Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR27103885.fastq.gz | Fastqsanger.gz | |||
| SRR27103886.fastq.gz | Fastqsanger.gz | |||
| SRR27103887.fastq.gz | Fastqsanger.gz | |||
| SRR27103888.fastq.gz | Fastqsanger.gz | |||
| SRR27103889.fastq.gz | Fastqsanger.gz |
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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..
| 2612481 | ecrin-mdr-crc
Project description:Primary objectives: Characterization of the macrophage population subset that is modulated by enteric neurons
Primary endpoints: Characterization of the macrophage population subset that is modulated by enteric neurons via RNA sequencing
| 2538227 | ecrin-mdr-crc
Project description:Intervention type:DRUG
Name of intervention:Huaier
Dose form / Japanese Medical Device Nomenclature:GRANULES
Route of administration / Site of application:ORAL
Dose per administration:20?
g
Dosing frequency / Frequency of use:OTHER, SPECIFY
20g? per day
Planned duration of intervention:3 months to extending if necessary
Intended dose regimen:20 to 60/day by either bulk or split for 3 months to extended term if necessary
detailes of teratment arms:hepatocellular carcinoma, breast cancer, colorectal cancer and related gastrointestinal cancers, urologic cancers including prostate cancer, pancreas cancer, and lung cancer, etc.
Comparative intervention name:None
Dose form / Japanese Medical Device Nomenclature:
Route of administration / Site of application:
Dose per administration:
Dosing frequency / Frequency of use:
Planned duration of intervention:
Intended dose regimen:
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.
Study Design: Comparative test, None, No, open(masking not used), EXPLORATORY
| 98681 | ecrin-mdr-crc
Project description:Analysis of the covalent attachment of GMP to the RNA dependent RNA polymerase proteins of equine arteritis virus and SARS-CoV-2 proteins using heavy-isotope assisted MS and MS/MS peptide sequencing.
2020-07-30 | MSV000085857 | MassIVE
Project description:Proteogenomic analysis and genomic profiling, RNA-sequencing, and mass spectrometry-based analysis of High hyperdiploid childhood acute lymphoblastic leukemia.
2020-01-29 | MSV000084862 | MassIVE
Project description:Collombet2016 - Lymphoid and myeloid cell
specification and transdifferentiation
This model is described in the article:
Logical modeling of lymphoid
and myeloid cell specification and transdifferentiation
Samuel Collombet, Chris van Oevelen,
Jose Luis Sardina Ortega, Wassim Abou-Jaoudé, Bruno Di
Stefano, Morgane Thomas-Chollier, Thomas Graf, and Denis
Thieffry
Proceedings of the National Academy of
Sciences of the United States of America
Abstract:
Blood cells are derived from a common set of hematopoietic
stem cells, which differentiate into more specific progenitors
of the myeloid and lymphoid lineages, ultimately leading to
differentiated cells. This developmental process is controlled
by a complex regulatory network involving cytokines and their
receptors, transcription factors, and chromatin remodelers.
Using public data and data from our own molecular genetic
experiments (quantitative PCR, Western blot, EMSA) or
genome-wide assays (RNA-sequencing, ChIP-sequencing), we have
assembled a comprehensive regulatory network encompassing the
main transcription factors and signaling components involved in
myeloid and lymphoid development. Focusing on B-cell and
macrophage development, we defined a qualitative dynamical
model recapitulating cytokine-induced differentiation of common
progenitors, the effect of various reported gene knockdowns,
and the reprogramming of pre-B cells into macrophages induced
by the ectopic expression of specific transcription factors.
The resulting network model can be used as a template for the
integration of new hematopoietic differentiation and
transdifferentiation data to foster our understanding of
lymphoid/myeloid cell-fate decisions.
This model is hosted on
BioModels Database
and identified by:
MODEL1610240000.
To cite BioModels Database, please use:
BioModels Database:
An enhanced, curated and annotated resource for published
quantitative kinetic models.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to
the public domain worldwide. Please refer to
CC0
Public Domain Dedication for more information.
2017-06-08 | MODEL1610240000 | BioModels
Project description:Blood cells are derived from a common set of hematopoietic stem cells, which differentiate into more specific progenitors of the myeloid and lymphoid lineages, ultimately leading to differentiated cells. This developmental process is controlled by a complex regulatory network involving cytokines and their receptors, transcription factors, and chromatin remodelers. Using public data and data from our own molecular genetic experiments (quantitative PCR, Western blot, EMSA) or genome-wide assays (RNA-sequencing, ChIP-sequencing), we have assembled a comprehensive regulatory network encompassing the main transcription factors and signaling components involved in myeloid and lymphoid development. Focusing on B-cell and macrophage development, we defined a qualitative dynamical model recapitulating cytokine-induced differentiation of common progenitors, the effect of various reported gene knockdowns, and the reprogramming of pre-B cells into macrophages induced by the ectopic expression of specific transcription factors. The resulting network model can be used as a template for the integration of new hematopoietic differentiation and transdifferentiation data to foster our understanding of lymphoid/myeloid cell-fate decisions.
| 8186 | Cell Collective
Project description:Subsequently, using a combination of BSA-seq, transcriptomic sequencing (RNA-seq), and proteomic sequencing approaches, we identified the candidate gene Nitab4.5_0008674g0010 that encodes dihydroneopterin aldolase as a factor associated with tobacco leaf yellowing.
2024-06-15 | PXD053162 |
Project description:Microbiome sequencing model is a Named Entity Recognition (NER) model that identifies and annotates microbiome nucleic acid sequencing method or platform in texts. This is the final model version used to annotate metagenomics publications in Europe PMC and enrich metagenomics studies in MGnify with sequencing metadata from literature. For more information, please refer to the following blogs: http://blog.europepmc.org/2020/11/europe-pmc-publications-metagenomics-annotations.html https://www.ebi.ac.uk/about/news/service-news/enriched-metadata-fields-mgnify-based-text-mining-associated-publications
2022-02-21 | MODEL2202170012 | BioModels
Project description:Long-range RNA-RNA pairing impacts the genome structure and function of SARS-CoV-2 variants. To understand structure and function relationships of different SARS-CoV-2 variants that have emerged during the COVID-19 pandemic, we performed high throughput structure probing and modelling of the genomic structures of the wildtype (WT), Alpha, Beta, Delta and Omicron variants of the SARS-CoV-2. We observed that genomes of SARS-CoV-2 variants are generally structurally conserved, and that single nucleotide variations (SNVs) and interactions with RNA binding proteins (RBPs) can impact RNA structures across the viruses. Importantly, using proximity ligation sequencing, we identified many conserved ultra-long-range RNA-RNA interactions, including one that spans more than 17kb in both the WT virus and Omicron variant. We showed that mutations that disrupt this 17kb long-range interacting structure reduce virus fitness at late stages of its infection cycle, while compensatory mutations partially restore virus fitness. Additionally, we showed that this ultra-long-range RNA-RNA interaction binds directly to ADAR1 to alter the RNA editing levels on the viral genome. These studies deepen our understanding of RNA structures in SARS-CoV-2 genome and their ability to interact with host factors to facilitate virus infectivity.
2025-07-30 | PXD065815 | JPOST Repository