CeCaFLUX: the first web server for standardized and visual instationary 13C metabolic flux analysis-Reference-Cited by-同舟云学术

CeCaFLUX: the first web server for standardized and visual instationary 13C metabolic flux analysis

Published:2022-05-20 Issue:13 Volume:38 Page:3481-3483
ISSN:1367-4803
Container-title:Bioinformatics
language:en
Short-container-title:

Author:

Liu Zhentao¹²,Zhang Zhengdong¹³,Liang Sheng³,Chen Zhen⁴,Xie Xiaoyao¹²,Shen Tie¹^ORCID

Affiliation:

1. Key Laboratory of Information and Computing Science Guizhou Province, Guizhou Normal University , Guiyang, Guizhou, China

2. College of Computer Science and Technology, Guizhou University , Guiyang, Guizhou, China

3. College of Mathematics and Information Science, Guiyang University , Guiyang, Guizhou, China

4. School of Mathematical Science, Guizhou Normal University , Guiyang, Guizhou, China

Abstract

Abstract Summary The number of instationary 13C-metabolic flux (INST-MFA) studies grows every year, making it more important than ever to ensure the clarity, standardization and reproducibility of each study. We proposed CeCaFLUX, the first user-friendly web server that derives metabolic flux distribution from instationary 13C-labeled data. Flux optimization and statistical analysis are achieved through an evolutionary optimization in a parallel manner. It can visualize the flux optimizing process in real-time and the ultimate flux outcome. It will also function as a database to enhance the consistency and to facilitate sharing of flux studies. Availability and implementation CeCaFLUX is freely available at https://www.cecaflux.net, the source code can be downloaded at https://github.com/zhzhd82/CeCaFLUX. Supplementary information Supplementary data are available at Bioinformatics online.

Funder

Guizhou Provincial Science and Technology Projects

National Science Foundation of China

NSFC

Science and Technology Foundation of Guizhou Province

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

Link

https://academic.oup.com/bioinformatics/advance-article-pdf/doi/10.1093/bioinformatics/btac341/43845928/btac341.pdf

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