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

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 f...

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Detalles Bibliográficos
Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Protocol
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9898792/
https://www.ncbi.nlm.nih.gov/pubmed/36853701
http://dx.doi.org/10.1016/j.xpro.2023.102069
Descripción
Sumario: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)

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