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

Summary: 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 me...

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Bibliographic Details
Main Authors: Helen O. Masson, David Borland, Jason Reilly, Adrian Telleria, Shalki Shrivastava, Matt Watson, Luthfi Bustillos, Zerong Li, Laura Capps, Benjamin P. Kellman, Zachary A. King, Anne Richelle, Nathan E. Lewis, Kimberly Robasky
Format: Article
Language:English
Published: Elsevier 2023-03-01
Series:STAR Protocols
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Online Access:http://www.sciencedirect.com/science/article/pii/S2666166723000278
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Summary:Summary: 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).1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.
ISSN:2666-1667