Author

Monica B. Emelko

University of WaterlooORCID 0000-0002-8295-0071Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Assay:metagenomics· 3 Approach:statistical model· 3 Research Focus:benchmarking· 2 Research Focus:cell type annotation· 1 Research Focus:gene regulatory network inference· 1

Frequent Co-Authors

Ellen S. CameroniD· 3 shared Kirsten M. MülleriD· 3 shared Philip J. SchmidtiD· 2 shared Benjamin J.-M. TremblayiD· 1 shared Cody C CollisiD· 1 shared Jozef I. NissimoviD· 1 shared Nicolas TromasiD· 1 shared

Activity by Year

2021-2026 · peak 1/yr

Co-Author Collaboration Network

7 top collaborators · 15 mutual co-author links

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3 shared papersBioinformatics

Ellen S. CameronORCID

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3 papers

Recent·Most cited

Cell-associated viral community composition and its functional potential in a dimictic lake on the Canadian Shield

Cody C Collis, Ellen S. Cameron, Kirsten M. Müller, Monica B. Emelko, Nicolas Tromas, Jozef I. Nissimov

The paper characterizes the seasonal dynamics of cell-associated viral communities in Big Turkey Lake, identifies their functional roles through auxiliary metabolic genes, and reconstructs viral genomes.

Frontiers in Microbiology · Oct 27, 2026Peer-reviewedMicrobiology

Ensuring that fundamentals of quantitative microbiology are reflected in microbial diversity analyses based on next-generation sequencing

Philip J. Schmidt, Ellen S. Cameron, Kirsten M. Müller, Monica B. Emelko

The paper applies statistical methods from quantitative microbiology to improve diversity analysis of amplicon sequencing data by addressing random error and model limitations.

Frontiers in Microbiology · Mar 1, 2022Peer-reviewedBioinformatics

To rarefy or not to rarefy: Enhancing diversity analysis of microbial communities through next-generation sequencing and rarefying repeatedly

Ellen S. Cameron, Philip J. Schmidt, Benjamin J.-M. Tremblay, Monica B. Emelko, Kirsten M. Müller

The paper evaluates the use of repeated rarefying to normalize amplicon sequencing data for microbial community diversity analysis, showing its utility in representing sequence proportions and characterizing rarefaction effects.

Scientific Reports · Nov 16, 2021Peer-reviewedBioinformatics