Semi-Automatic Detection of Errors in Genome-Scale Metabolic Models.

Devlin M Campbell Justin Reimertz Daniel Segrè Juan Ignacio Fuxman Bass

Published in: bioRxiv : the preprint server for biology (2024)

MACAW is capable of identifying inaccuracies of varying severity in a wide range of GSMMs. Correcting these errors can measurably improve the predictive capacity of a GSMM. The relative prevalence of each type of error we identify in a large collection of GSMMs could help shape future efforts for further automation of error correction and GSMM creation.

Keyphrases

patient safety
adverse drug
risk factors
quality improvement
current status
deep learning
machine learning
loop mediated isothermal amplification
real time pcr
genome wide
label free
emergency department
dna methylation
neural network
electronic health record