Shreyes Rajan Madgaonkar

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.

TickMapKB is a spatial knowledgebase compiling tick species, pathogens, and associated data in India to aid in disease surveillance and resistance management.

This study constructs computational adverse outcome pathways for organic mercury toxicity in fish using an integrative network-based framework and curated toxicological data.

This paper introduces ReCAnt, a resource compiling data on 690 aquaculture chemicals and their ecotoxicity, highlighting regulatory gaps and environmental fate.

This study updates the DEDuCT database with 1043 EDCs and 796 endpoints from 3269 articles, constructs a toxicology knowledge graph, and aligns it with FAIR principles for EDC research and regulation.

This study uses network toxicology to analyze the toxic effects of inorganic arsenic and cadmium on human and ecosystem health, identifying 51 and 78 adverse outcome pathways respectively.

This paper creates a database of tattoo ink chemicals and their toxicities, identifying hazardous substances and regulatory coverage.

This study uses network-based frameworks to assess the ecotoxicological effects of petroleum hydrocarbons and their risks to aquatic ecosystems.

This study constructs a stressor-centric adverse outcome pathway network for plastic additives using toxicogenomic data, identifying 1287 additive-AOP associations and demonstrating their utility for risk assessment.