Author

Nour Mimouni

University of PennsylvaniaPrimary ORCID profile (0009-0006-1203-543X · 1 paper)Unclaimed ORCID profile · follow to get notified of new preprints

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Nour MimouniiD1 paper · Division of Cardiovascular Medicine, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA;

Biology Disciplines

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Genetic & Genomic Medicine· 1 Neuroscience· 1

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 2 Approach:Bayesian inference· 1 Approach:deep learning· 1 Assay:GWAS summary statistics· 1 Organism:human· 1 Assay:imaging· 1 Organism:mouse· 1 Approach:statistical model· 1

Frequent Co-Authors

Adam Yongxin YeiD· 1 shared Afiya Poindexter· 1 shared Alejandra Lozada· 1 shared Alex Ahn· 1 shared Amanda Hsieh· 1 shared Anurag VermaiD· 1 shared Benjamin F. VoightiD· 1 shared Bogdan PaşaniuciD· 1 shared

Activity by Year

2022-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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1 shared paperNeuroscience

Adam Yongxin YeORCID

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2 papers

Recent·Most cited

Population Performance and Individual Agreement of Coronary Artery Disease Polygenic Risk Scores

Sarah A. Abramowitz, Kristin M. Boulier, Karl Keat, Katie M. Cardone, Manu Shivakumar, John S. DePaolo, Renae Judy, Francisca Bermudez, Nour Mimouni, Christopher J. Neylan, Dokyoon Kim, Daniel James Rader, Marylyn DeRiggi Ritchie, Benjamin F. Voight, Bogdan Paşaniuc, , Theodore G. Drivas

This study evaluates the reliability of coronary artery disease polygenic risk scores across diverse populations, finding poor individual agreement despite equivalent population-level performance.

JAMA · Nov 16, 2024Peer-reviewedGenetic & Genomic Medicine

Scratch-AID: A Deep-learning Based System for Automatic Detection of Mouse Scratching Behavior with High Accuracy

Huasheng Yu, Jingwei Xiong, Adam Yongxin Ye, Suna Li Cranfill, Tariq Cannonier, Mayank Gautam, Marina Yue Zhang, Rayan Bilal, Jong-Eun Park, Yuji Xue, Vidhur Polam, Zora Vujovic, Daniel Dai, William Ong, Jasper Ip, , Wenqin Luo

Scratch-AID automatically detects and quantifies mouse scratching behavior with high accuracy, outperforming manual methods in various itch models and drug screening applications.

eLife · Dec 8, 2022Peer-reviewedNeuroscience