Author

Mehmet Gönen

Koç UniversityORCID 0000-0002-2483-075XUnclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Organism:human· 3 Approach:Bayesian inference· 1 Assay:bulk RNA-seq· 1 Research Focus:cell signaling & trafficking· 1 Research Focus:cell-cell communication· 1 Research Focus:drug response / drug discovery· 1 Approach:experimental assay· 1 Research Focus:gene regulatory network inference· 1

Frequent Co-Authors

Baris SergiiD· 1 shared Büşra YildirimiD· 1 shared Ceyda AçılaniD· 1 shared Dharani ThirumalaisamyiD· 1 shared Elif Nur Firat‐KaralariD· 1 shared F. Basak TuraniD· 1 shared Ilgin Sezer· 1 shared Jovana DereticiD· 1 shared

Activity by Year

2025-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 12 mutual co-author links

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1 shared paperBioinformatics

Baris SergiORCID

Mutual co-authors in cluster

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3 papers

Recent·Most cited

GLproxScape reconstructs spatial chromatin occupancy landscapes from tiled genomic locus proteomics

Selahattin Can Özcan, Baris Sergi, Büşra Yildirim, Umut Cagiral, Mehmet Gönen, Ceyda Açılan

GLproxScape reconstructs spatial chromatin occupancy landscapes from genomic locus proteomics data by modeling per-region enrichments as spatial measurements.

bioRxiv · Jul 3, 2026 · PreprintBioinformatics

CCDC66 couples actin-microtubule crosslinking to KANK1-associated microtubule targeting and focal adhesion turnover

F. Basak Turan, Ilgin Sezer, Jovana Deretic, Mehmet Gönen, Elif Nur Firat‐Karalar

This study identifies CCDC66 as an actin-microtubule crosslinker that couples microtubule targeting to focal adhesion turnover and migration, with implications for cancer progression.

bioRxiv · May 20, 2026 · PreprintCell Biology

Transfer learning framework via Bayesian group factor analysis incorporating feature-wise dependencies

Dharani Thirumalaisamy, Natasha Black, Mehmet Gönen, Olga H. Nikolova

This paper introduces a Bayesian group factor analysis transfer learning framework that improves drug response prediction and tumor purity prediction across cancer datasets by modeling feature dependencies.

bioRxiv · May 7, 2025 · PreprintBioinformatics