Yifan Wang

The paper uses single-cell DNA sequencing to analyze somatic mosaicism in postmortem lung and colon tissues, revealing mutation heterogeneity, chromosomal abnormalities, and cellular ancestry.

This study identifies MmpE as a nucleomodulin in Mycobacterium tuberculosis that inhibits host inflammatory gene expression and promotes intracellular survival by targeting the VDR promoter and regulating the PI3K-Akt-mTOR pathway.

HEARTSVG identifies spatially variable genes in spatial transcriptomic data with high accuracy and efficiency, uncovering biologically significant patterns in colorectal cancer.

This study uses single-cell transcriptomics to show reduced interneurons and microglia activation in TS basal ganglia, linking gene expression changes to impaired striatal function.

The paper uses MPRA in forebrain organoids to validate enhancer activity in early human neurodevelopment, identifying over 2,300 enhancers with temporal-specific activity.

This study identifies 69 mutated genes in malformations of cortical development using multiomic profiling of 317 brain resections and single-cell sequencing.

DeepMosaic detects mosaic single nucleotide variants without control samples using deep convolutional neural networks, achieving high accuracy and uncovering many variants missed by existing methods.

The paper evaluates brain somatic mosaicism in the adult human to identify rules governing cellular distribution during embryogenesis.

The paper identifies prenatal mutational processes in schizophrenia brains linked to transcription factor binding sites and proposes a new term 'skiagenesis' for these mutations.

SearcHPV identifies and assembles HPV-host integration sites in cancer with higher sensitivity and specificity than existing methods.

This study identifies somatic SNVs in non-cancerous human brain tissues and establishes best practices for detecting low-frequency variants.

The paper tracks cell lineages in humans using post-zygotic mutations and finds lineage imbalance and correlations with developmental axes.

The paper introduces a machine learning method to detect somatic L1 insertions in human brain tissue, revealing their widespread distribution in neurons and glia and potential role in neuropsychiatric diseases.

The paper examines how learning and sleep affect ribosomal mRNA profiles in hippocampal neurons, finding that sleep loss disrupts post-learning transcript changes more in active neurons.