Author

Moritz Madern

University of ViennaORCID 0000-0001-8593-5785Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Immunology· 1 Molecular Biology· 1

Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Research Focus:differential expression· 2 Assay:proteomics· 2 Approach:benchmark study· 1 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:database / resource· 1 Organism:human· 1

Frequent Co-Authors

Markus HartliD· 2 shared Anela TosevskaiD· 1 shared Bianca Luckerbauer· 1 shared Daniel AletahaiD· 1 shared Florian StanekiD· 1 shared Karl MechtleriD· 1 shared Lisa GöschliD· 1 shared Manuela BaccariniiD· 1 shared

Activity by Year

2022-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 19 mutual co-author links

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2 shared papersMolecular Biology

Markus HartlORCID

Mutual co-authors in cluster

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3 papers

Recent·Most cited

ImmunologybioRxivPreprintJan 14, 2025

Targeting histone acetylation enables epigenetic modulation of inflammatory pathways, a novel therapeutic strategy for rheumatoid arthritis

Marie Brinkmann, Anela Tosevska, Bianca Luckerbauer…·Michael Markus Bonelli

This study screens histone acetylation inhibitors to modulate immune pathways in RA, showing concentration-dependent effects and overlap with existing RA drug pathways.

1 citation

humanbulk RNA-seq

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Molecular BiologyMolecular & Cellular ProteomicsPeer-reviewedDec 12, 2023

A causal model of ion interference enables assessment and correction of ratio compression in multiplex proteomics

Moritz Madern, Wolfgang Reiter, Florian Stanek…·Markus Hartl

The paper develops a causal model to assess and correct ratio compression caused by ion interference in multiplex proteomics data.

15 citations

proteomicsstatistical model

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BioinformaticsBMC GenomicsPeer-reviewedDec 9, 2022

amica: an interactive and user-friendly web-platform for the analysis of proteomics data

Sebastian Didusch, Moritz Madern, Markus Hartl, Manuela Baccarini

amica provides a user-friendly web platform for proteomics data analysis, offering quality control, differential expression, and network analysis with minimal user input.

64 citationstop 4%

proteomicsstatistical model

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