Anat Kreimer

This study examines how different SETD1A mutations and genetic backgrounds affect human hippocampal neurons derived from hiPSCs, revealing divergent molecular and cellular phenotypes and contrasting mutation impacts.

The paper identifies 92 functional regulatory variants associated with adolescent idiopathic scoliosis using massively parallel reporter assays in chondrocytes.

The paper identifies tissue-specific molecular changes in paraspinal muscle and spinal cartilage in AIS patients, linking non-coding genetic risk variants to dysregulated developmental pathways.

This paper introduces MPRabc, an MPRA-informed model that improves enhancer-gene interaction prediction across cell types.

The paper investigates XCI erosion in CRISPR-edited female iPSCs and their derived neurons, showing variable erosion in iPSCs and preserved XIST effects on gene expression in neurons.

This study examines how polygenic risk scores for Alcohol Use Disorder affect microglial responses to ethanol exposure in human iPSC-derived microglia.

This study investigates how rare mutations in the SETD1A gene affect human neurons, showing they disrupt synaptic function and may contribute to schizophrenia pathophysiology.

The paper constructs enhancer-promoter interaction networks during neural differentiation and identifies their temporal dynamics and disease-associated variant enrichment using computational and experimental methods.

This paper evaluates sequence design strategies for perturbation MPRA using a computational framework and finds that random nucleotide shuffling outperforms other methods.

The paper uses perturbation assays to study how regulatory elements guide neural differentiation over time, identifying sequence-driven activity and environmental effects on transcription.

The paper maps chromatin accessibility in developing human brain and organoids using scATAC-seq, revealing cell type-specific regulatory elements and their role in neurodevelopment.

MPRAnalyze provides a statistical framework for analyzing MPRA data to estimate regulatory sequence effects and compare differential activity across conditions.

The paper performs a meta-analysis of MPRA datasets to predict regulatory activity and identifies cell-type specific features affecting accuracy.

The paper characterizes regulatory dynamics during neural induction using genomic assays and computational tools, identifying key transcription factors and functional regulatory elements.

This study identifies antibiotic-induced changes in gene expression and regulation in HepG2 cells using RNA-seq and ChIP-seq.