Nikhil Chivukula

This paper introduces AgingHallmarksDB, a resource for systems-level analysis of aging hallmarks and associated genes, demonstrating its utility through various analyses of disease and transcriptome data.

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.

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.

This study constructs the first adverse outcome pathway network for inorganic cadmium toxicity by integrating data from multiple sources and analyzing key events and relationships.

ViCEKb compiles 113 unique chemical triggers of vitiligo from literature, standardizes chemical data, and highlights their biological impacts and regulatory status.

T9GPred predicts Type 9 secretion system, gliding motility, and associated secreted proteins in Bacteroidetes strains using curated experimental data and signal domain analysis.

EPEK compiles and analyzes gene, metabolite, and SNP expression data from human ectopic pregnancy studies to identify potential diagnostic markers and cellular signaling processes involved.