Author

D. Moulton

Los Alamos National LaboratoryORCID 0000-0002-9456-0871Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Systems Biology· 2

Signature Assays, Organisms & Methods

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Approach:statistical model· 2 Organism:bacteria (other)· 1 Research Focus:benchmarking· 1 Approach:machine learning (classical)· 1 Assay:metabolomics· 1

Frequent Co-Authors

Hyun‐Seob SongiD· 2 shared Joon‐Yong LeeiD· 2 shared Tim ScheibeiD· 2 shared William C. NelsoniD· 2 shared Xingyuan CheniD· 2 shared Christopher S. HenryiD· 1 shared Emily B. GrahamiD· 1 shared Firnaaz AhamediD· 1 shared

Activity by Year

2020-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 39 mutual co-author links

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2 shared papersSystems Biology

Hyun‐Seob SongORCID

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2 papers

Recent·Most cited

Coupling Flux Balance Analysis with Reactive Transport Modeling through Machine Learning for Rapid and Stable Simulation of Microbial Metabolic Switching

Hyun‐Seob Song, Firnaaz Ahamed, Joon‐Yong Lee, Christopher S. Henry, Janaka N. Edirisinghe, William C. Nelson, Xingyuan Chen, D. Moulton, Tim Scheibe

The paper develops an ANN-based reduced-order model to accelerate FBA integration with RTMs, enabling efficient simulation of microbial metabolic switching in Shewanella oneidensis.

Scientific Reports · Feb 19, 2025Peer-reviewedSystems Biology

Representing Organic Matter Thermodynamics in Biogeochemical Reactions via Substrate-Explicit Modeling

Hyun‐Seob Song, James Stegen, Emily B. Graham, Joon‐Yong Lee, Vanessa A. Garayburu‐Caruso, William C. Nelson, Xingyuan Chen, D. Moulton, Tim Scheibe

This paper introduces a new biogeochemical modeling approach that explicitly represents organic matter thermodynamics to improve predictions of microbial degradation processes and their environmental impacts.

Frontiers in Microbiology · Oct 23, 2020Peer-reviewedSystems Biology