Similar Datasets
Project description:By analyzing brain cerebral cortex transcriptome, we provide the gene expression profile from diverse cell types from brain.
2022-12-31 | GSE197360 | GEO
Project description:Single cell RNA-seq for brain cerebral cortex transcriptome
| PRJNA810030 | ENA
Project description:Single cell RNA-seq for brain cerebral cortex transcriptome
| PRJNA649578 | ENA
Project description:Thiele2013 - Cerebral cortex neuronal cells
The model of cerebral cortex neuronal 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: MODEL1310110033
.
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 | MODEL1310110033 | BioModels
Project description:Thiele2013 - Cerebral cortex glial cells
The model of cerebral cortex glial 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: MODEL1310110064
.
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 | MODEL1310110064 | BioModels
Project description:The complexity of the mature adult brain is a result of both developmental processes and experience-dependent circuit formation. One way to look at the process of brain development is to examine gene expression changes, and previous studies have used microarrays to address this in a global manner. However, the transcriptome is more complex than gene expression levels alone, as both alternative splicing and RNA editing occur to generate a more diverse set of mature transcripts. The aim of the current study was to develop a high-resolution transcriptome dataset of mouse cortical development using RNA sequencing (RNA-Seq), thus assaying exon usage and RNA editing as well as overcoming some of the inherent limitations of microarrays. We found a large number of differentially expressed genes, but also altered splicing and RNA editing between embryonic and adult cerebral cortex. Each dataset was validated both technically and biologically, and in each case tested we found our RNA-Seq observations to have high predictive validity. We propose this dataset, and the accompanying analysis, to be a helpful resource in the understanding of changes in gene expression during development. Three young adult cerebral cortices four embryonic cerebral cortices
2013-02-10 | E-GEOD-39866 | biostudies-arrayexpress
Project description:Transcriptome Analysis of the Mouse Cerebral Cortex in Brain ischemia Injury Model
| PRJNA1129118 | ENA
Project description:<p><strong>BACKGROUND:</strong> The protozoan parasite Toxoplasma gondii infects and alters the neurotransmission in cerebral cortex and other brain regions, leading to neurobehavioral and neuropathologic changes in humans and animals. However, the molecules that contribute to these changes remain largely unknown.</p><p><strong>METHODS:</strong> We have investigated the impact of T. gondii infection on the overall metabolism of mouse cerebral cortex. Mass-spectrometry-based metabolomics and multivariate statistical analysis were employed to discover metabolomic signatures that discriminate between cerebral cortex of T. gondii-infected and uninfected control mice.</p><p><strong>RESULTS:</strong> Our results identified 73, 67 and 276 differentially abundant metabolites, which were involved in 25, 37 and 64 pathways at 7, 14 and 21 days post-infection (dpi), respectively. Metabolites in the unsaturated fatty acid biosynthesis pathway were upregulated as the infection progressed, indicating that T. gondii induces the biosynthesis of unsaturated fatty acids to promote its own growth and survival. Some of the downregulated metabolites were related to pathways, such as steroid hormone biosynthesis and arachidonic acid metabolism. Nine metabolites were identified as T. gondii responsive metabolites, namely galactosylsphingosine, arachidonic acid, LysoSM(d18:1), L-palmitoylcarnitine, calcitetrol, 27-Deoxy-5b-cyprinol, L-homophenylalanine, oleic acid and ceramide (d18:1/16:0).</p><p><strong>CONCLUSIONS:</strong> Our data provide novel insight into the dysregulation of the metabolism of the mouse cerebral cortex during T. gondii infection and have important implications for studies of T. gondii pathogenesis.</p>
2020-04-23 | MTBLS770 | MetaboLights
Project description:Study on selective vulnerability of certain brain regions to oxidative stress. Here we selected 4 brain regions (hippocampal CA1 and CA3, cerebral cortex, and cerebellar granular layer) to study this phenomenon. Experiment Overall Design: Neurons were collected from the 4 regions of the rat brain and subjected to Affymetrix RAE230A analysis, in order to identify genes related to the differential vulnerability of the neurons to oxidative stress.
2008-04-07 | E-GEOD-7139 | biostudies-arrayexpress
Project description:We analyzed transcriptomic characteristic of motor cortex from Sprague-Dawley rats brain with cerebral ischemia and reperfusion (CIR).
2024-01-12 | GSE222704 | GEO