Author

Nicholas Bogard

University of WashingtonORCID 0000-0001-9231-9382Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:gene regulatory network inference· 3 Research Focus:variant effect prediction· 3 Approach:deep learning· 2 Assay:DNA methylation· 2 Approach:experimental assay· 2 Organism:human· 2 Research Focus:protein design· 2 Organism:bacteria (other)· 1

Frequent Co-Authors

Alexander B. RosenbergiD· 3 shared Georg SeeligiD· 3 shared Johannes LinderiD· 3 shared Aerilynn Nguyen· 1 shared Alex K. Sabo· 1 shared Angela M YuiD· 1 shared Charles M. RocoiD· 1 shared Gabriel C. Fonseca· 1 shared

Activity by Year

2019-2025 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 24 mutual co-author links

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3 shared papersGenomics

Alexander B. RosenbergORCID

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4 papers

Recent·Most cited

Massively parallel assay of human splice variants reveals cis-regulatory drivers of disease-associated and cell type-specific splicing regulation

Samantha E. Koplik, Angela M Yu, Madelyn R. Shelby, Gabriel C. Fonseca, Charles M. Roco, Yue Zhang, Nicholas Bogard, Alex K. Sabo, Alexander B. Rosenberg, Johannes Linder, Georg Seelig

The paper develops COMPASS, a method to assess splicing variant effects across cell types, identifying disease-associated variants and cell type-specific splicing programs.

bioRxiv · Oct 12, 2025 · PreprintSynthetic Biology

Multiplexed direct detection of barcoded protein reporters on a nanopore array

Nicolás Cardozo, Karen Huilin Zhang, Kathryn J Doroschak, Aerilynn Nguyen, Zoheb Siddiqui, Nicholas Bogard, Karin Strauß, Luís Ceze, Jeff Nivala

This paper introduces a new class of reporter proteins that can be directly detected using nanopore sensors for multiplexed, real-time gene expression tracking.

Nature Biotechnology · Aug 12, 2021Peer-reviewedSynthetic Biology

Deep exploration networks for rapid engineering of functional DNA sequences

Johannes Linder, Nicholas Bogard, Alexander B. Rosenberg, Georg Seelig

This paper introduces Deep Exploration Networks (DENs) to generate high-fitness DNA sequences, demonstrating improved performance in engineering RNA isoforms compared to gradient ascent methods.

bioRxiv · Dec 4, 2019 · PreprintGenomics

Predicting the Impact of cis-Regulatory Variation on Alternative Polyadenylation

Nicholas Bogard, Johannes Linder, Alexander B. Rosenberg, Georg Seelig

This paper introduces APARENT, a deep learning model that predicts alternative polyadenylation from DNA sequence, outperforming models trained on endogenous data and identifying genetic variants impacting APA in disease contexts.

Cell · Jun 1, 2019Peer-reviewedGenomics