Author

Bharani Nammi

The University of Texas at ArlingtonORCID 0009-0009-2149-5085Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2 Genomics· 1

Signature Assays, Organisms & Methods

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Assay:protein sequence· 3 Research Focus:cell type annotation· 2 Approach:deep learning· 2 Approach:transformer / foundation model· 2 Research Focus:benchmarking· 1 Research Focus:database / resource· 1 Approach:machine learning (classical)· 1 Research Focus:protein design· 1

Frequent Co-Authors

Jin LiuiD· 3 shared Sita Sirisha MadugulaiD· 3 shared Vindi M. Jayasinghe‐ArachchigeiD· 3 shared Maria ArtilesiD· 2 shared Pranav PujariD· 2 shared Shouyi WangiD· 2 shared Charlene Norgan RadleriD· 1 shared Dominic Mashburn· 1 shared

Activity by Year

2024-2025 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 38 mutual co-author links

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3 shared papersBioinformatics

Jin LiuORCID

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3 papers

Recent·Most cited

GenomicsbioRxivPreprintFeb 28, 2025

CasGen: A Regularized Generative Model for CRISPR Cas Protein Design with Classification and Margin-Based Optimization

Bharani Nammi, Vindi M. Jayasinghe‐Arachchige, Sita Sirisha Madugula…·Shouyi Wang

CasGen generates novel Cas9 and Cas12 proteins using a transformer-based model with margin-based regularization, achieving structural similarity and functional integrity.

4 citations

protein sequencedeep learning

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BioinformaticsJournal of Chemical Information and ModelingPeer-reviewedJun 5, 2024

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…·Jin Liu

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

6 citations

protein sequencemachine learning (classical)

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BioinformaticsbioRxivPreprintMar 2, 2024

Transformer-Based Deep Learning Model with Latent Space Regularization for CRISPR-Cas Protein Sequence Classification

Bharani Nammi, Sita Sirisha Madugula, Pranav Pujar…·Shouyi Wang

This paper develops two deep learning models for classifying CRISPR-Cas proteins, achieving high accuracy in distinguishing CAS from non-CAS and sub-classifying CAS9 and CAS12.

DOI 10.1101/2024.03.02.583136

protein sequencedeep learning

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