Author

Ilia Buralkin

Baylor College of MedicineORCID 0009-0003-3563-2999Unclaimed 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· 2 Organism:human· 1 Assay:scRNA-seq· 1 Research Focus:variant calling· 1 Research Focus:variant effect prediction· 1 Assay:whole-genome sequencing· 1

Frequent Co-Authors

Junseok ParkiD· 2 shared Zhandong LiuiD· 2 shared Athanasios Papastathopoulos-KatsarosiD· 1 shared Hu CheniD· 1 shared Jorge BotasiD· 1 shared Kai-Li ChangiD· 1 shared Yueqian DengiD· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

7 top collaborators · 17 mutual co-author links

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2 shared papersBioinformatics

Junseok ParkORCID

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2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintMay 26, 2026

Vision-Based Genomic Model for Copy Number Variant Pathogenicity Prediction

Ilia Buralkin, Jorge Botas, Kai-Li Chang…·Junseok Park

This paper introduces a vision-based model for predicting CNV pathogenicity using track-based spatial representations, achieving improved performance on benchmarks and clinical datasets.

DOI 10.64898/2026.05.21.726953

whole-genome sequencingdeep learning

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BioinformaticsbioRxivPreprintMay 21, 2026

scDeepVariant: A population-informed deep learning framework for germline variant calling in scRNA-seq

Ilia Buralkin, Hu Chen, Zhandong Liu, Junseok Park

scDeepVariant improves germline variant calling in scRNA-seq by integrating population allele frequency data, outperforming existing methods in precision, recall, and rare variant detection.

DOI 10.64898/2025.12.31.696877

humanscRNA-seq

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