Author

Joseph L. Usset

Hartwig Medical FoundationORCID 0000-0002-5820-9881Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2 Genomics· 1

Signature Assays, Organisms & Methods

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Organism:human· 3 Research Focus:differential expression· 2 Approach:statistical model· 2 Assay:whole-genome sequencing· 2 Research Focus:benchmarking· 1 Research Focus:clustering· 1 Research Focus:drug response / drug discovery· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Francisco Martínez-JiméneziD· 2 shared Joep de LigtiD· 2 shared Adam GodzikiD· 1 shared Adriano ChiòiD· 1 shared Adrienne O’DonnelliD· 1 shared Agnieszka Kitlas GolińskaiD· 1 shared Alex G. Karanevich· 1 shared Anatoly ChernysheviD· 1 shared

Activity by Year

2019-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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2 shared papersBioinformatics

Francisco Martínez-JiménezORCID

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3 papers

Recent·Most cited

BioinformaticsbioRxivPreprintOct 23, 2026

Whole-genome sequencing reveals tumor T-cell infiltration associated with immunotherapy outcomes

Joseph L. Usset, Hong Wing Lee, Reece Jones…·Francisco Martínez-Jiménez

The paper develops a DNA-based T-cell infiltration score from whole-genome sequencing to predict immunotherapy response and survival.

DOI 10.64898/2026.10.22.760891

humanwhole-genome sequencing

𝕏 PostBluesky

GenomicsESMO Real World Data and Digital OncologyPeer-reviewedJun 23, 2026

Systematic identification of genomic non-response biomarkers to cancer therapies

Joseph L. Usset, Joep de Ligt, Sophie F. Roerink…·Francisco Martínez-Jiménez

The paper develops a statistical framework to identify genomic non-response biomarkers in cancer therapies using whole-genome and transcriptome sequencing data from 2,596 patients.

DOI 10.1016/j.esmorw.2026.100721

humanwhole-genome sequencing

𝕏 PostBluesky

BioinformaticsScientific ReportsPeer-reviewedJan 24, 2019

Stratification of amyotrophic lateral sclerosis patients: a crowdsourcing approach

Robert Kueffner, Neta Zach, Maya Bronfeld…·Shihua Zhang

This study uses a crowdsourcing approach to stratify ALS patients, identifying four distinct clusters with unique predictors and improving outcome prediction.

55 citationstop 3%

humanmachine learning (classical)

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