Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1074831 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR27921576_1.fastq.gz | Fastqsanger.gz | |||
| SRR27921576_2.fastq.gz | Fastqsanger.gz | |||
| SRR27921577_1.fastq.gz | Fastqsanger.gz | |||
| SRR27921577_2.fastq.gz | Fastqsanger.gz | |||
| SRR27921578_1.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 12 |
Similar Datasets
Project description:Thiele2013 - Bone marrow hematopoietic cells
The model of bone marrow hematopoietic 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: MODEL1310110030
.
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 | MODEL1310110030 | BioModels
Project description:Non-hematopoietic cells contribute essentially to hematopoiesis. However, heterogeneity and spatial organization of these cells in human bone marrow remain largely uncharacterized. We used single-cell RNA sequencing (scRNA-Seq) to profile 29,325 non-hematopoietic cells and discovered nine transcriptionally distinct subtypes. We simultaneously profiled 53,417 hematopoietic cells and predicted their interactions with non-hematopoietic subsets. We employed Co-Detection by Indexing (CODEX) to spatially profile over one million single cells with a novel 53-antibody panel. We integrated scRNA-Seq and CODEX data to link cellular signaling and spatial proximity. Spatial analysis also revealed a hyperoxygenated arterio-endosteal niche for early myelopoiesis, and an adipocytic, but not endosteal or perivascular, localization for early hematopoietic stem and progenitor cells. We used our CODEX atlas to automatically annotate cell types in new bone marrow images and uncovered MSC expansion and leukemic blast/MSC-enriched spatial neighborhoods in AML patient samples. This comprehensive, spatially-resolved multiomic atlas of human bone marrow serve as a reference for future investigation of cellular interactions that drive hematopoiesis.
2024-04-24 | GSE253355 | GEO
Project description:The paper describes a model of tumor invasion to bone marrow.
Created by COPASI 4.26 (Build 213)
This model is described in the article:
Modeling invasion of metastasizing cancer cells to bone marrow utilizing ecological principles
Kun-Wan Chen, Kenneth J Pienta
Theoretical Biology and Medical Modelling 2011, 8:36
Abstract:
Background: The invasion of a new species into an established ecosystem can be directly compared to the steps involved in cancer metastasis. Cancer must grow in a primary site, extravasate and survive in the circulation to then intravasate into target organ (invasive species survival in transport). Cancer cells often lay dormant at their metastatic site for a long period of time (lag period for invasive species) before proliferating (invasive spread). Proliferation in the new site has an impact on the target organ microenvironment (ecological impact) and eventually the human host (biosphere impact).
Results: Tilman has described mathematical equations for the competition between invasive species in a structured habitat. These equations were adapted to study the invasion of cancer cells into the bone marrow microenvironment as a structured habitat. A large proportion of solid tumor metastases are bone metastases, known to usurp hematopoietic stem cells (HSC) homing pathways to establish footholds in the bone marrow. This required accounting for the fact that this is the natural home of hematopoietic stem cells and that they already occupy this structured space. The adapted Tilman model of invasion dynamics is especially valuable for modeling the lag period or dormancy of cancer cells.
Conclusions: The Tilman equations for modeling the invasion of two species into a defined space have been modified to study the invasion of cancer cells into the bone marrow microenvironment. These modified equations allow a more flexible way to model the space competition between the two cell species. The ability to model initial density, metastatic seeding into the bone marrow and growth once the cells are present, and movement of cells out of the bone marrow niche and apoptosis of cells are all aspects of the adapted equations. These equations are currently being applied to clinical data sets for verification and further refinement of the models.
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.
2024-09-02 | BIOMD0000000793 | BioModels
Project description:The paper describes a model of tumor invasion to bone marrow.
