Author

P.-S. Huang

Cornell UniversityORCID 0009-0002-4315-7254Unclaimed ORCID profile · follow to get notified of new preprints

Additional preprints under this name without ORCID

P.-S. Huang4 papers

Biology Disciplines

Click to filter author papers

Bioinformatics· 1 Scientific Communication & Education· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Approach:benchmark study· 1 Research Focus:benchmarking· 1 Research Focus:database / resource· 1 Approach:deep learning· 1 Organism:human· 1 Approach:large language model· 1 Organism:mouse· 1 Research Focus:sequence-to-function modeling· 1

Frequent Co-Authors

Erik P. GarrisoniD· 2 shared G. Edward SuhiD· 2 shared Pjotr PrinsiD· 2 shared Shelby S. DarnelliD· 2 shared Adrian Kibet· 1 shared Alexander Kabui· 1 shared Andrea GuarracinoiD· 1 shared Arun IsaaciD· 1 shared

Activity by Year

2025-2025 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

2 shared papersBioinformatics

Erik P. GarrisonORCID

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

BioinformaticsIEEE International Conference on Bioinformatics and Biomedicine (BIBM)Peer-reviewedDec 15, 2025

Pangenome-Informed Language Models for Synthetic Genome Sequence Generation

Pengzhi Huang, François Charton, Jan-Niklas M. Schmelzle…·G. Edward Suh

This paper introduces pangenome-informed language models for generating synthetic DNA sequences, showing improved efficiency and quality over classical methods.

4 citationstop 1%

whole-genome sequencingdeep learning

𝕏 PostBluesky

Scientific Communication & EducationOpen Research AfricaPeer-reviewedSep 2, 2025

✦ In-depth digest

Creating a biomedical knowledge base by addressing GPT inaccurate responses and benchmarking context

Shelby S. Darnell, Rupert W. Overall, Andrea Guarracino…·Pjotr Prins

GNQA, a retrieval-augmented GPT question-answering system over 3000 GeneNetwork, aging and diabetes papers, cites source paragraphs; RAGAS rated answer relevance above human thumbs-up ratings (89% vs 76%).

5 citations

𝕏 PostBluesky