Lihua Jiang

The paper characterizes the promoter proximal proteome of FOXP2 using proximity labeling and mass spectrometry, identifying 373 enriched proteins and validating IRF2BP2 as a negative regulator of FOXP2 transcription.

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.

This study shows that many premalignant colorectal polyps contain multiple genetic lineages, indicating polyclonal origins rather than single-cell expansion.

The paper quantifies protein abundance across human tissues and identifies genetic factors influencing protein levels, revealing both shared and tissue-specific genetic architectures.

The paper improves experimental design and normalization for multiplex proteomics by introducing reference samples and technical replicates, and presents ProMix to enhance analysis performance.

The paper identifies 46,802 enhancers and 164 psychiatric disorder variants with regulatory effects in the developing cortex and organoids using massively parallel reporter assays and deep learning.

The paper generates a molecular neuroanatomical map of the human prefrontal cortex using spatial transcriptomics and single nucleus RNA-sequencing, revealing novel spatial domains and cell-cell interactions linked to psychiatric disorders.

This study tracks microbiome changes across four body sites in 86 participants over six years, revealing site-specific stability, individualized dynamics, and altered patterns in insulin-resistant individuals.

The paper analyzes multi-omic data from two pig heart xenografts in human decedents to identify immune and metabolic responses associated with rejection and injury.

This study identifies Nav1 as a gene regulating learning, memory, and responses to addictive drugs through synaptic balance changes in the cortex and hippocampus.

The paper uses long-read RNA-seq data to identify new transcripts and develop a tool to analyze genetic effects on transcript structure, revealing insights into splicing regulation and variant interpretation.

This paper develops a statistical method to identify gene co-essentiality, creating a genome-wide functional module almanac that predicts functions for 102 uncharacterized genes and validates key findings.

The paper identifies conserved 5'UTRs as regulators of translation and reveals their structural dynamics using a new method.

This paper introduces AdaReg, a data-adaptive robust estimation method for linear regression, showing improved performance on GTEx gene expression data compared to fixed gamma methods.

RobNorm is a normalization method for proteomics data that reduces systematic bias while preserving biological heterogeneity in heterogeneous samples.

The paper quantifies protein levels across 32 human tissues and compares them to transcriptome data, revealing insights into post-transcriptional regulation and disease mechanisms.

The paper assembles the pig-tailed macaque genome using linked-read sequencing and HiC scaffolding, achieving chromosome-level resolution and identifying large-scale chromosomal rearrangements with humans.

AdaTiSS provides a data-adaptive method to quantify tissue specificity scores for genes, improving comparability across tissues and genes.