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The Lipid Droplet Knowledge Portal: A resource for systematic analyses of lipid droplet biology. | LitMetric

The Lipid Droplet Knowledge Portal: A resource for systematic analyses of lipid droplet biology.

Dev Cell

Department of Molecular Metabolism, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA; Department of Cell Biology, Harvard Medical School, Boston, MA 02115, USA; Howard Hughes Medical Institute, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Center on the Causes and Prevention of Cardiovascular Disease (CAP-CVD), Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA. Electronic address:

Published: February 2022

AI Article Synopsis

  • * Increased research into LDs is driven by their connection to diseases like atherosclerosis, obesity, type 2 diabetes, and hepatic steatosis, highlighting the need for comprehensive data on LD biology.
  • * The "Lipid Droplet Knowledge Portal" is an online platform that compiles high-quality datasets from human, mouse, and fly studies on LDs, offering valuable information such as transcriptional profiles and proteomics to help identify factors influencing lipid storage.

Article Abstract

Lipid droplets (LDs) are organelles of cellular lipid storage with fundamental roles in energy metabolism and cell membrane homeostasis. There has been an explosion of research into the biology of LDs, in part due to their relevance in diseases of lipid storage, such as atherosclerosis, obesity, type 2 diabetes, and hepatic steatosis. Consequently, there is an increasing need for a resource that combines datasets from systematic analyses of LD biology. Here, we integrate high-confidence, systematically generated human, mouse, and fly data from studies on LDs in the framework of an online platform named the "Lipid Droplet Knowledge Portal" (https://lipiddroplet.org/). This scalable and interactive portal includes comprehensive datasets, across a variety of cell types, for LD biology, including transcriptional profiles of induced lipid storage, organellar proteomics, genome-wide screen phenotypes, and ties to human genetics. This resource is a powerful platform that can be utilized to identify determinants of lipid storage.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9129885PMC
http://dx.doi.org/10.1016/j.devcel.2022.01.003DOI Listing

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