Author

Jiatong Liang

University of MichiganORCID 0009-0009-4100-9363Unclaimed ORCID profile · follow to get notified of new preprints

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Jiatong Liang1 paper · University of Michigan

Biology Disciplines

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Evolutionary Biology· 1 Genetics· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Assay:DNA methylation· 2 Research Focus:clustering· 1 Research Focus:differential expression· 1 Research Focus:dimensionality reduction· 1 Research Focus:gene regulatory network inference· 1 Approach:graph neural network· 1 Organism:human· 1

Frequent Co-Authors

Jonathan TerhorstiD· 2 shared Enes DilberiD· 1 shared Gideon BradburdiD· 1 shared Junyan TaniD· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

4 top collaborators · 4 mutual co-author links

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2 shared papersGenetics

Jonathan TerhorstORCID

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2 papers

Recent·Most cited

Deep Recovery of Effective Migration Surfaces

Jiatong Liang, Gideon Bradburd, Jonathan Terhorst

This paper introduces dreems, a graph neural network that efficiently estimates effective migration surfaces from genetic data, achieving lower error and faster computation than existing methods.

bioRxiv · Nov 4, 2026 · PreprintGenetics

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.

Bioinformatics · Jul 11, 2026Peer-reviewedEvolutionary Biology