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Fluxome Inc fluxome-wide association analysis (fwas)
First, we extract the organ-subnetworks from the Harvey/Harvetta multiorgan models, which were built from Recon3D, and we perform a liftover to update them to HUMAN1, the most recent human GSMM. Then, a reference flux map is computed for each organ using the GIM3E algorithm to integrate average transcript abundances and organ-specific metabolic objectives into the organ-specific metabolic subnetwork. In parallel, personalised organ-specific transcript abundances are imputed from genotype data of the INTERVAL and UK Biobank (UKB) cohorts using the models from PredictDB. Next, the quadratic metabolic transformation algorithm (qMTA) is used to integrate the organ-specific transcript abundances and reference flux distribution and compute personalised organ-specific metabolic flux maps. The resulting flux maps can be used to perform <t>FWAS</t> to complex traits or diseases such as blood metabolic features or coronary artery disease. A hypothetic representation of an organ-specific solution space, reference flux distribution, and a set of three personalised flux distributions is shown for a reaction network with three fluxes ( v x , v y and v z ).
Fluxome Wide Association Analysis (Fwas), supplied by Fluxome Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/quantile-quantile+plot+%28qq-plot%29/pmc09708841-176-2-2?v=Fluxome+Inc
Average 90 stars, based on 1 article reviews
fluxome-wide association analysis (fwas) - by Bioz Stars, 2026-07
90/100 stars

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1) Product Images from "Genetically personalised organ-specific metabolic models in health and disease"

Article Title: Genetically personalised organ-specific metabolic models in health and disease

Journal: Nature Communications

doi: 10.1038/s41467-022-35017-7

First, we extract the organ-subnetworks from the Harvey/Harvetta multiorgan models, which were built from Recon3D, and we perform a liftover to update them to HUMAN1, the most recent human GSMM. Then, a reference flux map is computed for each organ using the GIM3E algorithm to integrate average transcript abundances and organ-specific metabolic objectives into the organ-specific metabolic subnetwork. In parallel, personalised organ-specific transcript abundances are imputed from genotype data of the INTERVAL and UK Biobank (UKB) cohorts using the models from PredictDB. Next, the quadratic metabolic transformation algorithm (qMTA) is used to integrate the organ-specific transcript abundances and reference flux distribution and compute personalised organ-specific metabolic flux maps. The resulting flux maps can be used to perform FWAS to complex traits or diseases such as blood metabolic features or coronary artery disease. A hypothetic representation of an organ-specific solution space, reference flux distribution, and a set of three personalised flux distributions is shown for a reaction network with three fluxes ( v x , v y and v z ).
Figure Legend Snippet: First, we extract the organ-subnetworks from the Harvey/Harvetta multiorgan models, which were built from Recon3D, and we perform a liftover to update them to HUMAN1, the most recent human GSMM. Then, a reference flux map is computed for each organ using the GIM3E algorithm to integrate average transcript abundances and organ-specific metabolic objectives into the organ-specific metabolic subnetwork. In parallel, personalised organ-specific transcript abundances are imputed from genotype data of the INTERVAL and UK Biobank (UKB) cohorts using the models from PredictDB. Next, the quadratic metabolic transformation algorithm (qMTA) is used to integrate the organ-specific transcript abundances and reference flux distribution and compute personalised organ-specific metabolic flux maps. The resulting flux maps can be used to perform FWAS to complex traits or diseases such as blood metabolic features or coronary artery disease. A hypothetic representation of an organ-specific solution space, reference flux distribution, and a set of three personalised flux distributions is shown for a reaction network with three fluxes ( v x , v y and v z ).

Techniques Used: Transformation Assay



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