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:
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通讯作者:
Robasky, Kimberly
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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
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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DOI:
10.1016/j.crmeth.2021.100040
发表时间:
2021-07-26
期刊:
CELL REPORTS METHODS
影响因子:
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作者:
Richelle, Anne;Kellman, Benjamin P.;Lewis, Nathan E.
通讯作者:
Lewis, Nathan E.
DOI:
10.1038/nrmicro1949
发表时间:
2009-02
期刊:
Nature reviews. Microbiology
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影响因子:
4.3
作者:
King ZA;Dräger A;Ebrahim A;Sonnenschein N;Lewis NE;Palsson BO
通讯作者:
Palsson BO
影响因子:
4.3
作者:
Richelle, Anne;Joshi, Chintan;Lewis, Nathan E.
通讯作者:
Lewis, Nathan E.
DOI:
10.1038/nrmicro2737
发表时间:
2012-02-27
期刊:
Nature reviews. Microbiology
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