Aayushi Mittal

MutAIverse: An AI-Powered, Mechanism-backed Platform for Discovering Novel DNA Adducts and their precursor Genotoxins

MutAIverse detects known and novel DNA adducts and their precursor genotoxins using an AI-driven platform with mechanistic modeling and spectral mapping.

Deep Learning Reveals Endogenous Sterols as Allosteric Modulators of the GPCR-Gα Interface

The paper identifies endogenous sterols as intracellular allosteric modulators of the GPCR-Gα interface using a deep learning toolkit and experimental validation.

Chemical Dice Integrator (CDI): A Scalable Framework for Multimodal Molecular Representation Learning

The paper introduces CDI, a framework that unifies multiple molecular representations into a single embedding, achieving better predictive performance than individual methods.

Simultaneous visualization of cells and marker genes from scRNA-seq studies

Stardust is a visualization method that embeds cells and marker genes together on a 2D map, performing competitively with existing tools on scRNA-seq and spatial transcriptomics data.

Artificial Intelligence uncovers carcinogenic human metabolites

The paper develops Metabokiller, an AI model that predicts carcinogenic human metabolites by analyzing their biochemical properties and validates predictions through experimental assays.