Data dimensionality reduction technique for clustering problem of metabolomics data

Data dimensionality reduction technique for clustering problem of metabolomics data

In metabolomics studies, independent analyses or replicating the metabolite concentration measurements are often performed to anticipate errors. On the other hand, the size of the dataset is increasing. For clustering purposes, obtaining representative information chemically from independent analyse...

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Bibliographic Details
Main Authors: Rustam, Agus Yodi Gunawan, Made Tri Ari Penia Kresnowati
Format: Article
Language:English
Published: Elsevier 2022-06-01
Series:Heliyon
Subjects:
Metabolomics
Chemometric
Metabolite data
Dimensionality reduction
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Online Access:http://www.sciencedirect.com/science/article/pii/S2405844022010039

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http://www.sciencedirect.com/science/article/pii/S2405844022010039

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