Ayush Noori

SHEPHERD uses few-shot learning and a knowledge graph to improve diagnosis of rare genetic diseases using simulated data and real-world patient cohorts.

This paper introduces a multimodal foundation model for predicting protein phenotypes using sequence, structure, and natural language, showing competitive performance and novel insights into disease-related proteins.

The paper examines transcriptomic changes in Alzheimer's disease brain regions associated with Aβ plaques, tangles, and APOE ε4, finding distinct gene expression patterns linked to neuroinflammation and neuronal dysfunction.

This study uses single-nucleus RNA-sequencing to analyze astrocyte transcriptomic changes across the spatiotemporal progression of Alzheimer's disease, revealing gene expression trajectories and heterogeneity.

The paper describes the generation and characterization of 301 new LexA enhancer trap lines in Drosophila through an international network of educational institutions.

The paper describes the generation and characterization of novel LexA enhancer trap lines in Drosophila through a collaborative interscholastic network.