@inproceedings{a4cbc0eb03834722b89f74ad28f893e5,
title = "Density-based clustering analyses to identify heterogeneous cellular sub-populations",
abstract = "Autofluorescence microscopy of NAD(P)H and FAD provides functional metabolic measurements at the single-cell level. Here, density-based clustering algorithms were applied to metabolic autofluorescence measurements to identify cell-level heterogeneity in tumor cell cultures. The performance of the density-based clustering algorithm, DENCLUE, was tested in samples with known heterogeneity (co-cultures of breast carcinoma lines). DENCLUE was found to better represent the distribution of cell clusters compared to Gaussian mixture modeling. Overall, DENCLUE is a promising approach to quantify cell-level heterogeneity, and could be used to understand single cell population dynamics in cancer progression and treatment.",
keywords = "Metabolic imaging, breast cancer, cellular heterogeneity, density-based clustering, fluorescence lifetime, quantitative spatial analysis",
author = "Heaster, {Tiffany M.} and Walsh, {Alex J.} and Landman, {Bennett A.} and Skala, {Melissa C.}",
note = "Publisher Copyright: {\textcopyright} 2017 SPIE.; Diagnosis and Treatment of Diseases in the Breast and Reproductive System ; Conference date: 28-01-2017 Through 29-01-2017",
year = "2017",
doi = "10.1117/12.2252499",
language = "English (US)",
series = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",
publisher = "SPIE",
editor = "Campagnola, {Paul J.} and Skala, {Melissa C.}",
booktitle = "Diagnosis and Treatment of Diseases in the Breast and Reproductive System",
address = "United States",
}