Author

Andreas Schäfer

University of Regensburg

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

Click to filter author papers

Bioinformatics· 3

Signature Assays, Organisms & Methods

Click to filter · or open tag

Approach:statistical model· 3 Assay:bulk RNA-seq· 2 Research Focus:deconvolution· 2 Organism:human· 2 Research Focus:cell-cell communication· 1 Research Focus:gene regulatory network inference· 1 Assay:spatial transcriptomics· 1

Frequent Co-Authors

Helena U. ZachariasiD· 3 shared Michael AltenbuchingeriD· 3 shared Tim BeißbarthiD· 3 shared Dennis VoelkliD· 2 shared Franziska GörtleriD· 2 shared Malte Mensching-BuhriD· 2 shared Stefan SchrodiD· 2 shared Sushma Nagaraja GrellscheidiD· 2 shared

Activity by Year

2022-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 44 mutual co-author links

Click any collaborator node to inspect or filter shared papers

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

Curved chords = mutual co-authorship

3 shared papersBioinformatics

Helena U. ZachariasORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

HIDE: Hierarchical cell-type Deconvolution

Dennis Voelkl, Malte Mensching-Buhr, Thomas Sterr, Sarah Bolz, Andreas Schäfer, Nicole Seifert, Jana Tauschke, Austin J. Rayford, Oddbjørn Straume, Helena U. Zacharias, Sushma Nagaraja Grellscheid, Tim Beißbarth, Michael Altenbuchinger, Franziska Görtler

HIDE improves cell-type deconvolution by incorporating a cell hierarchy, showing better performance in simulations and applied to breast cancer data.

Bioinformatics · Jul 1, 2025Peer-reviewedBioinformatics

Adaptive Digital Tissue Deconvolution

Franziska Görtler, Malte Mensching-Buhr, Ørjan Skaar, Stefan Schrod, Thomas Sterr, Andreas Schäfer, Tim Beißbarth, Anagha Joshi, Helena U. Zacharias, Sushma Nagaraja Grellscheid, Michael Altenbuchinger

ADTD improves estimation of cellular compositions from bulk transcriptomics data by adapting reference profiles to the molecular environment and identifying hidden contributions.

Bioinformatics · Apr 12, 2024Peer-reviewedBioinformatics

SpaCeNet: Spatial Cellular Networks from omics data

Stefan Schrod, Niklas Lück, Robert Lohmayer, Stefan Solbrig, Dennis Voelkl, Tina Wipfler, Katherine Hoff Shutta, Marouen Ben Guebila, Andreas Schäfer, Tim Beißbarth, Helena U. Zacharias, Peter Josef Oefner, John F Quackenbush, Michael Altenbuchinger

SpaCeNet identifies intracellular and intercellular molecular networks from spatial omics data by analyzing conditional independence relations between variables within and across cells.

bioRxiv · Sep 1, 2022 · PreprintBioinformatics