Jia-Jun Liu

This study identifies RBBP5 as an essential epigenetic regulator of the 12h oscillator and proteostasis, linking it to metabolic and cellular homeostasis in mammals.

This study identifies Fibulin-2 as a matrix cue that transduces fibrotic ECM remodeling into mitochondrial metabolic reprogramming in kidney fibrosis.

The paper uses AI to analyze pancreatic islet composition in type 1 diabetes, finding age, sex, and region-dependent changes and beta-cell loss with reciprocal cell expansion.

This study shows that loss of Profilin1 reduces plasma membrane PIP2 levels, linking actin regulation to PIP2 homeostasis and revealing Pfn1's broader role in lipid metabolism.

This study shows that deleting both Sox9 and Yap1 eliminates cholangiocarcinoma by blocking transcriptional compensation, suggesting co-targeting as a therapeutic strategy.

This study identifies Mfap2 as a key ECM component that regulates kidney repair by linking mechanical cues to metabolic reprogramming through Esr2-mediated transcriptional control.

The paper analyzes transcriptome diversity in alcohol-related liver disease to identify novel pathways and genes not detected by differential expression analysis.

This study identifies SALL4 as a regulator of YAP1-driven hepatocyte-to-cholangiocyte reprogramming, showing its role in both malignant and regenerative liver processes.

This study uses deep spatial sequencing to reveal differential immune responses in HCC and benign liver tissues, showing more intense HCC cell responses to immune cells.

This paper describes a mouse model with a human ADAR G1007R mutation that causes neuroinflammation and shows that deleting MDA5 can reverse brain inflammation.

This study evaluates manual gating, unsupervised clustering, and auto-gating methods for high-dimensional cytometry data using six datasets and provides practical guidelines for selecting appropriate methods.

IFDlong is a tool for detecting and quantifying isoform and fusion transcripts in long-read RNA-seq data, showing high accuracy and performance in simulations and real datasets.

This study compares the AVITI and Illumina sequencing chemistries for DNA and RNA short-read and long-read sequencing, finding AVITI has higher quality scores and lower error rates in short-read applications.