Author

Jaisubasri Karthikeyan

PSG College of Technology

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Pharmacology & Toxicology· 1

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Approach:benchmark study· 1 Research Focus:benchmarking· 1 Approach:deep learning· 1 Approach:machine learning (classical)· 1 Assay:metagenomics· 1

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Areejit SamaliD· 1 shared Harshini Thangavel· 1 shared Nikhil ChivukulaiD· 1 shared Shreyes Rajan MadgaonkariD· 1 shared

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2026-2026 · peak 1/yr

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Areejit SamalORCID

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Pharmacology & ToxicologyComputational ToxicologyPeer-reviewedJul 21, 2026

Benchmarking Artificial Intelligence Models for Predicting Nuclear Receptor Activity from Tox21 Assays

Nikhil Chivukula, Jaisubasri Karthikeyan, Harshini Thangavel…·Areejit Samal

This study benchmarks AI models for predicting nuclear receptor activity using Tox21 assays, finding that tree-based models perform better on imbalanced data while deep learning shows robustness on moderate imbalances.

1 citation

metagenomicsmachine learning (classical)

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