Author

Aaron A. King

Santa Fe InstituteORCID 0000-0001-6159-3207Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Organism:human· 2 Approach:statistical model· 2 Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1 Research Focus:drug response / drug discovery· 1 Approach:experimental assay· 1 Research Focus:host-pathogen & immune response· 1 Organism:mouse· 1

Frequent Co-Authors

Robert J. WoodsiD· 2 shared Andrew F. ReadiD· 1 shared Clare L. KinneariD· 1 shared Jess A. MillariD· 1 shared Jordan M. McKaigiD· 1 shared Kevin C. TracyiD· 1 shared Madeline A. E. PetersiD· 1 shared Mercedes PascualiD· 1 shared

Activity by Year

2017-2024 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 19 mutual co-author links

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2 shared papersMicrobiology

Robert J. WoodsORCID

Mutual co-authors in cluster

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3 papers

Recent·Most cited

MicrobiologyFrontiers in MalariaPeer-reviewedAug 16, 2024

Red blood cell dynamics during malaria infection challenge the assumptions of mathematical models of infection dynamics

Madeline A. E. Peters, Aaron A. King, Nina Wale

This study challenges existing mathematical models of malaria infection dynamics by showing RBC supply and clearance do not conform to common model assumptions.

1 citation

mousebulk RNA-seq

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MicrobiologybioRxivPreprintJun 3, 2024

Reversion to sensitivity explains limited transmission of resistance in a hospital pathogen

Kevin C. Tracy, Jordan M. McKaig, Clare L. Kinnear…·Robert J. Woods

The paper investigates how resistance in hospital pathogens reverts to sensitivity when antibiotic pressure is removed, finding that transmitted resistance loses less resistance than de novo resistance.

2 citations

humanexperimental assay

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Systems BiologyScience Translational MedicinePeer-reviewedOct 25, 2017

Evolution-informed forecasting of seasonal influenza A (H3N2)

Xiangjun Du, Aaron A. King, Robert J. Woods, Mercedes Pascual

The paper demonstrates a method to forecast seasonal H3N2 influenza incidence by integrating evolutionary changes with an epidemiological model, achieving accurate real-time predictions for the 2016/2017 season.

88 citationstop 4%

humanstatistical model

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