Author

Kaixin Hu

Helmholtz Centre for Infection ResearchORCID 0009-0007-3307-3395Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Assay:whole-genome sequencing· 2 Research Focus:benchmarking· 1 Organism:E. coli· 1 Approach:machine learning (classical)· 1 Approach:statistical model· 1 Research Focus:variant effect prediction· 1

Frequent Co-Authors

Aldert ZomeriD· 1 shared Alice Carolyn McHardyiD· 1 shared Ehsaneddin AsgariiD· 1 shared Fernando MeyeriD· 1 shared Julián PaganiniiD· 1 shared Lapo Mughini‐GrasiD· 1 shared Michael S. M. BrouweriD· 1 shared Peilin Liu· 1 shared

Activity by Year

2024-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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1 shared paperBioinformatics

Aldert ZomerORCID

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2 papers

Recent·Most cited

BioinformaticsGenomicsPeer-reviewedAug 23, 2026

Exploring differences across pangenome-graph representations using Escherichia coli O157:H7 as a model

Peilin Liu, Kaixin Hu, Lapo Mughini‐Gras…·Julián Paganini

The paper benchmarks pangenome graph construction methods using Escherichia coli O157:H7 genomes, showing that representation strategies and assembly completeness significantly affect graph topology and accuracy.

DOI 10.1016/j.ygeno.2026.111309

E. coliwhole-genome sequencing

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BioinformaticsBriefings in BioinformaticsPeer-reviewedMar 27, 2024

Assessing computational predictions of antimicrobial resistance phenotypes from microbial genomes

Kaixin Hu, Fernando Meyer, Zhi-Luo Deng…·Alice Carolyn McHardy

This study benchmarks ML and rule-based methods for predicting antimicrobial resistance from microbial genomes, finding significant variation in performance across species and antibiotics.

57 citationstop 1%

whole-genome sequencingmachine learning (classical)

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