Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR22269026_1.fastq.gz | Fastqsanger.gz | |||
| SRR22269026_2.fastq.gz | Fastqsanger.gz | |||
| SRR22269027_1.fastq.gz | Fastqsanger.gz | |||
| SRR22269027_2.fastq.gz | Fastqsanger.gz | |||
| SRR22269028_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:Evaluating Detection of small RNA derived fragments from small RNA-seq data
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Project description:Intervention type:DRUG. Intervention1:Huaier, Dose form:GRANULES, Route of administration:ORAL, intended dose regimen:20 to 60/day by either bulk or split for 3 months to extended term if necessary. Control intervention1:None.
Primary outcome(s): For mRNA libraries, focus on mRNA studies. Data analysis includes sequencing data processing and basic sequencing data quality control, prediction of new transcripts, differential expression analysis of genes. Gene Ontology (GO) and the KEGG pathway database are used for annotation and enrichment analysis of up-regulated genes and down-regulated genes.
For small RNA libraries, data analysis includes sequencing data process and sequencing data process QC, small RNA distribution across the genome, rRNA, tRNA, alignment with snRNA and snoRNA, construction of known miRNA expression pattern, prediction New miRNA and Study of their secondary structure Based on the expression pattern of miRNA, we perform not only GO / KEGG annotation and enrichment, but also different expression analysis.. Timepoint:RNA sequencing of 240 blood samples of 80 cases and its analysis, scheduled from June 30, 2022..
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Project description:RNA-seq and small RNA-seq data in boot mutant ovaries
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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:Panagrellus redivivus Small RNA-Seq data (the microworm)
| PRJNA186507 | ENA
Project description:Data analysis is a critical part of quantitative proteomics studies in interpreting biological questions. Numerous computational tools including protein quantification, imputation, and differential expression (DE) analysis were generated in the past decade. However, searching optimized tools is still an unsolved issue. Moreover, due to the rapid development of RNA-Seq technology, a vast number of DE analysis methods are created. Applying these newly developed RNA-Seq-oriented tools to proteomics data is still a question that needs to be addressed. In order to benchmark these analysis methods, a proteomics dataset constituted the proteins derived from human, yeast, and drosophila with different ratios were generated. Based on this dataset, DE analysis tools (including array-based and RNA-Seq based), imputation algorithms, and protein quantification methods were compared and benchmarked. This study provided useful information on analyzing quantitative proteomics datasets. All the methods used in this study were integrated into Perseus which are available at https://www.maxquant.org/perseus.
2022-11-16 | PXD029891 | JPOST Repository