BP_September_2016_ChIPmentation_Germinal_Center_B-Cell-Like_Diffuse_Large_B-Cell_Lymphoma_from_lymph_node,_on_Genome_GRCh38 - sa
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ABSTRACT:
PROVIDER: EGAD00001002946 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:ChIPmentation data for 2 sample(s) Activated B-Cell-Like Diffuse Large B-Cell Lymphoma from lymph node, on Genome GRCh38. 3 run(s), 3 experiment(s), 3 alignment(s). Part of BLUEPRINT (September 2016).
| EGAD00001002944 | EGA
Project description:ChIPmentation data for 1 sample(s) for germinal center B cell from tonsil, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).
| EGAD00001002932 | EGA
Project description:ChIPmentation data for 3 sample(s) Lymphoma_Follicular from lymph node, on Genome GRCh38. 7 run(s), 6 experiment(s), 6 alignment(s). Part of BLUEPRINT (September 2016).
| EGAD00001002931 | EGA
Project description:ChIPmentation data for 3 sample(s) Burkitt Lymphoma from lymph node, on Genome GRCh38. 10 run(s), 8 experiment(s), 8 alignment(s). Part of BLUEPRINT (September 2016).
| EGAD00001002939 | EGA
Project description:Thiele2013 - Lymph node germinal center cells
The model of lymph node germinal center cells metabolism is derived from the community-driven global reconstruction of human metabolism (version 2.02, MODEL1109130000
).
This model is described in the article:
A community-driven global reconstruction of human metabolism.
Thiele I, et al
.
Nature Biotechnology
Abstract:
Multiple models of human metabolism have been reconstructed, but each represents only a subset of our knowledge. Here we describe Recon 2, a community-driven,
consensus 'metabolic reconstruction', which is the most comprehensive representation of human metabolism that is applicable to computational modeling. Compared
with its predecessors, the reconstruction has improved topological and functional features, including ~2x more reactions and ~1.7x more unique metabolites. Using
Recon 2 we predicted changes in metabolite biomarkers for 49 inborn errors of metabolism with 77% accuracy when compared to experimental data. Mapping metabolomic
data and drug information onto Recon 2 demonstrates its potential for integrating and analyzing diverse data types. Using protein expression data, we automatically
generated a compendium of 65 cell type-specific models, providing a basis for manual curation or investigation of cell-specific metabolic properties. Recon 2 will
facilitate many future biomedical studies and is freely available at http://humanmetabolism.org/.
This model is hosted on BioModels Database
and identified by: MODEL1310110036
.
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.
2005-01-01 | MODEL1310110036 | BioModels
Project description:Thiele2013 - Lymph node non germinal center cells
The model of lymph node non germinal center cells metabolism is derived from the community-driven global reconstruction of human metabolism (version 2.02, MODEL1109130000
).
This model is described in the article:
A community-driven global reconstruction of human metabolism.
Thiele I, et al
.
Nature Biotechnology
Abstract:
Multiple models of human metabolism have been reconstructed, but each represents only a subset of our knowledge. Here we describe Recon 2, a community-driven,
consensus 'metabolic reconstruction', which is the most comprehensive representation of human metabolism that is applicable to computational modeling. Compared
with its predecessors, the reconstruction has improved topological and functional features, including ~2x more reactions and ~1.7x more unique metabolites. Using
Recon 2 we predicted changes in metabolite biomarkers for 49 inborn errors of metabolism with 77% accuracy when compared to experimental data. Mapping metabolomic
data and drug information onto Recon 2 demonstrates its potential for integrating and analyzing diverse data types. Using protein expression data, we automatically
generated a compendium of 65 cell type-specific models, providing a basis for manual curation or investigation of cell-specific metabolic properties. Recon 2 will
facilitate many future biomedical studies and is freely available at http://humanmetabolism.org/.
This model is hosted on BioModels Database
and identified by: MODEL1310110007
.
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.
2005-01-01 | MODEL1310110007 | BioModels
Project description:We performed V(D)J scRNA sequencing to find transcriptional and B cell receptor repertoire differences in the germinal center of the draining lymph node of mice born to mothers chronically infected with Schistosoma mansoni. Cite-seq was used to help identify antigen specific cells.
2024-05-01 | GSE205376 | GEO
Project description:The survival of patients with diffuse large-B-cell lymphoma after chemotherapy is influenced by molecular features of the tumors. We used the gene-expression profiles of these lymphomas to develop a molecular predictor of survival. METHODS: Biopsy samples of diffuse large-B-cell lymphoma from 240 patients were examined for gene expression with the use of DNA microarrays and analyzed for genomic abnormalities. Subgroups with distinctive gene-expression profiles were defined on the basis of hierarchical clustering. A molecular predictor of risk was constructed with the use of genes with expression patterns that were associated with survival in a preliminary group of 160 patients and was then tested in a validation group of 80 patients. The accuracy of this predictor was compared with that of the international prognostic index. RESULTS: Three gene-expression subgroups--germinal-center B-cell-like, activated B-cell-like, and type 3 diffuse large-B-cell lymphoma--were identified. Two common oncogenic events in diffuse large-B-cell lymphoma, bcl-2 translocation and c-rel amplification, were detected only in the germinal-center B-cell-like subgroup. Patients in this subgroup had the highest five-year survival rate. To identify other molecular determinants of outcome, we searched for individual genes with expression patterns that correlated with survival in the preliminary group of patients. Most of these genes fell within four gene-expression signatures characteristic of germinal-center B cells, proliferating cells, reactive stromal and immune cells in the lymph node, or major-histocompatibility-complex class II complex. We used 17 genes to construct a predictor of overall survival after chemotherapy. This gene-based predictor and the international prognostic index were independent prognostic indicators.
2016-12-07 | GSE90953 | GEO
Project description:Productive B cell responses are critical to protect a host from infection. The spleen and lymph nodes are populated by resting follicular B cells, which can enter germinal centers upon antigen encounter. Once in the germinal center, B cells migrate between the dark and light zones, where they undergo somatic hypermutation and selection, respectively. While germinal center B cells have been studied, an intense molecular understanding of these cells/subsets (and the differences between them) is lacking.
2020-04-06 | PXD015524 | Pride
Project description:ATAC-seq data for 2 sample(s) for germinal center B cell from tonsil, on Genome GRCh38. 2 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT (September 2016).
| EGAD00001002917 | EGA