Author

Austin G. Meyer

Primary ORCID profile (0000-0002-0581-800X · 4 papers)Unclaimed ORCID profile · follow to get notified of new preprints

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Austin G. MeyeriD4 papers · Baylor College of Medicine

Biology Disciplines

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Evolutionary Biology· 2 Systems Biology· 1

Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Research Focus:chromatin & epigenetic regulation· 1 Approach:deep learning· 1 Organism:E. coli· 1 Assay:metabolomics· 1 Research Focus:protein folding & dynamics· 1 Assay:protein structure· 1 Organism:virus· 1

Frequent Co-Authors

Claus O. WilkeiD· 2 shared Stephanie J. SpielmaniD· 2 shared Amir Shahmoradi· 1 shared Claus O Wilke· 1 shared Daniel Segrè· 1 shared Dariya K. SydykovaiD· 1 shared Eleisha L. Jackson· 1 shared Eric T. Dawson· 1 shared

Activity by Year

2014-2014 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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2 shared papersEvolutionary Biology

Claus O. WilkeORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Increased evolutionary rate in the 2014 West African Ebola outbreak is due to transient polymorphism and not positive selection

Stephanie J. Spielman, Austin G. Meyer, Claus O. Wilke

The paper challenges claims of rapid Ebola virus evolution during the 2014 outbreak, attributing the apparent increased substitution rate to technical artifacts rather than adaptive evolution.

bioRxiv · Nov 19, 2014 · PreprintEvolutionary Biology

Predicting growth conditions from internal metabolic fluxes in an in-silico model of E. coli

Viswanadham Sridhara, Austin G. Meyer, Piyush Rai, Jeffrey E. Barrick, Pradeep Ravikumar, Daniel Segrè, Claus O Wilke

The paper predicts growth conditions of E. coli from metabolic fluxes using regularized multinomial regression and finds that metabolic end products and a small number of reactions are sufficient for accurate prediction.

bioRxiv · Oct 14, 2014Systems Biology

Predicting evolutionary site variability from structure in viral proteins: buriedness, packing, flexibility, and design

Amir Shahmoradi, Dariya K. Sydykova, Stephanie J. Spielman, Eleisha L. Jackson, Eric T. Dawson, Austin G. Meyer, Claus O. Wilke

The paper evaluates how structural properties predict evolutionary sequence variation in viral proteins and finds that buriedness and packing density are better predictors than flexibility or design-based measures.

bioRxiv · Jul 21, 2014Evolutionary Biology