Cycle-Extractor accurately reconstructs ecDNA structures from both short- and long-read sequencing data, outperforming existing methods in speed and completeness.

bioRxiv · Apr 15, 2026 · PreprintBioinformatics

Reconstructing the three-dimensional architecture of extrachromosomal DNA with ec3D

Biswanath Chowdhury, Kaiyuan Zhu, Chaohui Li, Jessica Alsing, Jens Luebeck, Maria E. Stefanova, Owen S. Chapman, Katerina Kraft, Shu Zhang, Jun Yi Stanley Lim, Yipeng Xie, Yoon Jung Kim, Sihan Wu, Lukas Chávez, Guy Nir, , Vineet Bafna

The paper introduces ec3D, a method to reconstruct 3D structures of ecDNA from Hi-C data, revealing spherical configurations and unique long-range interactions in cancer.

Nature Communications · Dec 20, 2025Peer-reviewedCancer Biology

TX-Phase: Secure Phasing of Private Genomes in a Trusted Execution Environment

Natnatee Dokmai, Kaiyuan Zhu, S. Cenk Şahinalp, Hyunghoon Cho

TX-Phase securely phases private genomes using Trusted Execution Environments, achieving high accuracy and efficiency on UK Biobank and Haplotype Reference Consortium datasets.

Genome Research · Dec 1, 2025Peer-reviewedBioinformatics

Learning-Augmented Sketching Offers Improved Performance for Privacy Preserving and Secure GWAS

Junyan Xu, Kaiyuan Zhu, Jieling Cai, Can Koçkan, Natnatee Dokmai, Hyunghoon Cho, David Paul Woodruff, S. Cenk Şahinalp

The paper improves the SkSES method for privacy-preserving GWAS by integrating a learning-augmented approach, achieving up to 40% higher accuracy under memory constraints.

iScience · Feb 13, 2025Peer-reviewedBioinformatics

CoRAL accurately resolves extrachromosomal DNA genomestructures with long-read sequencing

Kaiyuan Zhu, Matthew G. Jones, Jens Luebeck, Xinxin Bu, Hyerim Yi, King L. Hung, Ivy Tsz-Lo Wong, Shu Zhang, Paul S. Mischel, Howard Y. Chang, Vineet Bafna

CoRAL improves ecDNA structure reconstruction using long-read sequencing, outperforming short-read methods in simulations and cell-line datasets.

bioRxiv · Feb 15, 2024Cancer Biology

Strain Level Microbial Detection and Quantification with Applications to Single Cell Metagenomics

Kaiyuan Zhu, Alejandro A. Schäffer, Welles Robinson, Junyan Xu, Eytan Ruppin, Funda Ergün, Yuzhen Ye, S. Cenk Şahinalp

CAMMiQ improves microbial strain-level detection and quantification in single-cell metagenomics by using combinatorial optimization and doubly-unique substrings, outperforming existing methods in accuracy.

Nature Communications · Oct 28, 2022Peer-reviewedBioinformatics

Privacy-Preserving Genotype Imputation in a Trusted Execution Environment

Natnatee Dokmai, Can Koçkan, Kaiyuan Zhu, Xiaofeng Wang, S. Cenk Şahinalp, Hyunghoon Cho

This paper introduces a privacy-preserving genotype imputation method using a Trusted Execution Environment to protect genetic data while maintaining accuracy comparable to existing tools.

Cell Systems · Aug 26, 2021Peer-reviewedBioinformatics

Sketching Algorithms for Genomic Data Analysis and Querying in a Secure Enclave

Can Koçkan, Kaiyuan Zhu, Natnatee Dokmai, Nikolai Karpov, Muhammed Oğuzhan Külekci, David Paul Woodruff, S. Cenk Şahinalp

SkSES enables secure and privacy-preserving SNP analysis across encrypted genomic data using sketching algorithms in Intel SGX enclaves, demonstrating efficient SNP querying in a large dataset.

Nature Methods · Mar 1, 2020Peer-reviewedBioinformatics

Combinatorial Detection of Conserved Alteration Patterns for Identifying Cancer Subnetworks

Ermin Hodzic, Raunak Shrestha, Kaiyuan Zhu, Kuoyuan Cheng, Colin C. Collins, S. Cenk Şahinalp

The paper introduces cd-CAP, a method to detect conserved alteration patterns in cancer subnetworks across tumor samples.

GigaScience · Apr 1, 2019Peer-reviewedSystems Biology