人类代谢化学计量模型的标准化:挑战和方向

Marilena D. A. Pantziri, M. Klapa
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引用次数: 1

摘要

基因组规模的代谢网络模型在系统生物学研究中具有重要意义,因为它们用于代谢活动动力学研究,并在多组学研究中提供代谢水平的表示。特别是对人类来说,准确的代谢网络重建在生物医学研究和药物发现中具有重要意义。今天,人类代谢网络作为一个整体及其组织特异性版本存在许多实例。其中一些是对同一研究团队重建的模型的改进更新,而另一些是不同团队模型的组合,目的是包括基因组注释和组学数据集的所有可用信息。人类化学计量模型的一个主要挑战是重建方法、表示格式和模型库的标准化。化学计量模型标准化将使人们能够有根据地选择更符合研究目标的模型,直接比较各种通量分析研究的结果,并确定需要重新考虑和更新的人类基因组和蛋白质组注释的模型部分。与人类基因组一致的标准化人类代谢模型将是多组学研究中非常有用的工具,使代谢与基因调控和蛋白质相互作用网络能够直接一致地整合。在这项工作中,我们对当前人类代谢化学计量模型的收集进行了全面的概述,描述了当前在各种模型库的背景下直接比较和比对的问题,揭示了标准化需求,并提出了潜在的解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Standardization of Human Metabolic Stoichiometric Models: Challenges and Directions
Genome-scale metabolic network models are of great importance in systems biology research, as they are used in metabolic activity dynamics studies and provide the metabolic level representation in multi-omic investigations. Especially for human, accurate metabolic network reconstruction is important in biomedical research and drug discovery. Today, there exist many instances of the human metabolic network as a whole and in its tissue-specific versions. Some are improved updates of models reconstructed from the same research team, while others are combinations of models from various teams, in an effort to include all available information from genome annotation and omic datasets. A major challenge regarding the human stoichiometric models in particular is the standardization of the reconstruction methods, representation formats and model repositories. Stoichiometric model standardization will enable the educated selection of the model that better fits the goals of a study, the direct comparison of results from various flux analysis studies and the identification of model sections that require reconsideration and updating with respect to the annotation of the human genome and proteome. Standardized human metabolic models aligned to the human genome will be a very useful tool in multi-omic studies, enabling the direct and consistent integration of the metabolic with the gene regulation and protein interaction networks. In this work, we provide a thorough overview of the current collection of human metabolic stoichiometric models, describe the current issues regarding their direct comparison and alignment in the context of the various model repositories, exposing the standardization needs, and propose potential solutions.
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