Author

Tina Subic

University of PittsburghORCID 0000-0002-9394-7839Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:deep learning· 1 Research Focus:gene regulatory network inference· 1 Assay:Hi-C· 1 Approach:statistical model· 1

Frequent Co-Authors

Ali Tuğrul BalcıiD· 1 shared Diego Borges-RiveraiD· 1 shared Geoffrey FudenbergiD· 1 shared Jacqueline DreschiD· 1 shared Jieni Hu· 1 shared Kristina PerevoshchikovaiD· 1 shared Maria D. ChikinaiD· 1 shared

Activity by Year

2025-2025 · peak 1/yr

Co-Author Collaboration Network

7 top collaborators · 21 mutual co-author links

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1 shared paperGenomics

Ali Tuğrul BalcıORCID

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1 paper

Recent·Most cited

Mechanistic Genome Folding at Scale through the Differentiable Loop Extrusion Model

Tina Subic, Ali Tuğrul Balcı, Kristina Perevoshchikova, Diego Borges-Rivera, Jieni Hu, Geoffrey Fudenberg, Jacqueline Dresch, Maria D. Chikina

This paper introduces dLEM, a differentiable loop extrusion model that predicts genome folding mechanisms from contact maps and integrates with deep learning to infer extrusion parameters from genomic features.

bioRxiv · Oct 17, 2025 · PreprintGenomics