Author

Ramin Hasibi

University of BergenORCID 0000-0002-6175-8195Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Research Focus:differential expression· 1 Organism:E. coli· 1 Research Focus:gene regulatory network inference· 1 Approach:graph neural network· 1 Approach:machine learning (classical)· 1 Assay:metabolomics· 1 Research Focus:variant effect prediction· 1

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Diego A. OyarzúniD· 1 shared Tom MichoeliD· 1 shared

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2024-2024 · peak 1/yr

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1 shared paperSystems Biology

Diego A. OyarzúnORCID

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1 paper

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Systems Biologynpj Systems Biology and ApplicationsPeer-reviewedMar 6, 2024

Integration of graph neural networks and genome-scale metabolic models for predicting gene essentiality

Ramin Hasibi, Tom Michoel, Diego A. Oyarzún

The paper introduces FlowGAT, a hybrid FBA-machine learning method to predict gene essentiality in E. coli by leveraging metabolic network structure and knock-out fitness data.

39 citationstop 3%

E. colimetabolomics

𝕏 PostBluesky