Author

Na Zhu

Humboldt-Universität zu Berlin

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

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Biology Disciplines

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Bioinformatics· 1 Genetic & Genomic Medicine· 1

Signature Assays, Organisms & Methods

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Organism:human· 2 Approach:statistical model· 2 Assay:whole-exome sequencing· 2 Research Focus:variant calling· 1 Research Focus:variant effect prediction· 1

Frequent Co-Authors

Aiping MaoiD· 1 shared Alain VerloèsiD· 1 shared Alexej KnausiD· 1 shared Alfredo OrricoiD· 1 shared Allan BayatiD· 1 shared Angela Maria KaindliD· 1 shared Anna Keryan· 1 shared Anna Sarah Schossig· 1 shared

Activity by Year

2019-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 36 mutual co-author links

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1 shared paperGenetic & Genomic Medicine

Aiping MaoORCID

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2 papers

Recent·Most cited

Berrylyzer-an Efficient, Traceable, and Lightweight Intelligent Agentic System for Prenatal Genetic Diagnosis

Meng Meng, Ling Liu, Qianqian Du, Xinyao Zhou, Yuan Tian, Kuan Sun, Naiqi Li, Pinggui Zhang, Xianyi Lian, Ning Fan, Na Zhu, Shujing Li, Aiping Mao, Yuezhen Li, Gang Zou

Berrylyzer is a variant prioritization system for prenatal genetic diagnosis that outperforms existing tools in ranking diagnostic variants and recall rates.

medRxiv · Apr 4, 2026 · PreprintGenetic & Genomic Medicine

PEDIA: Prioritization of Exome Data by Image Analysis

Tzung‐Chien Hsieh, Martin A. Mensah, Jean Tori Pantel, Dione Aguilar, Omri Bar, Allan Bayat, Luis Eduardo Becerra-Solano, Heidi Beate Bentzen, Saskia Biskup, Oleg Borisov, Øivind Braaten, Claudia Ciaccio, Marie Coutelier, Kirsten Cremer, Magdalena Danyel, , Peter Michael Krawitz

The paper introduces an AI-driven method that uses facial images to prioritize exome data, achieving 99% top-10 accuracy in identifying disease-causing genes.

Genetics in Medicine · Jun 4, 2019Peer-reviewedBioinformatics