Yun William Yu

alamem and alasight are tools for fast and memory-efficient local alignment and horizontal gene transfer detection in bacterial genomes.

RAmpSim simulates hybridization capture in metagenomic sequencing by modeling thermodynamic binding and fragment generation, improving coverage accuracy over uniform baselines.

KuPID preprocesses long RNA-seq reads using kmer sketching to improve isoform discovery accuracy and reduce runtime.

divider reconstructs haplotypes from long-read sequencing data, achieving higher accuracy than existing methods on synthetic and real datasets.

Sylph is a metagenome profiler that estimates genome-to-metagenome containment ANI using k-mer statistics, outperforming Kraken2 in speed and memory usage while detecting more viral sequences in the human gut.

Floria rapidly and accurately recovers strain haplotypes from metagenomic data, outperforming existing methods in speed and strain content recovery.

Fairy provides a fast, approximate coverage calculation method for multi-sample metagenomic binning, achieving high accuracy and speed compared to read alignment.

Mora reassigns metagenomic reads to strains with high precision, outperforming other algorithms on similar reads and achieving comparable F1 scores with less runtime.

SlowMoMan identifies discriminative features along user-drawn paths in 2D embeddings by back-projecting to high-dimensional data, aiding in trajectory inference and cell classification.

This paper introduces a secure federated Boolean count query method using homomorphic encryption to address data deduplication and record unification challenges in distributed biomedical data.

The paper introduces PIC, an image-based compression method for protein structures, achieving better compression ratios than gzip for large proteins.

skani estimates average nucleotide identity (ANI) from sparse FracMinHash k-mer chains, staying robust to incomplete, fragmented metagenome-assembled genomes while running over 20 times faster than FastANI.

The paper provides theoretical guarantees for the seed-chain-extend heuristic in sequence alignment, showing it can achieve near-linear runtime and high accuracy with optimal k-mer size.

This paper introduces two new formulations for polyploid haplotype phasing and presents a method called flopp that outperforms existing algorithms in speed and accuracy.

The paper develops a theoretical framework for evaluating k-mer selection methods and demonstrates improved long-read alignment using an optimized method.

The paper proves theoretical bounds on the 10-anonymity privacy risk of using HyperLogLog sketches for federated clinical data queries and provides code to compute these bounds.

The paper develops a method to estimate distinct patient counts in federated clinical data queries while balancing accuracy and privacy.

Opal improves metagenomic binning by using low-density hashing to achieve faster and more accurate identification of sequencing read origins compared to existing methods.