Single-cell transcriptomic analysis reveals a novel cell state and switching genes during hepatic stellate cell activation in vitro

[1] Parola M(2019)Liver fibrosis: pathophysiology, pathogenetic targets and clinical issues Mol Aspects Med 65 37-55

[2] Pinzani M(2015)Pathobiology of liver fibrosis: a translational success story Gut 64 830-841

[3] Lee YA(2016)Promising therapy candidates for liver fibrosis Front Physiol 7 47-1847.e8

[4] Wallace MC(2019)Single-cell transcriptomics uncovers zonation of function in the mesenchyme during liver fibrosis Cell Rep 29 1832-420

[5] Friedman SL(2019)Single cell RNA sequencing identifies subsets of hepatic stellate cells and myofibroblasts in liver fibrosis Cells 8 503-502

[6] Wang P(2018)Integrating single-cell transcriptomic data across different conditions, technologies, and species Nat Biotechnol 36 411-982

[7] Koyama Y(2018)Structure—aware principal component analysis for single-cell RNA-seq data J Comput Biol 33 495-3275

[8] Liu X(2015)Spatial reconstruction of single-cell gene expression data Nat Biotechnol 14 979-425

[9] Xu J(2017)Reversed graph embedding resolves complex single-cell trajectories Nat Methods 36 3273-30

[10] Ma HY(2020)GeneSwitches: ordering gene expression and functional events in single-cell experiments Bioinformatics 1 417-482

[1] Parola M(2019)Liver fibrosis: pathophysiology, pathogenetic targets and clinical issues Mol Aspects Med 65 37-55

[2] Pinzani M(2015)Pathobiology of liver fibrosis: a translational success story Gut 64 830-841

[3] Lee YA(2016)Promising therapy candidates for liver fibrosis Front Physiol 7 47-1847.e8

[4] Wallace MC(2019)Single-cell transcriptomics uncovers zonation of function in the mesenchyme during liver fibrosis Cell Rep 29 1832-420

[5] Friedman SL(2019)Single cell RNA sequencing identifies subsets of hepatic stellate cells and myofibroblasts in liver fibrosis Cells 8 503-502

[6] Wang P(2018)Integrating single-cell transcriptomic data across different conditions, technologies, and species Nat Biotechnol 36 411-982

[7] Koyama Y(2018)Structure—aware principal component analysis for single-cell RNA-seq data J Comput Biol 33 495-3275

[8] Liu X(2015)Spatial reconstruction of single-cell gene expression data Nat Biotechnol 14 979-425

[9] Xu J(2017)Reversed graph embedding resolves complex single-cell trajectories Nat Methods 36 3273-30

[10] Ma HY(2020)GeneSwitches: ordering gene expression and functional events in single-cell experiments Bioinformatics 1 417-482