Author

Y. Assenov

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

Cancer Biology· 2

Signature Assays, Organisms & Methods

Click to filter · or open tag

Research Focus:differential expression· 2 Assay:DNA methylation· 2 Organism:human· 2 Research Focus:cell type annotation· 1 Research Focus:gene regulatory network inference· 1 Approach:machine learning (classical)· 1 Research Focus:protein structure prediction· 1 Approach:statistical model· 1

Frequent Co-Authors

C. Plass· 2 shared R. Toth· 2 shared C. C. Oakes· 1 shared C. Fraune· 1 shared C. Gerhauser· 1 shared C. Hube-Magg· 1 shared D. B. Lipka· 1 shared D. Höflmayer· 1 shared

Activity by Year

2019-2020 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 30 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

2 shared papersCancer Biology

C. Plass

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

Methylome-based cell-of-origin modeling (Methyl-COOM) identifies aberrant expression of immune regulatory molecules in CLL

J. A. Wierzbinska, R. Toth, N. Ishaque, K. Rippe, J.-P. Mallm, L. Klett, D. Mertens, T. Zenz, T. Hielscher, M. Seifert, R. Kueppers, Y. Assenov, P. Lutsik, S. Stilgenbauer, P. M. Roessner, , D. B. Lipka

This study introduces Methyl-COOM, a method to identify cell-of-origin and CLL-specific epigenetic aberrations by analyzing DNA methylation patterns.

bioRxiv · Feb 4, 2020Cancer Biology

Random forest-based modelling to detect biomarkers for prostate cancer progression

R. Toth, H. Schiffmann, C. Hube-Magg, F. Büscheck, D. Höflmayer, S. Weidemann, P. Lebok, C. Fraune, S. Minner, T. Schlomm, G. Sauter, C. Plass, Y. Assenov, R. Simon, J. Meiners, C. Gerhauser

This study uses a random forest model to identify DNA methylation biomarkers for prostate cancer progression, finding ZIC2 expression loss as an independent prognostic marker.

bioRxiv · Apr 8, 2019Cancer Biology