Author

Shuxin Zhang

The University of Melbourne

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

Biology Disciplines

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Bioinformatics· 1 Genetic & Genomic Medicine· 1 Genomics· 1

Signature Assays, Organisms & Methods

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Research Focus:differential expression· 2 Approach:experimental assay· 2 Assay:long-read sequencing· 2 Research Focus:benchmarking· 1 Assay:DNA methylation· 1 Research Focus:gene regulatory network inference· 1 Organism:human· 1 Approach:statistical model· 1

Frequent Co-Authors

Jessie J.‐Y. ChangiD· 2 shared Jianshu ZhangiD· 2 shared Lachlan CoiniD· 2 shared Ailin WeiiD· 1 shared An N.T. Nguyen· 1 shared Ang Li· 1 shared Benjamin Reames· 1 shared Chang Jian GaoiD· 1 shared

Activity by Year

2023-2025 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 19 mutual co-author links

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Curved chords = mutual co-authorship

2 shared papersGenomics

Jessie J.‐Y. ChangORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Customizable host and viral transcript enrichment using CRISPR-Cas9 long-read sequencing for isoform discovery and validation

An N.T. Nguyen, Jianshu Zhang, Shuxin Zhang, Miranda E. Pitt, Devika Ganesamoorthy, Svenja Fritzlar, Jessie J.‐Y. Chang, Sarah L. Londrigan, Lachlan Coin

This study uses CRISPR-Cas9 to enrich specific transcripts for long-read sequencing, enabling efficient and accurate isoform discovery and low abundance transcript detection.

bioRxiv · Apr 11, 2025 · PreprintGenomics

Using synthetic RNA to benchmark poly(A) length inference from direct RNA sequencing.

Jessie J.‐Y. Chang, Xuan Yang, Haotian Teng, Jianshu Zhang, Benjamin Reames, Shuxin Zhang, Vincent Corbin, Lachlan Coin

The paper benchmarks poly(A) tail-length estimation tools using synthetic RNA standards, finding all tools accurate within 12% and recommending Dorado for its speed and ease of use.

GigaScience · Jan 1, 2025Peer-reviewedBioinformatics

Integrated fragmentomic profile and 5-Hydroxymethylcytosine of capture-based low-pass sequencing data enables pan-cancer detection via cfDNA

Zhidong Zhang, Xuenan Pi, Chang Jian Gao, Jun Zhang, Xia Lin, Xiaoqin Yan, Xinlei Hu, Ziyue Yan, Shuxin Zhang, Ailin Wei, Yuer Guo, Jingfeng Liu, Ang Li, Xiaolong Liu, Wei Zhang, , Dan Xie

The paper develops an integrated model using fragmentomic and 5-hydroxymethylcytosine features from low-pass sequencing data to achieve high sensitivity and specificity in pan-cancer detection.

Translational Oncology · May 18, 2023Peer-reviewedGenetic & Genomic Medicine