Author

Mohammad Moshfeghnia

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University of TehranORCID 0009-0001-7217-2317Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1

Signature Assays, Organisms & Methods

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Approach:machine learning (classical)· 1

Activity by Year

2023-2023 · peak 1/yr

1 paper

Recent·Most cited

BioinformaticsbioRxivPreprintNov 14, 2023

AI-Driven Insights into the complexities of Chinese hamster ovary cells death in order to optimize production processes.

Mohammad Moshfeghnia

The paper uses AI and machine learning to identify key targets in signaling pathways related to CHO cell death, aiming to optimize biopharmaceutical production.

1 citation

machine learning (classical)

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