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PreprintCC BYChemRxiv

FRACTAL: A Ratiometric-based Fingerprinting Framework for Robust Spectral Classification and Ratio-based Spectroscopic Marker Discovery

  • Lamyaa M. Almehmadi1,2
  1. 1Department of Materials Science and Engineering
  2. 2Massachusetts Institute of Technology
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Abstract

Spectral classification is conventionally performed on band intensities, yet ratios between bands have long served as diagnostic indices in vibrational spectroscopy, from lipid-to-protein markers of membrane composition to amide ratios reporting protein secondary structure. Their use, however, has remained confined to a handful of expert-selected pairs, leaving most of the ratio information contained in a spectrum unexamined. Here I present FRACTAL (Full Ratio Combinatorial Analysis for Classification and Analytical Interpretation), which computes every pairwise log-intensity ratio among detected peaks to form a complete ratiometric fingerprint, grounded in compositional data analysis. Each component is a contrast between two assigned bands and is invariant to the multiplicative factors that scale spectral intensities. Applied to serum Raman spectra from a total of 103 donors (53 with COVID-19, 50 healthy controls), FRACTAL screened all 105 ratios among 15 reproducible peaks and identified 38 discriminant contrasts; a ten-ratio fingerprint then matched full-spectrum performance across six classifier architectures spanning linear, kernel-based and ensemble methods (mean internal AUC 0.89–0.93) and generalized to a withheld 20-donor cohort, where every classifier exceeded an AUC of 0.92 and all six converged on the same donor-level prediction accuracy at the median-AUC seed. The retained ratios map onto aromatic amino acid, acute-phase protein and protein–lipid contrasts independently reported in COVID-19. FRACTAL establishes exhaustive ratiometric fingerprinting as a compact, robust and interpretable representation for spectral classification and spectroscopic marker discovery.

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Cite

BibTeXRIS
BibTeX
@misc{almehmadi2026fractal,
  title = {{FRACTAL: A Ratiometric-based Fingerprinting Framework for Robust Spectral Classification and Ratio-based Spectroscopic Marker Discovery}},
  author = {Lamyaa M. Almehmadi},
  howpublished = {ChemRxiv},
  year = {2026},
  month = oct,
  doi = {10.26434/chemrxiv.15010325/v1},
  url = {https://chemrxiv.org/doi/full/10.26434/chemrxiv.15010325/v1},
  note = {CC BY},
}
RIS
TY  - UNPB
TI  - FRACTAL: A Ratiometric-based Fingerprinting Framework for Robust Spectral Classification and Ratio-based Spectroscopic Marker Discovery
AU  - Lamyaa M. Almehmadi
PY  - 2026
DA  - 2026/10/12
PB  - ChemRxiv
DO  - 10.26434/chemrxiv.15010325/v1
UR  - https://chemrxiv.org/doi/full/10.26434/chemrxiv.15010325/v1
AB  - Spectral classification is conventionally performed on band intensities, yet ratios between bands have long served as diagnostic indices in vibrational spectroscopy, from lipid-to-protein markers of membrane composition to amide ratios reporting protein secondary structure. Their use, however, has remained confined to a handful of expert-selected pairs, leaving most of the ratio information contained in a spectrum unexamined. Here I present FRACTAL (Full Ratio Combinatorial Analysis for Classification and Analytical Interpretation), which computes every pairwise log-intensity ratio among detected peaks to form a complete ratiometric fingerprint, grounded in compositional data analysis. Each component is a contrast between two assigned bands and is invariant to the multiplicative factors that scale spectral intensities. Applied to serum Raman spectra from a total of 103 donors (53 with COVID-19, 50 healthy controls), FRACTAL screened all 105 ratios among 15 reproducible peaks and identified 38 discriminant contrasts; a ten-ratio fingerprint then matched full-spectrum performance across six classifier architectures spanning linear, kernel-based and ensemble methods (mean internal AUC 0.89–0.93) and generalized to a withheld 20-donor cohort, where every classifier exceeded an AUC of 0.92 and all six converged on the same donor-level prediction accuracy at the median-AUC seed. The retained ratios map onto aromatic amino acid, acute-phase protein and protein–lipid contrasts independently reported in COVID-19. FRACTAL establishes exhaustive ratiometric fingerprinting as a compact, robust and interpretable representation for spectral classification and spectroscopic marker discovery.
ER  -