Hananeh Aliee

This study creates a single-cell multiomics atlas of B cell development in prenatal and adult bone marrow and in vitro models, identifying novel cell subsets and molecular signatures.

inVAE improves cell state identification by disentangling biological and technical variation in single-cell data, outperforming existing methods across multiple human tissues.

The paper introduces muBind, a deep learning model that predicts genomic counts from DNA sequences and cell relationships, enhancing understanding of regulatory dynamics during cell transitions.

The paper identifies a shared inflammatory glial cell signature after brain injury using spatial and single-cell transcriptomics in mice, showing common injury-regulated genes across astrocytes, microglia, and oligodendrocyte precursor cells.

The paper identifies fibroblast-like cell types as key drivers of heart regeneration in zebrafish using single-cell transcriptomics and lineage tracing.

Sfaira provides a data and model zoo for single-cell RNA-seq, enabling fast reuse of pre-trained models and datasets across human and mouse tissues.

AutoGeneS automatically selects genes for RNA-seq deconvolution by optimizing multiple criteria, improving accuracy in identifying cell-type proportions from bulk RNA samples.

Across 1,176,683 airway and lung cells from 22 datasets, ACE2 rises with age, in males and in smokers' multiciliated cells, and is lowest in young children.