Ladder - probabilistic modeling of single-cell omics data
Ladder is a probabilistic modeling framework developed mainly for single-cell omics data. It is under active development; check out the GitHub page for more updates soon.
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Variational Learning of Disentangled Representations
Yuli Slavutsky*, Ozgur Beker*, David Blei, Bianca Dumitrascu
ICML, 2026
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Patches: A Representation Learning Framework for Decoding Shared and Condition-Specific Transcriptional Programs in Wound Healing
Ozgur Beker, Simon Van Deursen, Michel Tarnow, Dreyton Amador, Jonathan Chin Cheong, Jose Francisco Pomarino Nima ProfileMark D. Robinson, Yvon Woappi, Bianca Dumitrascu
bioRxiv, 2024
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Biophysical modeling for morphodynamics
This section is still under construction; check in again soon.
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Single-cell morphodynamics predict cell fate decisions during mucociliary epithelial differentiation
Mari Tolonen, Ziwei Xu, Ozgur Beker, Varun Kapoor, Bianca Dumitrascu & Jakub Sedzinski
Molecular Systems Biology, 2026
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Past projects
Projects I worked on in the past.
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Brendo: an open resource for uniquely transcribed genes in brain endothelial cells
Ozgur Beker, Fereshteh Ramezani Khorsand, Ogun Adebali, Nur Mustafaoglu
bioRxiv, 2025
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CATD: a reproducible pipeline for selecting cell-type deconvolution methods across tissues
Anna Vathrakokoili Pournara , Zhichao Miao , Ozgur Yilimaz Beker, Nadja Nolte , Alvis Brazma , Irene Papatheodorou
Bioinformatics Advances, 2024
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