Author

Navleen Kaur

Institute for Bioscience and Biotechnology Research

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· 2

Signature Assays, Organisms & Methods

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Organism:bacteria (other)· 1 Research Focus:benchmarking· 1 Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1 Approach:machine learning (classical)· 1 Assay:protein sequence· 1 Assay:proteomics· 1 Approach:transformer / foundation model· 1

Frequent Co-Authors

Antonio CardoneiD· 2 shared David P. HoogerheideiD· 2 shared Frank HeinrichiD· 2 shared Jeffery B. KlaudaiD· 2 shared Kinjal MondaliD· 2 shared Sarala PadiiD· 2 shared Ella Mihailescu· 1 shared Mihaela Mihailescu· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 41 mutual co-author links

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2 shared papersBioinformatics

Antonio CardoneORCID

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2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintNov 4, 2026

XAMPGen: An Interpretable SI Pipeline For Novel Antimicrobial Peptide Discovery

Kinjal Mondal, Sarala Padi, Navleen Kaur…·Antonio Cardone

This paper introduces XAMPGen, an interpretable generative model for discovering novel antimicrobial peptides using fine-tuned protein language models and explainable AI techniques.

DOI 10.64898/2026.11.03.764041

proteomicsdeep learning

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BioinformaticsbioRxivPreprintJun 1, 2026

Species- and Topic-aware Representation Learning for Antimicrobial Peptide Discovery

Sarala Padi, Kinjal Mondal, Navleen Kaur…·Walid Keyrouz

This paper introduces STAMP, a machine learning framework for predicting antimicrobial peptide efficacy across bacterial species, achieving strong predictive performance and real-world validation.

DOI 10.64898/2026.05.28.728246

bacteria (other)protein sequence

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