Tian Birui, Chen Meifeng, Liu Lunxian, Rui Bin, Deng Zhouhui, Zhang Zhengdong, Shen Tie
Key Laboratory of Information and Computing Science Guizhou Province, Guizhou Normal University, Guiyang, China.
Key Laboratory of National Forestry and Grassland Administration on Biodiversity Conservation in Karst Mountainous Areas of Southwestern China, Key Laboratory of Plant Physiology and Development Regulation, School of Life Science, Guizhou Normal University, Guiyang, China.
Front Mol Neurosci. 2022 Sep 8;15:883466. doi: 10.3389/fnmol.2022.883466. eCollection 2022.
C metabolic flux analysis (C-MFA) has emerged as a forceful tool for quantifying metabolic pathway activity of different biological systems. This technology plays an important role in understanding intracellular metabolism and revealing patho-physiology mechanism. Recently, it has evolved into a method family with great diversity in experiments, analytics, and mathematics. In this review, we classify and characterize the various branch of C-MFA from a unified perspective of mathematical modeling. By linking different parts in the model to each step of its workflow, the specific technologies of C-MFA are put into discussion, including the isotope labeling model (ILM), isotope pattern measuring technique, optimization algorithm and statistical method. Its application in physiological research in neural cell has also been reviewed.
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