Author

Deniz Sezer

Department of Pharmacology, UTSW Medical Center, TX 75390, USAORCID 0000-0002-9635-4369Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Systems Biology· 1

Signature Assays, Organisms & Methods

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Approach:statistical model· 2 Research Focus:benchmarking· 1 Assay:metabolomics· 1 Approach:variational autoencoder· 1

Frequent Co-Authors

Erdal ToprakiD· 1 shared Martin J. LercheriD· 1 shared Peter Schubert· 1 shared

Activity by Year

2020-2025 · peak 1/yr

Co-Author Collaboration Network

3 top collaborators · 1 mutual co-author link

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1 shared paperBioinformatics

Erdal ToprakORCID

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2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintOct 10, 2025

Counting-based inference of mutant growth rates from pooled sequencing across growth regimes

Deniz Sezer, Erdal Toprak

The paper develops methods to infer mutant growth rates from pooled sequencing data by modeling growth and noise, improving accuracy over existing approaches.

DOI 10.1101/2025.10.10.681719

statistical modelvariational autoencoder

𝕏 PostBluesky

Systems BiologybioRxivPreprintSep 19, 2020

Structure of autosynthetic models of balanced cell growth and numerical optimization of their growth rate

Deniz Sezer, Peter Schubert, Martin J. Lercher

This paper develops numerical methods to optimize the growth rate of genome-scale metabolic models by treating enzyme concentrations as variables and clarifying simplifying assumptions in the optimization framework.

1 citation

metabolomicsstatistical model

𝕏 PostBluesky