Author

Dukka B. KC

Rochester Institute of TechnologyORCID 0000-0001-7443-1928Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 3

Signature Assays, Organisms & Methods

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Approach:deep learning· 3 Research Focus:benchmarking· 2 Research Focus:differential expression· 2 Assay:proteomics· 2 Approach:statistical model· 2 Approach:transformer / foundation model· 2 Approach:contrastive learning· 1 Organism:plant (other)· 1

Frequent Co-Authors

Pawel PratyushiD· 3 shared Suresh PokhareliD· 2 shared Bhawana PrasainiD· 1 shared Callen Carrier· 1 shared Hamid D. IsmailiD· 1 shared Kepha Barasa· 1 shared Meenal ChaudhariiD· 1 shared Stefan SchulzeiD· 1 shared

Activity by Year

2024-2026 · peak 1/yr

Co-Author Collaboration Network

8 top collaborators · 15 mutual co-author links

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3 shared papersBioinformatics

Pawel PratyushORCID

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3 papers

Recent·Most cited

BioinformaticsbioRxivPreprintAug 27, 2026

TaHL-PTM: Post-Translational Modification Prediction in Proteins via Target-Hooked Discriminative Fine-Tuning of Decoder-only Protein Language Models

Bhawana Prasain, Pawel Pratyush, Stefan Schulze, Dukka B. KC

TaHL-PTM improves PTM prediction by addressing tokenization issues in decoder-only PLMs, achieving better performance on residue-level tasks.

DOI 10.64898/2026.08.24.746791

proteomicsdeep learning

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BioinformaticsBioinformaticsPeer-reviewedMar 17, 2025

CaLMPhosKAN: Prediction of General Phosphorylation Sites in Proteins via Fusion of Codon Aware Embeddings with Amino Acid Aware Embeddings and Wavelet-based Kolmogorov Arnold Network

Pawel Pratyush, Callen Carrier, Suresh Pokharel…·Dukka B. KC

CaLMPhosKAN predicts phosphorylation sites by combining codon and amino acid embeddings with a wavelet-based KAN model, outperforming existing methods on independent test sets.

11 citations

proteomicsdeep learning

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BioinformaticsbioRxivPreprintOct 4, 2024

pLM-DBPs: Enhanced DNA-Binding Protein Prediction in Plants Using Embeddings From Protein Language Models

Suresh Pokharel, Kepha Barasa, Pawel Pratyush, Dukka B. KC

The paper develops pLM-DBPs, a tool for predicting DNA-binding proteins in plants using protein language model embeddings, achieving 83.8% MCC on an independent test set.

2 citations

plant (other)protein sequence

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