Author

Olivia L. Riedling

Vanderbilt UniversityORCID 0000-0003-2735-0513Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Ecology· 1 Evolutionary Biology· 1 Microbiology· 1

Signature Assays, Organisms & Methods

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Organism:fungi (other)· 2 Assay:metabolomics· 2 Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Research Focus:ecology & biodiversity· 1 Approach:experimental assay· 1 Research Focus:host-pathogen & immune response· 1

Frequent Co-Authors

Antonis RokasiD· 3 shared Adiyantara GumilangiD· 2 shared David C. RinkeriD· 2 shared Huzefa A. RajaiD· 2 shared Karin SteffeniD· 2 shared Manuel Rangel‐GrimaldoiD· 2 shared Nicholas H. OberliesiD· 2 shared Thomas J. C. SautersiD· 2 shared

Activity by Year

2024-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 44 mutual co-author links

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3 shared papersEvolutionary Biology

Antonis RokasORCID

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3 papers

Recent·Most cited

Evolutionary BiologybioRxivPreprintJul 20, 2026

Opportunistic pathogenicity in fungi can transcend species boundaries

David C. Rinker, Thomas J. C. Sauters, Adiyantara Gumilang…·Antonis Rokas

This study compares phenotypic, metabolomic, and genomic variation between two Aspergillus species to determine factors distinguishing opportunistic pathogens from non-pathogens.

DOI 10.64898/2026.07.02.736111

mousemetabolomics

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MicrobiologyOrganic & Biomolecular ChemistryPeer-reviewedJan 1, 2026

An integrative genomic and chemical similarity approach linking fungal secondary metabolites and biosynthetic gene clusters

Karin Steffen, Manuel Rangel‐Grimaldo, Thomas J. C. Sauters…·Antonis Rokas

The paper links fungal secondary metabolites to their biosynthetic gene clusters using genomic and chemical similarity, identifying 22 known pairs and hypothesizing 38 others in Aspergillus fischeri.

4 citations

fungi (other)metabolomics

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EcologyCurrent BiologyPeer-reviewedDec 3, 2024

Global patterns of species diversity and distribution in the biomedically and biotechnologically important fungal genus Aspergillus

Olivia L. Riedling, Kyle T. David, Antonis Rokas

The paper uses machine learning to analyze Aspergillus species distribution and predicts climate change impacts on their ranges and diversity.

12 citations

fungi (other)machine learning (classical)

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