Author

Megan L. Matthews

University of Illinois Urbana-ChampaignORCID 0000-0002-5513-9320Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Plant Biology· 2 Systems Biology· 2

Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Research Focus:metabolism & bioenergetics· 2 Organism:plant (other)· 2 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:development & morphogenesis· 1 Approach:mechanistic / dynamical model· 1 Assay:metabolomics· 1

Frequent Co-Authors

Joshua A. M. KasteiD· 2 shared Rourou JiiD· 2 shared Cranos WilliamsiD· 1 shared Edward B. LochockiiD· 1 shared Jack P. WangiD· 1 shared Justin M. McGrathiD· 1 shared Patrick William SydowiD· 1 shared Ronald R. SederoffiD· 1 shared

Activity by Year

2020-2026 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 13 mutual co-author links

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2 shared papersPlant Biology

Joshua A. M. KasteORCID

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4 papers

Recent·Most cited

Plant BiologyMetabolic EngineeringPeer-reviewedSep 15, 2026

Kinetic model of a determinate legume root nodule reveals plant metabolic characteristics for more efficient nitrogen fixation symbiosis

Rourou Ji, Joshua A. M. Kaste, Megan L. Matthews

The paper develops a kinetic model of legume root nodule metabolism to identify metabolic targets for improving nitrogen fixation efficiency and rate.

DOI 10.1016/j.ymben.2026.102553

metabolomicsstatistical model

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Plant BiologybioRxivPreprintAug 28, 2026

Integrating carbon utilization and transport processes into a crop growth model enables the prediction of emergent soybean carbon allocation behavior

Ximin Piao, Edward B. Lochocki, Justin M. McGrath, Megan L. Matthews

The paper integrates carbon utilization and transport processes into a crop growth model to predict soybean carbon allocation behavior under varying conditions.

DOI 10.64898/2026.08.27.747615

plant (other)bulk RNA-seq

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Systems BiologyPLANT PHYSIOLOGYPeer-reviewedMay 30, 2026

Metabolic modeling predicts synergistic growth benefits between arbuscular mycorrhizal fungi and theoretical N2-fixing rhizobia symbiosis in maize

Joshua A. M. Kaste, Rourou Ji, Patrick William Sydow…·Megan L. Matthews

The paper uses metabolic modeling to predict growth benefits of combining arbuscular mycorrhizal fungi and hypothetical N2-fixing rhizobia in maize, finding synergies under nutrient limitation and antagonism under nutrient sufficiency.

DOI 10.1093/plphys/kiag327

plant (other)statistical model

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Systems BiologyPLoS Computational BiologyPeer-reviewedApr 10, 2020

Modeling cross-regulatory influences on monolignol transcripts and proteins under single and combinatorial gene knockdowns in Populus trichocarpa

Megan L. Matthews, Jack P. Wang, Ronald R. Sederoff…·Cranos Williams

The paper develops a computational model to estimate monolignol transcript and protein abundances under gene knockdowns, showing improved accuracy in predicting responses to single and combinatorial perturbations.

18 citations

statistical model

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