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Kuan-Hao Chao @kuanhaochao.bsky.social · 19/05/2026

Thank you @stevensalzberg.bsky.social and Ela for making yesterday so special. It was fantastic to see you both again! I couldn't have asked for better advisors during my PhD journey at @hopkinsengineer.bsky.social @jhucompsci.bsky.social

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Reposted by Kuan-Hao Chao

David Kelley @drkbio.bsky.social · 14/10/2025

Excited to share our new paper on predicting gene expression in yeast! We introduce "Shorkie," a supervised ML model that builds off a self-supervised foundation to interpret regulatory DNA. Preprint: www.biorxiv.org/content/10.1...

biorxiv.org

Predicting dynamic expression patterns in budding yeast with a fungal DNA language model

Predicting gene expression from DNA sequence remains challenging due to complex regulatory codes. We introduce a masked DNA language model pretrained on 165 fungal genomes closely related to budding y...

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Reposted by Kuan-Hao Chao

bioRxiv Genomics @biorxiv-genomic.bsky.social · 21/09/2025

Predicting dynamic expression patterns in budding yeast with a fungal DNA language model www.biorxiv.org/content/10.1101/202…

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Kuan-Hao Chao @kuanhaochao.bsky.social · 26/08/2025

Heart full—I defended my PhD in @jhucompsci.bsky.social @jhu.edu(Aug 25). Thanks to my advisors @stevensalzberg.bsky.social and Mihaela Pertea; my committee— @benlangmead.bsky.social, David Kelley & Anqi Liu; and all labmates, collaborators, and mentors. You made me who I am today. Deeply grateful!

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Kuan-Hao Chao @kuanhaochao.bsky.social · 21/08/2025

Friends I’m defending my PhD! 🗓 Mon, Aug 25 • 2:30 PM–4:30 PM ET 📍 JHU Homewood — Clark Hall 110 💻 Zoom: jhubluejays.zoom.us/j/9385611117... If you’re into genomics or deep learning (or just curious how AI reads DNA), I’d love to have you there—friends welcome! Details: khchao.com/thesis-defen...

jhubluejays.zoom.us

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Kuan-Hao Chao @kuanhaochao.bsky.social · 23/07/2025

🚀 Thrilled to share our OpenSpliceAI paper is out in @elife.bsky.social Open‑source, PyTorch extension of SpliceAI—fast, modular splice‑site prediction, transfer learning, and variant‑effect scoring. 🔗 Paper doi.org/10.7554/eLif... 🔗 Code github.com/Kuanhao-Chao... 🔗 Docs ccb.jhu.edu/openspliceai/

doi.org

OpenSpliceAI: An efficient, modular implementation of SpliceAI enabling easy retraining on non-human species

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Kuan-Hao Chao @kuanhaochao.bsky.social · 17/06/2025

Excited to introduce LiftOn – an open-source tool for accurate, scalable liftover of genome annotations (GFF) across assemblies. 🚀 👉 Code & community: github.com/Kuanhao-Chao... It’s been incredibly rewarding building this for the genomics community. Can’t wait for your feedback and contributions!

github.com

GitHub - Kuanhao-Chao/LiftOn: 🚀 LiftOn: Accurate annotation mapping for GFF/GTF across assemblies

🚀 LiftOn: Accurate annotation mapping for GFF/GTF across assemblies - Kuanhao-Chao/LiftOn

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Reposted by Kuan-Hao Chao

Steven Salzberg @stevensalzberg.bsky.social · 24/03/2025

@kuanhaochao.bsky.social and Alan Mao built an open-source version of SpliceAI, a deep learning model for predicting human splice sites, and it turned into quite a project! Many new features including training modules, check out the whole thread below

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Kuan-Hao Chao @kuanhaochao.bsky.social · 24/03/2025

Friends, I’m excited to release OpenSpliceAI, an open‐source, efficient, and modular framework for splice site prediction. It reimplements and extends SpliceAI (Jaganathan et al., 2019) using the modern PyTorch framework. 1/ Mihaela Pertea, @stevensalzberg.bsky.social, Anqi Liu, Alan Mao

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Kuan-Hao Chao @kuanhaochao.bsky.social · 03/03/2025

Friends, LiftOn is now published in @genomeresearch.bsky.social! LiftOn maps genes across genomes using a protein-centric, homology-based approach with both DNA & protein alignments @stevensalzberg.bsky.social Mihaela Pertea, Jakob Heinz, Alaina Shumate, Celine Hoh, Alan Mao doi.org/10.1101/gr.2...

doi.org

Combining DNA and protein alignments to improve genome annotation with LiftOn

An international, peer-reviewed genome sciences journal featuring outstanding original research that offers novel insights into the biology of all organisms

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