Author

Shouyi Wang

The University of Texas at ArlingtonORCID 0000-0002-9046-6474Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Pharmacology & Toxicology· 1

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Research Focus:database / resource· 1 Approach:deep learning· 1 Approach:machine learning (classical)· 1 Research Focus:protein folding & dynamics· 1 Assay:protein sequence· 1 Approach:statistical model· 1

Frequent Co-Authors

Jin LiuiD· 2 shared Sita Sirisha MadugulaiD· 2 shared Vindi M. Jayasinghe‐ArachchigeiD· 2 shared Bharani NammiiD· 1 shared Charlene Norgan RadleriD· 1 shared Dominic Mashburn· 1 shared Maria ArtilesiD· 1 shared Pranav PujariD· 1 shared

Activity by Year

2024-2025 · peak 1/yr

Co-Author Collaboration Network

9 top collaborators · 31 mutual co-author links

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2 shared papersPharmacology & Toxicology

Jin LiuORCID

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2 papers

Recent·Most cited

Structure-Based Classification of CRISPR/Cas9 Proteins: A Machine Learning Approach to Elucidating Cas9 Allostery

Sita Sirisha Madugula, Vindi M. Jayasinghe‐Arachchige, Charlene Norgan Radler, Shouyi Wang, Jin Liu

This paper uses machine learning to identify allosteric networks in Cas9, revealing key residues and an electrostatic valley that stabilize its structure and specificity.

Journal of Molecular Biology · Nov 9, 2025Peer-reviewedPharmacology & Toxicology

Identification of Family-Specific Features in Cas9 and Cas12 Proteins: A Machine Learning Approach Using Complete Protein Feature Spectrum

Sita Sirisha Madugula, Pranav Pujar, Bharani Nammi, Shouyi Wang, Vindi M. Jayasinghe‐Arachchige, Tyler Pham, Dominic Mashburn, Maria Artiles, Jin Liu

The paper uses machine learning to identify distinguishing features of Cas9 and Cas12 proteins, finding specific tripeptides important for their function.

Journal of Chemical Information and Modeling · Jun 5, 2024Peer-reviewedBioinformatics