Author

Natalie Maus

University of PennsylvaniaORCID 0000-0002-6616-8506Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Research Focus:drug response / drug discovery· 2 Approach:Bayesian inference· 1 Assay:bulk RNA-seq· 1 Research Focus:gene regulatory network inference· 1 Organism:human· 1 Assay:proteomics· 1 Approach:transformer / foundation model· 1

Frequent Co-Authors

Jacob R. GardneriD· 2 shared Anna Tangiyan· 1 shared Anupama JhaiD· 1 shared Benjamin D Wales-McGrathiD· 1 shared César de la Fuente‐NúñeziD· 1 shared Di WuiD· 1 shared Fangping WaniD· 1 shared Kevin YangiD· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 27 mutual co-author links

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2 shared papersBioinformatics

Jacob R. GardnerORCID

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2 papers

Recent·Most cited

BioinformaticseLifePeer-reviewedMay 29, 2026

Generative modeling for RNA splicing predictions and design

Di Wu, Natalie Maus, Anupama Jha…·Yoseph Barash

This paper introduces TrASPr+BOS, a generative AI model for predicting and designing RNA to achieve tissue-specific splicing outcomes, showing improved performance over existing methods.

3 citations

bulk RNA-seqdeep learning

𝕏 PostBluesky

MicrobiologyNature Machine IntelligencePeer-reviewedMay 13, 2026

A generative artificial intelligence approach for antibiotic optimization

Marcelo D. T. Torres, Yimeng Zeng, Fangping Wan…·César de la Fuente‐Núñez

This paper introduces APEXGO, a generative AI framework for optimizing antimicrobial peptides, achieving high success rates in enhancing antimicrobial activity and outperforming existing methods.

33 citationstop 1%

humanproteomics

𝕏 PostBluesky