Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR22301449_1.fastq.gz | Fastqsanger.gz | |||
| SRR22301449_2.fastq.gz | Fastqsanger.gz | |||
| SRR22301450_1.fastq.gz | Fastqsanger.gz | |||
| SRR22301450_2.fastq.gz | Fastqsanger.gz | |||
| SRR22301451_1.fastq.gz | Fastqsanger.gz |
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Project description:The first GSSM of V. vinifera was reconstructed (MODEL2408120001). Tissue-specific models for stem, leaf, and berry of the Cabernet Sauvignon cultivar were generated from the original model, through the integration of RNA-Seq data. These models have been merged into diel multi-tissue models to study the interactions between tissues at light and dark phases.
2024-09-02 | MODEL2408160001 | BioModels
Project description:In the current work, we present the first proteogenomic dataset of GBM clinical samples to date. We have assembled a cohort of 87 GBM patients of varying survival rates and performed MS-based proteomics analysis as well as RNA-seq in order to identify the molecular differences associated with survival and examine the contribution of each layer to GBM landscape. We show that each layer alone only partially reflects patient survival, but RNA-protein integration identifies clear patterns of layer-specific and layer-common processes specifically contributing to either short-term or long-term survival of patients. Furthermore, we compare our data to published single-cell RNA-seq of GBM tumors and evaluate the RNA-protein variability within single-cell based tumor subpopulations. We found that while all signatures of the four subpopulations tend to have high RNA-protein correlation, each signature is associated differently with survival. Altogether, these results highlight the potential of proteogenomics to further stratify heterogeneity in GBM tumors and identify processes contributing to poorer survival.
2021-04-16 | PXD018024 | Pride
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:QTL-seq for heading date in SYF2
| PRJDB5617 | ENA