Spatial distribution of the Shannon entropy for mass spectrometry imaging.

Autor: Lili Xu, Kenji Kikushima, Shumpei Sato, Ariful Islam, Tomohito Sato, Shuhei Aramaki, Chi Zhang, Takumi Sakamoto, Fumihiro Eto, Yutaka Takahashi, Ikuko Yao, Manabu Machida, Tomoaki Kahyo, Mitsutoshi Setou
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: PLoS ONE, Vol 18, Iss 4, p e0283966 (2023)
Druh dokumentu: article
ISSN: 1932-6203
DOI: 10.1371/journal.pone.0283966
Popis: Mass spectrometry imaging (MSI) allows us to visualize the spatial distribution of molecular components in a sample. A large amount of mass spectrometry data comprehensively provides molecular distributions. In this study, we focus on the information in the obtained data and use the Shannon entropy as a quantity to analyze MSI data. By calculating the Shannon entropy at each pixel on a sample, the spatial distribution of the Shannon entropy is obtained from MSI data. We found that low-entropy pixels in entropy heat maps for kidneys of mice had different structures between two ages (3 months and 31 months). Such changes cannot be visualized by conventional imaging techniques. We further propose a method to find informative molecules. As a demonstration of the proposed scheme, we identified two molecules by setting a region of interest which contained low-entropy pixels and by exploring changes of peaks in the region.
Databáze: Directory of Open Access Journals
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