Author

Ziynet Nesibe Kesimoglu

National Institutes of HealthORCID 0000-0001-8592-4365Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2 Cancer Biology· 1 Genomics· 1

Signature Assays, Organisms & Methods

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Organism:human· 3 Assay:bulk RNA-seq· 2 Research Focus:cell type annotation· 2 Research Focus:clustering· 2 Approach:deep learning· 2 Research Focus:gene regulatory network inference· 2 Approach:statistical model· 2 Research Focus:differential expression· 1

Frequent Co-Authors

Bayarbaatar AmgalaniD· 2 shared Ermin HodziciD· 2 shared Jan HoinkaiD· 2 shared Mary G HirschiD· 2 shared Serdar BozdagiD· 2 shared Teresa M. PrzytyckaiD· 2 shared Chi‐Ping DayiD· 1 shared David LevensiD· 1 shared

Activity by Year

2021-2026 · peak 1/yr

Co-Author Collaboration Network

9 top collaborators · 28 mutual co-author links

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2 shared papersGenomics

Bayarbaatar AmgalanORCID

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4 papers

Recent·Most cited

GenomicsbioRxivPreprintFeb 6, 2026

Combined inference of known and novel mutational signatures with ReDeNovo

Ziynet Nesibe Kesimoglu, Ermin Hodzic, Jan Hoinka…·Teresa M. Przytycka

ReDeNovo infers both known and novel mutational signatures from cancer genomes, outperforming existing methods and identifying new signatures in real data.

DOI 10.64898/2026.02.05.703798

whole-genome sequencingstatistical model

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Cancer BiologybioRxivPreprintDec 12, 2025

Connecting spatial regions to clinical phenotypes by transferring knowledge from bulk patient data

Bayarbaatar Amgalan, Ermin Hodzic, Ziynet Nesibe Kesimoglu…·Teresa M. Przytycka

SpacePhenotyper transfers predictive gene expression-phenotype relationships from bulk data to spatial transcriptomics data to analyze clinical phenotypes in spatial regions of tumors.

DOI 10.64898/2025.12.12.693322

humanspatial transcriptomics

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BioinformaticsNAR Genomics and BioinformaticsPeer-reviewedMar 29, 2023

SUPREME: A cancer subtype prediction methodology integrating multiomics data using Graph Convolutional Neural Network

Ziynet Nesibe Kesimoglu, Serdar Bozdag

SUPREME predicts cancer subtypes using multiomics data and graph convolutions, outperforming existing methods and showing significant survival differences.

37 citations

humanbulk RNA-seq

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BioinformaticsPLoS ONEPeer-reviewedMay 13, 2021

Crinet: A computational tool to infer genome-wide competing endogenous RNA (ceRNA) interactions

Ziynet Nesibe Kesimoglu, Serdar Bozdag

Crinet infers genome-wide ceRNA networks by considering mRNAs, lncRNAs, and pseudogenes and using network deconvolution to exclude spurious interactions, showing enrichment in cancer-related genes.

13 citations

humanbulk RNA-seq

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