Author

Harshini Thangavel

PSG College of Technology

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Biology Disciplines

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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

Frequent Co-Authors

Areejit SamaliD· 1 shared Jaisubasri Karthikeyan· 1 shared Nikhil ChivukulaiD· 1 shared Shreyes Rajan MadgaonkariD· 1 shared

Activity by Year

2026-2026 · peak 1/yr

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4 top collaborators · 6 mutual co-author links

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1 shared paperPharmacology & Toxicology

Areejit SamalORCID

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1 paper

Recent·Most cited

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

Nikhil Chivukula, Jaisubasri Karthikeyan, Harshini Thangavel, Shreyes Rajan Madgaonkar, 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.

Computational Toxicology · Jul 21, 2026Peer-reviewedPharmacology & Toxicology