Importantly, we found that c-MAF inducing protein (CMIP) protects cells from exposure to FFAs by modulating Akt signaling and we validated the role of CMIP in human pancreatic beta cells. Furthermore, we developed a new approach to prioritize genes that reflect the combined effects of exposure to harmful FFAs and genetic risk for type 2 diabetes (T2D). We identified a subset of lipotoxic monounsaturated fatty acids (MUFAs) with a distinct lipidomic profile associated with decreased membrane fluidity. Here we report the design and implementation of FALCON (Fatty Acid Library for Comprehensive ONtologies) as an unbiased, scalable and multimodal interrogation of 61 structurally diverse FFAs. Furthermore, assessing how these FFA- mediated processes interact with genetic risk for disease remains elusive. However, studies to date have assumed that a few select FFAs are representative of broad structural categories, and there are no scalable approaches to comprehensively assess the biological processes induced by exposure to diverse FFAs circulating in human plasma. Supplementary Data 1: Benchmarking performance of classifiers in CPA 2.0 versus CPA 1.0Ĭellular exposure to free fatty acids (FFA) is implicated in the pathogenesis of obesity-associated diseases. Supplementary Information: Supplementary Text 1: Manual to CellProfiler Analyst updated versions are available at /CPA We implemented an automatic build process that supports nightly updates and regular release cycles for the software. It is available as a packaged application for Mac OS X and Microsoft Windows and can be compiledįor Linux. CellProfiler AnalystĢ.0, completely rewritten in Python, builds on these features and adds enhanced supervised machine learning capabilities (Classifier),Īs well as visualization tools to overview an experiment (Plate Viewer and Image Gallery).Īvailability: CellProfiler Analyst 2.0 is free and open source, available at and from GitHub () under the BSD license. CellProfiler Analyst allows the exploration and visualization of image-based data, together with the classification of complexīiological phenotypes, via an interactive user interface designed for biologists and data scientists.
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