Author

Michael Erdmann

Friedrich-Alexander-Universität Erlangen-NürnbergORCID 0000-0001-7136-6489Unclaimed 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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Organism:human· 2 Research Focus:cell-cell communication· 1 Research Focus:drug response / drug discovery· 1 Assay:imaging· 1 Approach:machine learning (classical)· 1 Assay:spatial transcriptomics· 1 Approach:statistical model· 1

Frequent Co-Authors

Andreas S. BauriD· 2 shared Anna Cäcilie MölleriD· 2 shared Anne HartebrodtiD· 2 shared Christian OstaleckiiD· 2 shared David B. BlumenthaliD· 2 shared Katharina BreiningeriD· 1 shared Stefan UderhardtiD· 1 shared Suryadipto SarkariD· 1 shared

Activity by Year

2024-2024 · peak 2/yr

Co-Author Collaboration Network

8 top collaborators · 26 mutual co-author links

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2 shared papersBioinformatics

Andreas S. BaurORCID

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2 papers

Recent·Most cited

Spatial cell graph analysis reveals skin tissue organization characteristic for cutaneous T cell lymphoma

Suryadipto Sarkar, Anna Cäcilie Möller, Anne Hartebrodt, Michael Erdmann, Christian Ostalecki, Andreas S. Baur, David B. Blumenthal

The paper analyzes spatial protein abundance data from skin tissue samples to identify characteristic spatial organization patterns in CTCL compared to AD and PSO.

npj Systems Biology and Applications · Dec 2, 2024Peer-reviewedBioinformatics

High-accuracy prediction of 5-year progression-free melanoma survival using spatial proteomics and few-shot learning on primary tissue

Anna Cäcilie Möller, Christian Ostalecki, Anne Hartebrodt, Katharina Breininger, Michael Erdmann, Stefan Uderhardt, Andreas S. Baur, David B. Blumenthal

This paper predicts 5-year progression-free survival in melanoma using spatial proteomics and few-shot learning, achieving over 90% accuracy.

bioRxiv · Oct 30, 2024 · PreprintBioinformatics