ImmCellFie：一个用户友好的基于网络的平台，可从组学数据推断代谢功能。

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

机构信息

Department of Bioengineering, UC San Diego, La Jolla, CA 92093, USA.

Renaissance Computing Institute, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27517, USA.

出版信息

STAR Protoc. 2023 Mar 17;4(1):102069. doi: 10.1016/j.xpro.2023.102069. Epub 2023 Jan 25.

DOI:10.1016/j.xpro.2023.102069

PMID:36853701

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9898792/

Abstract

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)..

摘要

了解细胞代谢在生物技术和生物医学研究中都很重要，并且对广泛的正常和病理条件都有重要影响。在这里，我们介绍了一个用户友好的基于网络的平台 ImmCellFie，它允许对从转录组或蛋白质组数据推断的代谢功能进行全面分析。我们解释了如何使用公开可用的组学数据设置运行，以及如何可视化结果。ImmCellFie 算法超越了传统的统计富集，纳入了复杂的生物学机制来量化细胞活性。有关使用和执行本方案的完整详细信息，请参阅 Richelle 等人（2021 年）。。