Author

Matthias Bernd Schulze

University of PotsdamORCID 0000-0002-0830-5277Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Genetic & Genomic Medicine· 2 Bioinformatics· 1

Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Research Focus:GWAS / association mapping· 2 Organism:human· 2 Research Focus:batch correction / integration· 1 Assay:bulk RNA-seq· 1 Assay:metabolomics· 1 Assay:proteomics· 1

Frequent Co-Authors

Arina V. NostaevaiD· 2 shared Clemens WittenbecheriD· 2 shared Frano VučkovićiD· 2 shared Gordan LauciD· 2 shared Irena Trbojević‐AkmačićiD· 2 shared Massimo ManginoiD· 2 shared Sodbo SharapoviD· 2 shared Tamara ŠtambukiD· 2 shared

Activity by Year

2021-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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Focal author (center)Selected co-authorORCID co-authorUnlinked name

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2 shared papersGenetic & Genomic Medicine

Arina V. NostaevaORCID

Mutual co-authors in cluster

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3 papers

Recent·Most cited

Genetic & Genomic MedicineNature CommunicationsPeer-reviewedJul 1, 2025

A genome-wide association study in 10,000 individuals links plasma N-glycome to liver disease and anti-inflammatory proteins

Sodbo Sharapov, Anna N. Timoshchuk, Olga O. Zaytseva…·Yurii S. Aulchenko

This study identifies 16 new genetic loci associated with plasma N-glycosylation in 10,000 individuals and links them to liver disease and inflammatory proteins.

7 citations

humanproteomics

Genetic & Genomic MedicineAgingPeer-reviewedDec 26, 2023

Mapping of the gene network that regulates glycan clock of ageing

Azra Frkatović-Hodžić, Karlo Miškec, Anika Mijakovac…·Gordan Lauc

The paper identifies 16 genomic loci associated with IgG galactosylation through GWAS and validates three genes using CRISPR/dCas9 in an in vitro system.

13 citations

humanbulk RNA-seq

BioinformaticsMetabolitesPeer-reviewedSep 17, 2021

A new pipeline for the normalization and pooling of metabolomics data

Vivian Viallon, Mathilde His, Sabina Rinaldi…·Pietro Ferrari

The paper introduces a pipeline to normalize and pool metabolomics data across studies, improving comparability and reducing inter-study variability.

29 citations

metabolomicsstatistical model