Sayali Anil Alatkar

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.

The paper constructs a gene regulatory network resource across species and brain regions to study neurogenesis dynamics and their links to neurodevelopmental disorders.

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.

DeepGAMI improves phenotype prediction from multimodal data by integrating biological knowledge and imputing missing modalities, outperforming existing methods and providing interpretable insights.

CMOT infers missing single-cell modalities using optimal transport, outperforming existing methods and producing biologically interpretable results.

The paper uses single-cell multi-omics data to predict gene regulatory networks in Alzheimer's disease and control, identifying cell-type-specific dysregulation and potential drug targets.