利用系统生物学方法确定微藻类胡萝卜素生物合成途径的特征

IF 2.3 Q3 BIOCHEMISTRY & MOLECULAR BIOLOGY
Bahman Panahi , Nahid Hosseinzadeh Gharajeh , Hossein Mohammadzadeh Jalaly , Mohammad Amin Hejazi
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引用次数: 0

摘要

系统生物学是一个跨学科领域,旨在从系统层面了解复杂的生物过程。由高通量全息技术驱动的数据可用于研究不同条件下代谢物产生的基础机制,从而利用这些知识构建调控网络、蛋白质网络、代谢模型,并对微藻类株进行工程改造,以提高目标代谢物的产量。在本研究中,我们全面回顾了应用这些技术表征微藻类胡萝卜素生物合成途径的最新进展。此外,我们还全面讨论了如何利用网络分析、荟萃分析和机器学习模型等综合方法来解读类胡萝卜素生物合成途径的复杂性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Harnessing systems biology approach for characterization of carotenoid biosynthesis pathways in microalgae

Systems biology is an interdisciplinary field that aims to understand complex biological processes at the system level. The data, driven by high-throughput omics technologies, can be used to study the underpinning mechanisms of metabolite production under different conditions to harness this knowledge for the construction of regulatory networks, protein networks, metabolic models, and engineering of strains with enhanced target metabolite production in microalgae. In the current study, we comprehensively reviewed the recent progress in the application of these technologies for the characterization of carotenoid biosynthesis pathways in microalgae. Moreover, harnessing integrated approaches such as network analysis, meta-analysis, and machine learning models for deciphering the complexity of carotenoid biosynthesis pathways were comprehensively discussed.

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来源期刊
Biochemistry and Biophysics Reports
Biochemistry and Biophysics Reports Biochemistry, Genetics and Molecular Biology-Biophysics
CiteScore
4.60
自引率
0.00%
发文量
191
审稿时长
59 days
期刊介绍: Open access, online only, peer-reviewed international journal in the Life Sciences, established in 2014 Biochemistry and Biophysics Reports (BB Reports) publishes original research in all aspects of Biochemistry, Biophysics and related areas like Molecular and Cell Biology. BB Reports welcomes solid though more preliminary, descriptive and small scale results if they have the potential to stimulate and/or contribute to future research, leading to new insights or hypothesis. Primary criteria for acceptance is that the work is original, scientifically and technically sound and provides valuable knowledge to life sciences research. We strongly believe all results deserve to be published and documented for the advancement of science. BB Reports specifically appreciates receiving reports on: Negative results, Replication studies, Reanalysis of previous datasets.
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