Author

Deming Chen

University of Illinois Urbana-ChampaignORCID 0000-0002-3016-0270Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Assay:proteomics· 1 Research Focus:sequence-to-function modeling· 1 Research Focus:variant calling· 1 Organism:virus· 1 Assay:whole-genome sequencing· 1

Frequent Co-Authors

Steven S. Lumetta· 2 shared A. RamachandraniD· 1 shared Anand Ramachandran· 1 shared Eric W. KleeiD· 1 shared

Activity by Year

2020-2024 · peak 1/yr

Co-Author Collaboration Network

4 top collaborators · 4 mutual co-author links

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2 shared papersBioinformatics

Steven S. Lumetta

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2 papers

Recent·Most cited

BioinformaticsPLoS Computational BiologyPeer-reviewedJan 19, 2024

PandoGen: Generating complete instances of future SARS-CoV-2 sequences using Deep Learning

A. Ramachandran, Steven S. Lumetta, Deming Chen

PandoGen generates future SARS-CoV-2 protein sequences using deep learning, forecasting novel variants with higher accuracy than larger models.

10 citations

virusproteomics

𝕏 PostBluesky

BioinformaticsbioRxivPreprintMar 23, 2020

HELLO: A hybrid variant calling approach

Anand Ramachandran, Steven S. Lumetta, Eric W. Klee, Deming Chen

The paper introduces a hybrid variant calling method integrating NGS and TGS reads to improve small variant accuracy, achieving up to 30% reduction in errors in challenging regions.

2 citations

whole-genome sequencingdeep learning

𝕏 PostBluesky