Author

April L. Lukowski

Scripps Institution of OceanographyORCID 0000-0003-4865-0910Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Biochemistry· 2 Bioinformatics· 1

Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Research Focus:database / resource· 2 Organism:human· 2 Assay:metabolomics· 2 Assay:metagenomics· 2 Approach:benchmark study· 1 Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1

Frequent Co-Authors

Anna E. SkripiD· 2 shared Ipsita MohantyiD· 2 shared Jasmine ZemliniD· 2 shared Pieter C. DorresteiniD· 2 shared Victoria DelerayiD· 2 shared Vincent Charron-LamoureuxiD· 2 shared Abubaker PataniD· 1 shared Abzer Kelminal Pakkir Mohamed ShahiD· 1 shared

Activity by Year

2026-2026 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 36 mutual co-author links

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2 shared papersBiochemistry

Anna E. SkripORCID

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3 papers

Recent·Most cited

BiochemistrybioRxivPreprintNov 3, 2026

Mapping bacterial bile amidation across the bile salt hydrolase family

Anna E Skrip, Swati Shyam Prasad, Igor H Wierzbicki…·April Lukowski

The paper maps bacterial bile amidation by analyzing BSH transaminase activities and identifying BBAs in human samples.

DOI 10.64898/2026.11.01.763480

humanmetabolomics

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BioinformaticsACS OmegaPeer-reviewedAug 11, 2026

Computational pipeline reveals nature's untapped reservoir of halogenating enzymes

Judit Szenei, Ashleigh J. Burke, Anne Liong…·Kai Blin

The paper develops a computational pipeline and database to annotate halogenating enzymes in genomic and metagenomic data, revealing underexplored clusters and improving predictions of microbial halogenated natural products.

DOI 10.1021/acsomega.6c02136

metagenomicsstatistical model

𝕏 PostBluesky

BiochemistrybioRxivPreprintFeb 5, 2026

A searchable metadata network graph for microbiome metabolomics

Vincent Charron‐Lamoureux, Shipei Xing, Abubaker Patan…·Pieter C. Dorrestein

The paper introduces microbiomeMASST, a metadata network graph linking metabolites across datasets, enabling cross-study analysis of microbial metabolites and their biological context.

4 citations

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