Author

Pranav Pujar

The University of Texas at ArlingtonORCID 0009-0009-7962-3713Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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

Frequent Co-Authors

Bharani NammiiD· 2 shared Jin LiuiD· 2 shared Sita Sirisha MadugulaiD· 2 shared Vindi M. Jayasinghe‐ArachchigeiD· 2 shared Dominic Mashburn· 1 shared Maria ArtilesiD· 1 shared Shouyi WangiD· 1 shared Shouyi WangiD· 1 shared

Activity by Year

2024-2024 · peak 2/yr

Co-Author Collaboration Network

9 top collaborators · 32 mutual co-author links

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2 shared papersBioinformatics

Bharani NammiORCID

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2 papers

Recent·Most cited

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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