ImmCellFie: A user-friendly web-based platform to infer metabolic function from omics data.

ImmCellFie: A user-friendly web-based platform to infer metabolic function from omics data.
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DOI:
10.1016/j.xpro.2023.102069
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发表时间:
2023-03-17
期刊:
影响因子:
--
通讯作者:
Robasky, Kimberly
Robasky, Kimberly
中科院分区:
其他
文献类型:
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作者:
Masson, Helen O.;Borland, David;Reilly, Jason;Telleria, Adrian;Shrivastava, Shalki;Watson, Matt;Bustillos, Luthfi;Li, Zerong;Capps, Laura;Kellman, Benjamin P.;King, Zachary A.;Richelle, Anne;Lewis, Nathan E.;Robasky, Kimberly

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了解细胞代谢在生物技术和生物医学研究中非常重要,并且在广泛的正常和病理条件下具有重要意义。在这里,我们介绍了用户友好的基于网络的平台ImmCellFie,它允许从转录组学或蛋白质组学数据推断的代谢功能的综合分析。我们解释了如何使用公开的组学数据建立运行,以及如何可视化结果。ImmCellFie算法超越了传统的统计富集,并结合了复杂的生物学机制来量化细胞活性。有关本方案使用和执行的完整详细信息,请参见Richelle等人。(2021年)。ImmCellFie提供了从组学数据推断代谢功能的平台,LeucomeMs提供了无需特殊用户培训的机械见解。可视化工具套件允许用户交互式地探索结果。API可用于通过笔记本通过HTTP与ImmCellFie接口(例如,yter)。出版商注:进行任何实验方案都需要遵守当地实验室安全和伦理的机构指南。了解细胞代谢在生物技术和生物医学研究中非常重要,并且在广泛的正常和病理条件下具有重要意义。在这里,我们介绍了用户友好的基于网络的平台ImmCellFie,它允许从转录组学或蛋白质组学数据推断的代谢功能的综合分析。我们解释了如何使用公开的组学数据建立运行,以及如何可视化结果。ImmCellFie算法超越了传统的统计富集,并结合了复杂的生物学机制来量化细胞活性。
Understanding cellular metabolism is important across biotechnology and biomedical research and has critical implications in a broad range of normal and pathological conditions. Here, we introduce the user-friendly web-based platform ImmCellFie, which allows the comprehensive analysis of metabolic functions inferred from transcriptomic or proteomic data. We explain how to set up a run using publicly available omics data and how to visualize the results. The ImmCellFie algorithm pushes beyond conventional statistical enrichment and incorporates complex biological mechanisms to quantify cell activity. For complete details on the use and execution of this protocol, please refer to Richelle et al. (2021). ImmCellFie provides a platform to infer metabolic function from omics data Leverages GeMs to provide mechanistic insights with no special user training required The suite of visualization tools allows users to interactively explore results API is available to interface with ImmCellFie over HTTP via notebooks (e.g., Jupyter). Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics. Understanding cellular metabolism is important across biotechnology and biomedical research and has critical implications in a broad range of normal and pathological conditions. Here, we introduce the user-friendly web-based platform ImmCellFie, which allows the comprehensive analysis of metabolic functions inferred from transcriptomic or proteomic data. We explain how to set up a run using publicly available omics data and how to visualize the results. The ImmCellFie algorithm pushes beyond conventional statistical enrichment and incorporates complex biological mechanisms to quantify cell activity.
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