Jingjing Li

scRBP infers cell-specific RNA-binding protein regulons from single-cell transcriptomes, resolving targets at gene and isoform levels and linking genetic risk to disease.

The paper uses single-nucleus RNA-seq and spatial transcriptomics to show how the maternal-fetal interface diverges in structure and function between the basal plate and chorionic membranes, identifying NID2 as an ancestry-associated regulator of trophoblast invasion.

This study identifies genetic loci associated with Meniere's disease and links them to inner ear development and retinoic acid metabolism.

This study develops a single-cell proteomics workflow to analyze the developing human brain, revealing transcriptome-proteome discordance and identifying molecular vulnerabilities in neurodevelopmental disorders.

The paper introduces anticlustering to balance batches and minimize batch effects in high-throughput sequencing, showing improved balance compared to existing methods.

This study shows that α7 nicotinic acetylcholine receptors influence radial glia fate in human cortical development, with nicotine exposure altering neuronal differentiation and RG proliferation.

This study maps the molecular and cellular dynamics of the developing human neocortex using single-nucleus data, revealing gene regulatory networks and a cancer-related progenitor subtype.

The paper investigates the substructure and maturation of lamina-associated domains (LADs) in postmitotic neurons across human brain development, revealing dynamic changes in T1 and T2 LADs.

This study creates a comprehensive single-cell atlas of the maternal-fetal interface, identifying cell-type-specific dysregulation in pregnancy complications.

This study creates a cross-species proteomic map of synapse development in human, macaque, and mouse neocortex, revealing slower human PSD maturation and its potential link to neoteny.

The paper uses systems analysis to identify a molecular network in hypoplastic left heart syndrome, revealing novel factors and mechanisms through integration of genomic and transcriptomic data.

This study combines common and rare variant analyses with single-cell multiomics to identify cell-type-specific genetic risk factors for severe COVID-19, revealing molecular mechanisms and potential therapeutic targets.

This study identifies 690 candidate ALS genes using a hierarchical Bayesian model, highlighting genetic convergence on the distal axon and functional significance in motor neurons.