J. Ravichandran

Machine learning models for prediction of xenobiotic chemicals with high propensity to transfer into human milk

This study develops machine learning models to predict xenobiotic chemicals likely to transfer into human milk using a curated dataset of 375 chemicals and evaluates their performance on internal and external test data.

Identification of activity cliffs in structure-activity landscape of androgen receptor binding chemicals

The paper identifies activity cliffs in the structure-activity landscape of androgen receptor binding chemicals, revealing heterogeneity and improving predictive toxicity models.

Investigation of a derived adverse outcome pathway (AOP) network for endocrine-mediated perturbations

The paper constructs an endocrine-specific AOP network to analyze systems-level perturbations from endocrine disruption and identifies key events in the network.

Constitutive signaling by the C-terminal fragment of polycystin-1 is mediated by a tethered peptide agonist

This paper shows that the C-terminal fragment of polycystin-1 mediates signaling via a tethered peptide agonist mechanism, and that mutations in the stalk region affect this process.

NeurotoxKb: compilation, curation and exploration of a knowledgebase of environmental neurotoxicants specific to mammals

NeurotoxKb compiles and curates 475 mammalian-specific neurotoxicants from 835 studies, providing chemical, environmental, and toxicological data, and explores their exposure through global regulations and biospecimens.

ExHuMId: A curated resource and analysis of Exposome of Human Milk across India

ExHuMId compiles data on 101 environmental contaminants in human milk from 13 Indian states and analyzes their health impacts using systems biology.

An exploratory analysis of the current chemical regulations and guidelines from the perspective of endocrine disrupting chemicals using public resources

This paper analyzes endocrine disrupting chemicals (EDCs) by curating a knowledgebase and comparing EDCs with chemical regulations and high production volume chemicals, highlighting gaps between academic research and regulatory practices.