Ana Cvejic

This study integrates single-cell multi-omics data from human foetal blood to show that trisomy restructures enhancer-gene maps, leading to dysregulated erythroid differentiation and haematological abnormalities in Down's Syndrome.

SMaSH identifies marker genes from single-cell RNA sequencing data to improve spatial transcriptomics analysis.

The paper introduces scAEspy, a tool using autoencoders to improve scRNA-seq data integration and cell-type identification by outperforming existing batch-effect removal methods.

This study identifies cell cycle regulation as a driver of endothelial-to-haematopoietic transition using single-cell transcriptomics in a human pluripotent stem cell system.

This paper develops a computational framework using variational autoencoders and graph autoencoders to model cell differentiation from single-cell RNA-seq data across species.

This study uses whole-genome sequencing of single-cell haematopoietic colonies to trace lineage and divergence of embryonic and extra-embryonic tissues in human fetal development.

This paper establishes a zebrafish rad51 loss-of-function model that recapitulates Fanconi anemia symptoms, showing hematopoietic defects and tumor predisposition upon p53 co-mutation.

The paper analyzes immune cell transcriptomes across vertebrates to reveal evolutionary patterns in gene conservation and turnover, finding higher gene turnover in NK cells compared to T cells.

This paper evaluates the sensitivity and accuracy of scRNA-seq protocols using spike-ins and a standardized pipeline, comparing sequencing depth trade-offs and RNA degradation effects.