James J. Cai

This study identifies a stromal metabolic program in HER2-low breast cancer that suppresses NK-cell immunity, promoting tumor progression through BCAT1-dependent BCKA production.

The paper identifies IL-17A, STAT1, CEBPB, and cGAS-STING as key drivers of HIV-associated neuroinflammation using HIV-infected cerebral organoids and validates findings in a primate model.

The paper introduces scPII, a metric to quantify gene perturbation impact on single-cell transcriptomic networks using gene regulatory networks, showing strong correlation with CRISPR screen results.

This study shows that circadian rhythm disruption causes abnormal mammary morphology and aggressive basal tumorigenesis by increasing LILRB4 signaling and creating an immunosuppressive tumor microenvironment.

This paper introduces a method using Chatterjee's rank correlation to construct gene regulatory networks from scRNA-seq data, outperforming existing methods in capturing complex dependencies.

This study uses isogenic hiPSC-derived motor cortical organoids to identify HDAC6 hyperactivation as a key driver of SPG4 pathology and a potential therapeutic target.

The paper identifies functional diversification of MADS-box genes in Talaromyces marneffei, showing mads9 inhibits hyphal-to-yeast transition while mads10 does not.

This study shows that extracellular vesicles from hiPSC-derived neural stem cells protect human neurons from Aβ-42 oligomer-induced neurodegeneration, mitochondrial dysfunction, and tau phosphorylation.

This study shows aerobic exercise reduces M1 macrophages and CD8+ T cells in EAT of female pigs, decreasing inflammation and increasing PPARγ expression.

This study introduces scSGS, a method using single-cell RNA sequencing to identify gene function by analyzing stochastic gene silencing and differentially expressed genes.

This study investigates the role of RSPO3 in estrogen-mediated sex differences in body fat distribution using single-cell RNA sequencing and spatial transcriptomics in humans and mice.

This study shows that intranasally administered EVs from hiPSC-derived NSCs reduce microglial activation and improve brain function in an Alzheimer's model.

This paper introduces spline-DV, a method to analyze variability in scRNA-seq data, identifying genes with differential expression variability in conditions like obesity and cancer.

This study investigates the link between chromatin accessibility and single-cell expression variability using scATAC-seq and scRNA-seq data from human hematopoietic cells, finding that chromatin accessibility explains much of the variability.

This study identifies Ephrin A ligands in mouse cells as mediators of cell death signaling to human pluripotent stem cells during interspecies co-culture, enhancing chimera formation when inhibited.

This study identifies nuclear roles for testis-specific ACTL7A and ACTL7B in chromatin regulation during spermiogenesis, supported by in vivo data and AI-enhanced in silico modeling.

This study identifies inflammation in tumor-adjacent lung tissue as a predictor of clinical outcome in lung adenocarcinoma using multi-omic analysis of 143 stage I cases.

The paper introduces CrossmodalNet, an interpretable model that predicts surface protein expression from scRNA-seq data and incorporates temporal information to uncover gene-protein relationships.

The paper introduces rPanglaoDB, an R package for downloading and merging labeled single-cell RNA-seq data from PanglaoDB, and demonstrates its use in characterizing fibrocytes through data integration.

scTenifoldKnk predicts gene function via virtual knockout using scRNA-seq data from wild-type samples, recapitulating real-animal KO results.

scTenifoldNet constructs and compares single-cell gene regulatory networks using scRNA-seq data to identify gene expression changes in response to various biological conditions.

The paper evaluates mitochondrial proportion thresholds in scRNA-seq data across human and mouse tissues, proposing tissue-specific thresholds to improve QC accuracy.

The paper identifies genes and gene sets with increased expression variability in schizophrenia, linking this variability to genetic factors and brain development processes.

The paper analyzes single-cell expression variability in homogeneous human cell populations, finding it widespread, heritable, and functionally relevant.

scGEApp is a Matlab toolbox for scRNA-seq data analysis that includes feature selection, normalization, visualization, and enrichment analyses through a GUI.

The paper presents single-cell RNA sequencing data from two lymphoblastoid cell lines and their mixture, providing insights into population differentiation in gene expression and aiding normalization methods.