Using Interactive Time-series Cluster Analysis to Relate Metabolomic Data with Perturbed Pathways
Asian Journal of Research in Biochemistry · pp. 18–26 · Published 27 Jun 2023
10.9734/ajrb/2023/v12i4242Abstract
The study conducted on interactive time-series cluster analysis has shed light on the dynamic nature of the interaction that exists between metabolites and the activities that occur within living organisms. Integration of metabolomic data with pathways that had been disrupted was the method that was used to achieve this goal. We investigated the significance of metabolomics in biological systems, the fundamentals and applications of time-series cluster analysis, and the connection between metabolomic data and pathways that have been altered in the various sections of this research paper, such as the introduction, the literature review, the methodology, the results, the discussion, and the recommendations. These sections include: the introduction; the literature review; the methodology; the results; the discussion; and the recommendations. The introduction, the literature review, the methodology, the results, the discussion, and the suggestions are included in these parts.
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Cited by 4
Qi Li, Hong-Zhou Chen, Peng Wu · LWT · 2026
A. Panara, E. Gikas, Anastasia Koupa · Molecules · 2023
Zhengyan Huang, Chi Wang · Metabolites · 2022
D. Hao, Jiangsong Bai, Jianyong Du · Metabolites · 2021
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