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haonanwu.bsky.social

@haonanwu.bsky.social

CSE PhD student at Penn State Theoretical and algorithmic bioinformatics wu-haonan.github.io

haonanwu.bsky.social @haonanwu.bsky.social · 11/07/2026

Our #ISMB2026 paper is now online! I’m excited to present it at HiTSeq on July 13. Many thanks to my advisor @pashadag.bsky.social. I’m also grateful to @iscb.bsky.social for awarding me the Conference Fellowship. If you’ll be at ISMB, feel free to stop by my talk and say hi. I’d love to connect!

academic.oup.com

The gift of novelty: repeat-robust k-mer-based estimators of mutation rates

AbstractMotivation. Estimating mutation rates between evolutionarily related sequences is a central problem in molecular evolution. Due to the rapid expans

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haonanwu.bsky.social @haonanwu.bsky.social · 07/05/2026

Recently, while mentoring an undergraduate student on her thesis, I realized that maybe many students do not actually know what each section of a paper is supposed to say — especially the Introduction and Results sections.

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Sina Majidian @sinamajidian.bsky.social · 06/11/2025

Haonan Wu gives a talk on "A k-mer-based estimator of the substitution rate between repetitive sequences" www.biorxiv.org/content/10.1... This work tackles the issue of Mash which ignores repeats in the genome, providing better distance estimation #GI2025

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Rob Patro @robp.bsky.social · 20/08/2025

"K-mer-based estimators of the substitution rate of repetitive sequences" presented by Haonan Wu at #WABI25!

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Paul Medvedev @pashadag.bsky.social · 25/06/2025

🧵1/n Estimating mutation rates using k-mers is fast—but what happens when repeats dominate the genome? In a new preprint, Haonan Wu, Antonio Blanca, and myself propose a *repeat-aware* estimator that's accurate even in centromeres.

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