughput bioreactor data.Bioresources and bioprocessing · 2026Article
- A Time-Gated Raman Spectroscopy and Mass Spectrometry Comparative Chemical Analysis of Plasticizers.ACS polymers Au · 2026Article
- Evaluating Limits of Machine Learning-Assisted Raman Spectroscopy in Classification of Biological Samples.ACS omega · 2026Article
- Potential of SERS and proteomics for biomarker detection in cancer cells.Analytical and bioanalytical chemistry · 2026Article
- Comparative Experimental Raman, DFT, and Chemometric Characterization of Selected Phenolic Acids: Structural and Environmental Contributions to the Vibrational Response.Molecules (Basel, Switzerland) · 2026Article
- Mineral biosignature identification from Raman spectroscopy using machine learning.PNAS nexus · 2026Article
- AI-Assisted Surface-Enhanced Raman Spectroscopy for Cardiovascular Diagnostics: From Plasmonic Materials to Clinical Translation.Nanomaterials (Basel, Switzerland) · 2026Review
- Raman Spectroscopy for Probing Pathological Protein Aggregates: Potential and Perspectives for Advanced Diagnostic Applications.International journal of molecular sciences · 2026Review
- Article
- Next-Generation SERS Probes: Engineering Hotspots, Intelligent Molecular Targeting, and AI-Driven Spectral Analysis for Emerging Applications.Nanomaterials (Basel, Switzerland) · 2026Review
75 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Raman spectroscopy is increasingly being used in biology, forensics, diagnostics, pharmaceutics and food science applications. This growth is triggered not only by improvements in the computational and experimental setups but also by the development of chemometric techniques. Chemometric techniques are the analytical processes used to detect and extract information from subtle differences in Raman spectra obtained from related samples. This information could be used to find out, for example, whether a mixture of bacterial cells contains different species, or whether a mammalian cell is healthy or not. Chemometric techniques include spectral processing (ensuring that the spectra used for the subsequent computational processes are as clean as possible) as well as the statistical analysis of the data required for finding the spectral differences that are most useful for differentiation between, for example, different cell types. For Raman spectra, this analysis process is not yet standardized, and there are many confounding pitfalls. This protocol provides guidance on how to perform a Raman spectral analysis: how to avoid these pitfalls, and strategies to circumvent problematic issues. The protocol is divided into four parts: experimental design, data preprocessing, data learning and model transfer. We exemplify our workflow using three example datasets where the spectra from individual cells were collected in single-cell mode, and one dataset where the data were collected from a raster scanning-based Raman spectral imaging experiment of mice tissue. Our aim is to help move Raman-based technologies from proof-of-concept studies toward real-world applications.
Indexed as
Identifiers
34741152What OpenQuestion holds
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.