Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA400277 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR5974290.fastq.gz | Fastqsanger.gz | |||
| SRR5974291.fastq.gz | Fastqsanger.gz | |||
| SRR5974292.fastq.gz | Fastqsanger.gz | |||
| SRR5974293.fastq.gz | Fastqsanger.gz | |||
| SRR5974294.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 14 |
Similar Datasets
Project description:Gene expression patterns define the hepatocyte-like cells derived by different strategies [ChIP-seq]
| PRJNA400276 | ENA
Project description:Gene expression patterns define the hepatocyte-like cells derived by different strategies
| PRJNA400163 | ENA
Project description:RNA sequence analysis of HBV genome inserted iPS cells derived hepatocyte
| PRJDB11601 | ENA
Project description:Comparative analysis of hESCs and iPSCs-derived hepatocyte-like cells reveals current drawbacks and possible strategies for improved differentiation
| PRJNA134097 | ENA
Project description:Kilian2024 - Immune cell dynamics in Cue-Induced Extended Human Colitis Model
Single-cell technologies such as scRNA-seq and flow cytometry provide critical insights into immune cell behavior in inflammatory bowel disease (IBD). However, integrating these datasets into computational models for dynamic analysis remains challenging. Here, Kilian et al., (2024) developed a deterministic ODE-based model that incorporates these technologies to study immune cell population changes in murine colitis. The model parameters were optimized to fit experimental data, ensuring an accurate representation of immune cell behavior over time. It was then validated by comparing simulations with experimental data using Pearson’s correlation and further tested on independent datasets to confirm its robustness. Additionally, the model was applied to clinical bulk RNA-seq data from human IBD patients, providing valuable insights into immune system dynamics and potential therapeutic strategies.
Figure 4c, obtained from the simulation of human colitis model is highlighted here.
This model is described in the article:
Kilian, C., Ulrich, H., Zouboulis, V.A. et al. Longitudinal single-cell data informs deterministic modelling of inflammatory bowel disease. npj Syst Biol Appl 10, 69 (2024). https://doi.org/10.1038/s41540-024-00395-9
Abstract:
Single-cell-based methods such as flow cytometry or single-cell mRNA sequencing (scRNA-seq) allow deep molecular and cellular profiling of immunological processes. Despite their high throughput, however, these measurements represent only a snapshot in time. Here, we explore how longitudinal single-cell-based datasets can be used for deterministic ordinary differential equation (ODE)-based modelling to mechanistically describe immune dynamics. We derived longitudinal changes in cell numbers of colonic cell types during inflammatory bowel disease (IBD) from flow cytometry and scRNA-seq data of murine colitis using ODE-based models. Our mathematical model generalised well across different protocols and experimental techniques, and we hypothesised that the estimated model parameters reflect biological processes. We validated this prediction of cellular turnover rates with KI-67 staining and with gene expression information from the scRNA-seq data not used for model fitting. Finally, we tested the translational relevance of the mathematical model by deconvolution of longitudinal bulk mRNA-sequencing data from a cohort of human IBD patients treated with olamkicept. We found that neutrophil depletion may contribute to IBD patients entering remission. The predictive power of IBD deterministic modelling highlights its potential to advance our understanding of immune dynamics in health and disease.
This model was curated during the Hackathon hosted by BioMed X GmbH in 2024.
2025-03-07 | MODEL2502180001 | BioModels
Project description:In patients with hepatocellular carcinoma (HCC) meeting the Milan criteria, liver transplantation (LT) is an effective therapy. This study aims to define the survival-related molecular biological features helping precisely identifying the patients with HCC beyond the Milan criteria who have acceptable outcomes. In the derivation cohort (n = 122), integrated analyses of tumor tissues are conducted using RNA sequencing (RNA-seq), proteomic landscape and transposase-accessible chromatin sequencing (ATAC-seq). Based on transcriptomics, three subgroups that significantly differ in overall survival were identified in the derivation cohort, and these findings are validated in an independent cohort. In-depth bioinformatics analysis using RNA-seq and proteomics reveals that the promotion of cancer stemness by cancer-associated fibroblasts (CAFs) can be responsible for the negative biological characteristics observed in high-risk HCC patients. The ATAC-seq identifies key factors regulating transcription, which may bridge CAF infiltration and stemness. Finally, we demonstrate that the CAF-derived CXCL12 sustains the stemness of HCC cells by promoting XRCC5 through CXCR4.
2025-02-24 | PXD061119 |
Project description:Hepatocytes are the predominant cell type in the liver and execute numerous essential biological functions. However, the crucial events and putative regulators during hepatocyte maturation require in-depth investigation. In this study, we performed single-cell and single-nucleus RNA-seq (scRNA-seq and snRNA-seq) to explore the developmental process of hepatocytes. We defined three maturation stages of postnatal hepatocytes, each of which establishes specific metabolic functions and exhibits distinct strategies for regulating proliferation. Hepatic zonation is gradually formed during hepatocyte maturation. The cells or nuclei of different ploidy exhibit zonation preferences in distribution, and asynchrony in the hepatocyte maturation pathway. In addition, combining gene regulatory network analysis and in vivo genetic manipulation, we identified critical maturation- and zonation-related transcription factors. This study not only delineates comprehensive transcriptomic profiles of hepatocyte maturation, but also presents a paradigm to identify functional genes in the development of hepatocyte maturation and zonation by combining genetic manipulation and measuring coordinates in a single-cell developmental trajectory.
2023-06-26 | GSE209749 | GEO
Project description:Enrichment of pluripotent stem cell-derived hepatocyte-like cells
| PRJNA341955 | ENA
Project description:Expression analysis of Hepatocyte like-cells derived SHEDs (SHED-Hep cells)
| PRJNA352165 | ENA
Project description:We devised two hepatocyte differentiation methods, namely Method 1 (M1) and Method 2 (M2), through modifying existing well-known hepatocyte differentiation strategies, and compared the resultant cells phenotypically, functionally and transcriptomically at different stages of hepatocyte differentiation. !Series_summary =We used microarrays to compare the global gene expression of the HLCs differentiated using the two methods, M1 and M2.
2021-11-03 | GSE187011 | GEO