Author

Kristopher Kieft

University of Wisconsin–MadisonORCID 0000-0002-9120-1961Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 4 Synthetic Biology· 1

Signature Assays, Organisms & Methods

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Assay:metagenomics· 5 Approach:statistical model· 4 Organism:bacteria (other)· 2 Research Focus:benchmarking· 2 Research Focus:database / resource· 2 Research Focus:gene regulatory network inference· 2 Organism:human· 2 Research Focus:software / tool· 2

Frequent Co-Authors

Karthik AnantharamaniD· 5 shared Zhichao ZhouiD· 2 shared Adam M. BreisteriD· 1 shared Alyssa AdamsiD· 1 shared Anthony MegeriD· 1 shared Elise S. CowleyiD· 1 shared Kyle K. NishikawaiD· 1 shared Lindsay KalaniD· 1 shared

Activity by Year

2020-2025 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 19 mutual co-author links

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5 shared papersBioinformatics

Karthik AnantharamanORCID

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5 papers

Recent·Most cited

Synthetic BiologyScience AdvancesPeer-reviewedApr 18, 2025

Engineering bacteriophages through deep mining of metagenomic motifs

Phil Huss, Kristopher Kieft, Anthony Meger…·Srivatsan Raman

This paper introduces Meta-SIFT, a method to discover functional sequence motifs in metagenomes to engineer bacteriophage activity, demonstrating its utility in creating variants with novel host specificity.

19 citationstop 1%

bacteria (other)metagenomics

𝕏 PostBluesky

BioinformaticsNucleic Acids ResearchPeer-reviewedApr 22, 2022

vRhyme enables binning of viral genomes from metagenomes

Kristopher Kieft, Alyssa Adams, Rauf Salamzade…·Karthik Anantharaman

vRhyme is a software tool that bins viral genomes from metagenomes, producing more complete and uncontaminated viral metagenome-assembled genomes (vMAGs) than existing methods.

122 citationstop 1%

humanmetagenomics

𝕏 PostBluesky

BioinformaticsmSystemsPeer-reviewedMar 24, 2022

Deciphering active prophages from metagenomes

Kristopher Kieft, Karthik Anantharaman

PropagAtE identifies active prophages in metagenomes by analyzing read coverage ratios, revealing distinct activation patterns across environments.

77 citationstop 1%

humanmouse

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BioinformaticsMicrobiomePeer-reviewedFeb 16, 2022

METABOLIC: High-throughput profiling of microbial genomes for functional traits, biogeochemistry, and community-scale metabolic networks

Zhichao Zhou, Patricia Q. Tran, Adam M. Breister…·Karthik Anantharaman

METABOLIC is a software tool for analyzing microbial genomes to predict metabolic functions, interactions, and contributions to biogeochemical cycles, showing better performance than existing tools.

668 citationstop 1%

metagenomicsstatistical model

𝕏 PostBluesky

BioinformaticsMicrobiomePeer-reviewedJun 10, 2020

VIBRANT: Automated recovery, annotation and curation of microbial viruses, and evaluation of virome function from genomic sequences

Kristopher Kieft, Zhichao Zhou, Karthik Anantharaman

VIBRANT improves virus recovery and virome function analysis from metagenomes, outperforming existing tools in accuracy and completeness.

1,133 citationstop 1%

metagenomicsmachine learning (classical)

𝕏 PostBluesky