Author

Rachel Ki

University of California, Los Angeles

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

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Systems Biology· 1

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Research Focus:benchmarking· 1 Approach:deep learning· 1 Assay:metabolomics· 1 Research Focus:software / tool· 1 Research Focus:variant effect prediction· 1

Frequent Co-Authors

Glenn NurwonoiD· 1 shared Junyoung O. ParkiD· 1 shared Kartikeya Pande· 1 shared Pin‐Kuang LaiiD· 1 shared Richard C. LawiD· 1 shared Samantha O’KeeffeiD· 1 shared

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2023-2023 · peak 1/yr

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6 top collaborators · 15 mutual co-author links

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1 shared paperSystems Biology

Glenn NurwonoORCID

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1 paper

Recent·Most cited

Accurate and rapid determination of metabolic flux by deep learning of isotope patterns

Richard C. Law, Kartikeya Pande, Samantha O’Keeffe, Glenn Nurwono, Rachel Ki, Pin‐Kuang Lai, Junyoung O. Park

This paper introduces ML-Flux, a deep learning framework for accurately and rapidly determining metabolic flux from isotope patterns, outperforming existing methods in speed and accuracy.

bioRxiv · Nov 6, 2023 · PreprintSystems Biology