Author

D. L. Weller

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Microbiology· 3 Ecology· 1

Signature Assays, Organisms & Methods

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Approach:statistical model· 4 Assay:metagenomics· 3 Research Focus:ecology & biodiversity· 2 Research Focus:host-pathogen & immune response· 2 Research Focus:benchmarking· 1 Approach:deep learning· 1 Research Focus:differential expression· 1

Frequent Co-Authors

D. E. Weller· 2 shared M. Wiedmann· 2 shared B. G. Rahm· 1 shared C. M. Murphy· 1 shared C. Rock· 1 shared E. Ganda· 1 shared E. Mudrak· 1 shared J. Kovac· 1 shared

Activity by Year

2020-2022 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 17 mutual co-author links

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2 shared papersEcology

D. E. Weller

Mutual co-authors in cluster

Author profile →

4 papers

Recent·Most cited

Structural equation models suggest that on-farm non-crop vegetation removal is not associated with improved food safety outcomes but is linked to impaired water quality

D. L. Weller, T. Love, D. E. Weller, C. M. Murphy, B. G. Rahm, M. Wiedmann

bioRxiv · Sep 19, 2022 · PreprintEcology

Conditional forest models built using metagenomic data could accurately predict Salmonella contamination in Northeastern streams

T. Chung, R. Yan, D. L. Weller, J. Kovac

This paper uses metagenomic data from Northeastern streams to predict Salmonella contamination using conditional forest models, finding Aeromonas and Tabrizicola as key indicators.

bioRxiv · Jul 11, 2022 · PreprintMicrobiology

Scale of analysis drives the observed ratio of spatial to non-spatial variance in microbial water quality: insights from two decades of citizen science data

D. L. Weller, D. E. Weller, L. K. Strawn, T. M. T. Love

The paper quantifies spatial and temporal variance in fecal indicator bacteria levels across different scales using citizen science data and identifies environmental factors influencing these levels.

bioRxiv · Feb 1, 2022Microbiology

Complex interactions between weather, and microbial and physiochemical water quality impact the likelihood of detecting foodborne pathogens in agricultural water

D. L. Weller, N. Brassill, C. Rock, R. Ivanek, E. Mudrak, S. Roof, E. Ganda, M. Wiedmann

This study examines how environmental factors and microbial indicators influence pathogen detection in agricultural water, finding that E. coli levels alone are not sufficient to predict food safety risks.

bioRxiv · Jan 2, 2020Microbiology

D. L. Weller · henhao