Author

Sven Kjellström

Lund UniversityORCID 0000-0003-4646-5279Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Organism:human· 2 Assay:proteomics· 2 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Research Focus:database / resource· 1 Approach:deep learning· 1 Approach:experimental assay· 1 Assay:metagenomics· 1

Frequent Co-Authors

Artur SchmidtcheniD· 2 shared Erik HartmaniD· 2 shared Johan A. MalmströmiD· 2 shared Aaron M. ScottiD· 1 shared Alejandro Gómez ToledoiD· 1 shared Anna BläckbergiD· 1 shared Arman IzadiiD· 1 shared Berit OlofssoniD· 1 shared

Activity by Year

2021-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 25 mutual co-author links

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2 shared papersBioinformatics

Artur SchmidtchenORCID

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3 papers

Recent·Most cited

ImmunologyNature CommunicationsPeer-reviewedFeb 24, 2025

Dissecting the properties of circulating IgG against Group A Streptococcus through a combined systems antigenomics-serology workflow

Alejandro Gómez Toledo, Sounak Chowdhury, Elisabeth Hjortswang…·Johan A. Malmström

This paper develops a combined systems antigenomics-serology workflow to characterize circulating IgG against Group A Streptococcus, revealing antigen repertoire and functional properties of antibodies in healthy and infected individuals.

12 citationstop 3%

humanproteomics

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BioinformaticsbioRxivPreprintDec 28, 2023

Community-based peptidomic clustering reveals pathogen-specific proteolytic signatures in wounds

Erik Hartman, Fredrik Forsberg, Sven Kjellström…·Artur Schmidtchen

The paper develops a computational workflow to cluster peptides in peptidomic data, revealing pathogen-specific proteolytic signatures in wound fluids.

DOI 10.1101/2023.12.28.573527

humanmetagenomics

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BioinformaticsFrontiers in BioinformaticsPeer-reviewedAug 25, 2021

Peptimetric: Quantifying and visualizing differences in peptidomic data

Erik Hartman, Simon Mahdavi, Sven Kjellström, Artur Schmidtchen

Peptimetric is a web tool for analyzing peptidomic data, enabling dynamic comparison of peptides across samples to identify differences.

1 citation

proteomicsexperimental assay

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