Author

Andrew K. Benson

University of Nebraska–LincolnORCID 0000-0001-6330-0252Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

Click to filter author papers

Bioinformatics· 2 Genomics· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Approach:statistical model· 3 Organism:bacteria (other)· 2 Research Focus:database / resource· 2 Research Focus:variant calling· 2 Assay:whole-genome sequencing· 2 Research Focus:benchmarking· 1 Approach:experimental assay· 1 Research Focus:GWAS / association mapping· 1

Frequent Co-Authors

Jitender S. DeoguniD· 2 shared João Carlos Gomes NetoiD· 2 shared Natasha Pavlovikj· 2 shared Bo Peng· 1 shared James C. SchnableiD· 1 shared Mackenzie ZwieneriD· 1 shared Mallory J. Suhr Van HauteiD· 1 shared Michael C. TrossiD· 1 shared

Activity by Year

2021-2023 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 24 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

2 shared papersBioinformatics

Jitender S. DeogunORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

GenomicsbioRxivPreprintSep 20, 2023

Grain Utilization by the Gut Microbiome as a Human Health Phenotype to Identify Multiple Effect Loci in Genome-Wide Association Studies of Sorghum bicolor

Nate Korth, Qinnan Yang, Mallory J. Suhr Van Haute…·Andrew K. Benson

This study identifies genetic loci in sorghum that influence human gut microbiome composition through in vitro fermentation of grain.

DOI 10.1101/2023.09.20.558616

humanmetagenomics

𝕏 PostBluesky

BioinformaticsbioRxivPreprintOct 28, 2021

Systems-based approach for optimization of a scalable bacterial ST mapping assembly-free algorithm

Natasha Pavlovikj, João Carlos Gomes Neto, Jitender S. Deogun, Andrew K. Benson

The paper optimizes an assembly-free algorithm for bacterial ST mapping and integrates it into a scalable platform for genomic epidemiology.

DOI 10.1101/2021.10.28.466354

bacteria (other)whole-genome sequencing

𝕏 PostBluesky

BioinformaticsPeerJPeer-reviewedMay 21, 2021

ProkEvo: an automated, reproducible, and scalable framework for high-throughput bacterial population genomics analyses

Natasha Pavlovikj, João Carlos Gomes Neto, Jitender S. Deogun, Andrew K. Benson

ProkEvo is a scalable framework for bacterial population genomics that automates analyses of WGS data and generates population-based genotypes and annotations.

7 citations

bacteria (other)whole-genome sequencing

𝕏 PostBluesky