Noah Cohen Kalafut

This study performs a single-nucleus transcriptome-wide association study to identify gene-trait associations in brain disorders, revealing cell-type-specific genetic regulation and ancestry-specific patterns.

The paper constructs a single-nucleus atlas of genetic regulation in the human brain, identifying cell-type-specific regulatory effects and disease-associated genes.

CellTRIP uses multi-agent reinforcement learning to infer dynamic virtual cell environments from single-cell gene expression data, enabling simulation and prediction of cell interactions and changes over time and space.

COSIME integrates multi-omics data to predict Alzheimer's disease phenotypes, improving accuracy and interpretability by analyzing feature interactions across data views.

NeuroTD infers time-varying neural activity delays using adaptive sliding windows, showing longer delays in hippocampal signals during working memory tasks and gene expression correlations in mouse motor cortex data.

MANGEM is a web app that aligns and analyzes neuronal multi-modal data using machine learning, enabling visualization and clustering of cells from different modalities.

JAMIE imputes and embeds multimodal single-cell data with partial modality matches, outperforming existing methods and providing mechanistic insights.

BOMA identifies conserved and specific developmental gene expression programs between human brains and organoids at cellular resolution.