Author

Enes Dilber

University of MichiganORCID 0000-0002-6292-9267Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:statistical model· 2 Approach:deep learning· 1 Research Focus:differential expression· 1 Assay:DNA methylation· 1 Research Focus:gene regulatory network inference· 1 Organism:human· 1 Research Focus:variant calling· 1

Frequent Co-Authors

Jonathan TerhorstiD· 2 shared Jiatong LiangiD· 1 shared Junyan TaniD· 1 shared

Activity by Year

2022-2026 · peak 1/yr

Co-Author Collaboration Network

3 top collaborators · 3 mutual co-author links

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2 shared papersEvolutionary Biology

Jonathan TerhorstORCID

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2 papers

Recent·Most cited

Evolutionary BiologyBioinformaticsPeer-reviewedJul 11, 2026

Faster inference of complex demographic models from large allele frequency spectra

Enes Dilber, Jiatong Liang, Junyan Tan, Jonathan Terhorst

The paper introduces a new method for inferring complex demographic models from genetic variation data, achieving significant speedups over existing methods.

5 citations

humanDNA methylation

𝕏 PostBluesky

GeneticsGeneticsPeer-reviewedJan 19, 2022

Robust detection of natural selection using a probabilistic model of tree imbalance

Enes Dilber, Jonathan Terhorst

This paper introduces likelihood-based methods to detect natural selection, robust to population size fluctuations, using a probabilistic model of tree imbalance.

2 citations

statistical model

𝕏 PostBluesky