Author

Wanwan Ge

Max Planck Institute for Biophysical ChemistryORCID 0000-0001-8879-077XUnclaimed ORCID profile · follow to get notified of new preprints

Additional preprints under this name without ORCID

Wanwan Ge1 paper · Robert Bosch Hospital

Biology Disciplines

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Bioinformatics· 1 Cancer Biology· 1

Signature Assays, Organisms & Methods

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Assay:ChIP-seq· 2 Research Focus:gene regulatory network inference· 2 Approach:statistical model· 2 Approach:Bayesian inference· 1 Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1 Research Focus:chromatin & epigenetic regulation· 1 Research Focus:differential expression· 1

Frequent Co-Authors

Amro AbdelrahmaniD· 1 shared Ashish Rajput· 1 shared Christian Michael RothiD· 1 shared Dominik SauliD· 1 shared Joana E. Aggrey-FynniD· 1 shared Johannes SödingiD· 1 shared Joshua Busch· 1 shared Julia ThieliD· 1 shared

Activity by Year

2021-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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1 shared paperCancer Biology

Amro AbdelrahmanORCID

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2 papers

Recent·Most cited

Cancer BiologyCell Death DiscoveryPeer-reviewedMar 17, 2026

Epigenetic Context Defines the Transcriptional Activity of Canonical and Noncanonical NF-κB Signaling in Pancreatic Cancer

Joana E. Aggrey-Fynn, Joshua Busch, Dominik Saul…·Steven A. Johnsen

This study identifies TNF and TWEAK as activators of canonical and noncanonical NF-κB signaling in PDAC, revealing distinct epigenetic dependencies of RELA and RELB.

1 citation

humanbulk RNA-seq

𝕏 PostBluesky

BioinformaticsNAR Genomics and BioinformaticsPeer-reviewedApr 9, 2021

Bayesian Markov models improve the prediction of binding motifs beyond first order

Wanwan Ge, Markus Meier, Christian Michael Roth, Johannes Söding

BaMMmotif2 improves binding motif prediction by modeling higher-order dependencies, achieving higher recall and speed compared to existing tools.

13 citations

ChIP-seqBayesian inference

𝕏 PostBluesky