Ontology highlight
ABSTRACT:
PROVIDER: PRJNA475651 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR7309440_1.fastq.gz | Fastqsanger.gz | |||
| SRR7309440_2.fastq.gz | Fastqsanger.gz | |||
| SRR7345611_1.fastq.gz | Fastqsanger.gz | |||
| SRR7345611_2.fastq.gz | Fastqsanger.gz | |||
| SRR7345932_1.fastq.gz | Fastqsanger.gz |
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Project description:Single-cell RNA-seq of HeLa S3 cell line
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Project description:Maps of open chromatin in three primary human blood cell types of the myeloid lineage (megakaryocytes, erythroblasts and monocytes) using the formaldehyde-assisted isolation of regulatory elements method followed by next-generation sequencing (FAIRE-seq). We also generated FAIRE-seq data in the megakaryocytic cell line CHRF-288-11. In addition to our data sets, we retrieved FAIRE-seq data for the erythroblastoid cell line K562 (ENCODE Project Consortium 2012) and pancreatic islets (Gaulton et al. 2010), and reanalyzed these data sets using the same methodology.
2013-04-08 | GSE37916 | 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:We comprehensively investigating mutated peptide detection in HCT116 human cell line. We collected transcriptome and translatome data from HCT116, gather the sets of nsSNVs that are express in two different RNA level to construct two customized mutated protein libraries, in addition, a non-customized library was constructed utilizing nsSNVs downloaded from COSMIC database. MaxQuant was used to searched the libraries against shotgun MS data obtain from the same sample. Then, various characteristics of the detected mutated peptides were described, including identification number, identification overlap, and peptide quality.
2022-06-28 | PXD034951 |
Project description:We developed a method, ChIP-sequencing (ChIP-seq), combining chromatin immunoprecipitation (ChIP) and massively parallel sequencing to identify mammalian DNA sequences bound by transcription factors in vivo. We used ChIP-seq to map STAT1 targets in interferon stimulated and unstimulated human HeLa S3 cells, and compared the method's performance to ChIP-PCR and to ChIP-chip for four chromosomes. By ChIP-seq, using 15.1 and 12.9 million uniquely mapped sequence reads, and an estimated false discovery rate of less than 0.001, we identified 41,582 and 11,004 putative STAT1-binding regions in stimulated and unstimulated cells, respectively. Of the 34 loci known to contain STAT1 interferon-responsive binding sites, ChIP-seq found 24 (71%). ChIP-seq targets were enriched in sequences similar to known STAT1 binding motifs. Comparisons with two ChIP-PCR data sets suggested that ChIP-seq sensitivity was between 70% and 92% and specificity was at least 95%. Use ChIP-seq to map STAT1 targets in interferon-gamma (IFN-gamma)-stimulated and unstimulated human HeLa S3 cells, and compared the method's performance to ChIP-PCR and to ChIP-chip for four chromosomes
2009-03-23 | E-GEOD-15353 | biostudies-arrayexpress