Advances in deep learning-based applications for Raman spectroscopy analysis: A mini-review of the progress and challenges
D Boateng - Microchemical Journal, 2025 - Elsevier
Raman spectroscopy is a non-invasive, label-free characterization technique that provides
detailed chemical information about samples, particularly of complex chemical mixtures …
detailed chemical information about samples, particularly of complex chemical mixtures …
Machine Learning-Assisted “Shrink-Restricted” SERS Strategy for Classification of Environmental Nanoplastic-Induced Cell Death
R Li, X Sun, Y Hu, S Liu, S Huang… - Environmental …, 2024 - ACS Publications
The biotoxicity of nanoplastics (NPs), especially from environmental sources, and “NPs
carrier effect” are in the early stages of research. This study presents a machine learning …
carrier effect” are in the early stages of research. This study presents a machine learning …
Enzymatic Desialylation Enables Reliable Charge Variant Characterization of Highly Glycosylated and Sialylated Fc Fusion Proteins
Fusion proteins constitute a class of engineered therapeutics and have emerged as
promising candidates for disease treatment. However, the structural complexity and …
promising candidates for disease treatment. However, the structural complexity and …
Exploring Breast Cancer-Related Biochemical Changes in Circulating Extracellular Vesicles Using Raman Spectroscopy
A Bonizzi, L Signati, M Grimaldi, M Truffi, F Piccotti… - bioRxiv, 2024 - biorxiv.org
Extracellular vesicles (EVs) are a subgroup of the circulating particles, released by cells in
both normal and diseased states, carrying active biomolecules. They have gained significant …
both normal and diseased states, carrying active biomolecules. They have gained significant …