Author

Sikha Pentyala

University of Washington TacomaORCID 0000-0001-7486-6016Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Genomics· 1

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 2 Approach:statistical model· 2 Assay:bulk RNA-seq· 1 Approach:deep learning· 1 Organism:human· 1 Assay:scRNA-seq· 1

Frequent Co-Authors

Martine De CockiD· 2 shared P.S. McKeeveriD· 2 shared Steven GolobiD· 2 shared A B Wicks· 1 shared Antti HonkelaiD· 1 shared Daniil FilienkoiD· 1 shared Hakime ÖztürkiD· 1 shared Jineta BanerjeeiD· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 39 mutual co-author links

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2 shared papersGenomics

Martine De CockORCID

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2 papers

Recent·Most cited

GenomicsbioRxivPreprintJun 6, 2026

Membership Inference on Synthetic Single-Cell Genomic Data

Steven Golob, P.S. McKeever, Sikha Pentyala…·Jonathan Peck

This paper demonstrates that synthetic scRNA-seq data generated by leading methods can be attacked to infer donor membership, showing privacy risks and evaluating noise-based defenses.

DOI 10.64898/2026.01.22.701160

scRNA-seqstatistical model

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BioinformaticsbioRxivPreprintMar 4, 2026

Towards Useful and Private Synthetic Omics: Community Benchmarking of Generative Models for Transcriptomics Data

Hakime Öztürk, Tejumade Afonja, Joonas Jälkö…·Antti Honkela

The paper benchmarks generative models for synthetic bulk RNA-seq data, finding trade-offs between utility, biological preservation, and privacy risks across different methods.

2 citations

humanbulk RNA-seq

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