Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR30596966_1.fastq.gz | Fastqsanger.gz | |||
| SRR30596966_2.fastq.gz | Fastqsanger.gz |
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Project description:Human parvovirus B19 (B19V) infection can cause transient aplastic crisis, persistent viremia, and pure red-cell aplasia. In fetuses, B19V infection can result in non-immune hydrops fetalis and fetal death. To systematically investigate the interaction between B19V and erythoid progenetor cells (EPC), microarray was applied to systematically analyze the dynamic transcriptome of CD36+ EPCs during B19V infection.
2017-12-07 | GSE103460 | GEO
Project description:B19V NS1 is known to be cytotoxic and involved in the pathogenesis of B19V infection. Our previous data demonstrated that NS1 impaired the cell-cycle progression of the CD36+ EPCs by inducing a stable G2 arrest. Microarray analysis was used to identify genes whose expressions were associated with the NS1-induced G2 arrest. A total of 1045 genes displayed a more than 1.5-fold differential expression in the NS1-transduced cells. Out of 1045 differentially expressed genes, 177 were involved in cell-cycle regulation and 51 were involved in the regulation of cell differentiation. Keywords: RNA CD36+ EPCs were generated from CD34+ stem cells, and transduced with B19V NS1 or control-lentivirus for 12, 24,and 48 hours. Each sample has triplicates. There are 18 samples analyzed.
2010-11-03 | E-GEOD-18906 | biostudies-arrayexpress
Project description:B19V NS1 is known to be cytotoxic and involved in the pathogenesis of B19V infection. Our previous data demonstrated that NS1 impaired the cell-cycle progression of the CD36+ EPCs by inducing a stable G2 arrest. Microarray analysis was used to identify genes whose expressions were associated with the NS1-induced G2 arrest. A total of 1045 genes displayed a more than 1.5-fold differential expression in the NS1-transduced cells. Out of 1045 differentially expressed genes, 177 were involved in cell-cycle regulation and 51 were involved in the regulation of cell differentiation. Keywords: RNA
2010-11-03 | GSE18906 | GEO
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:An updated representation of S. meliloti metabolism that was manually-curated and encompasses information from 240 literature sources, which includes transposon-sequencing (Tn-seq) data and Phenotype MicroArray data for wild-type and mutant strains.
2020-06-01 | MODEL2003240001 | BioModels