Created by COPASI 4.26 (Build 213)
This model is described in the article:
Modeling invasion of metastasizing cancer cells to bone marrow utilizing ecological principles
Kun-Wan Chen, Kenneth J Pienta
Theoretical Biology and Medical Modelling 2011, 8:36
Abstract:
Background: The invasion of a new species into an established ecosystem can be directly compared to the steps involved in cancer metastasis. Cancer must grow in a primary site, extravasate and survive in the circulation to then intravasate into target organ (invasive species survival in transport). Cancer cells often lay dormant at their metastatic site for a long period of time (lag period for invasive species) before proliferating (invasive spread). Proliferation in the new site has an impact on the target organ microenvironment (ecological impact) and eventually the human host (biosphere impact).
Results: Tilman has described mathematical equations for the competition between invasive species in a structured habitat. These equations were adapted to study the invasion of cancer cells into the bone marrow microenvironment as a structured habitat. A large proportion of solid tumor metastases are bone metastases, known to usurp hematopoietic stem cells (HSC) homing pathways to establish footholds in the bone marrow. This required accounting for the fact that this is the natural home of hematopoietic stem cells and that they already occupy this structured space. The adapted Tilman model of invasion dynamics is especially valuable for modeling the lag period or dormancy of cancer cells.
Conclusions: The Tilman equations for modeling the invasion of two species into a defined space have been modified to study the invasion of cancer cells into the bone marrow microenvironment. These modified equations allow a more flexible way to model the space competition between the two cell species. The ability to model initial density, metastatic seeding into the bone marrow and growth once the cells are present, and movement of cells out of the bone marrow niche and apoptosis of cells are all aspects of the adapted equations. These equations are currently being applied to clinical data sets for verification and further refinement of the models.
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.
2024-09-02 | BIOMD0000000795 | BioModels
Project description:Spatial transcriptomic profiling was performed on whole bone marrow sections from KrasG12D/+ and wild-type mice. Frozen 10-µm bone marrow sections were processed by Biomarker Technologies Corporation (Beijing, China) following standard spatial transcriptomics procedures, including tissue fixation, H&E staining, permeabilization, reverse transcription, and spatial cDNA library construction. Libraries were sequenced on an Illumina NovaSeq 6000 (PE150). Spot-level gene expression matrices were generated using BSTMatrix, aligned with corresponding bright-field images, and tissue-covered spots were identified for downstream analysis. Spatial mapping revealed spatially resolved patterns of gene expression and cellular organization within bone marrow. These data provide comprehensive spatial transcriptomic information enabling investigation of bone marrow architecture and microenvironmental interactions in Kras-driven JMML.
2026-03-31 | GSE313878 | GEO
Project description:The generation of blood cells in the hematopoietic microenvironment requires support from mesenchymal cells. We found that stably growing cell populations derived from individually sorted human bone marrow mesenchymal cells immortalized by enforced expression of hTERT comprised both supportive and non-supportive clones. We compared gene expression of supportive and non-supportive clones to identify genes associated with the growth supportive capacity of mesenchymal cells Keywords: Cell type comparison
2021-01-22 | GSE10292 | GEO
Project description:The skeletal system plays a pivotal role in the human body, and bone-related diseases present an urgent public health challenge. Understanding the bone microenvironment is essential for elucidating the mechanisms underlying bone homeostasis and developing innovative therapeutic strategies for bone diseases such as osteoporosis and osteoarthritis. In this study, we applied spatial and single-cell transcriptomic assays on bone tissue from human femur to comprehensively characterize the multi-dimensional cellular landscape of the human bone marrow microenvironment. We identified one niche related to bone formation and characterized cell-cell communication within bone marrow. Notably, we performed comprehensive dependency analysis, uncovering critical cellular relationships and molecular dependencies within the bone ecosystem. By mapping spatial distributions of gene expression, cellular composition, and pathway activities, we constructed a high-resolution atlas of the human bone microenvironment. This atlas not only delineates the intricate cellular architecture but also illuminates key molecular processes and dependencies governing bone metabolism.
2024-12-18 | GSE284089 | GEO
Project description:Bone marrow stromal cells (BMSCs) provide hematopoietic support, immunoregulation and contain a stem cell fraction capable of skeletogenic differentiation. A heterogeneous population of primary bone marrow BMSCs were isolated from a single human donor (FH181), and a lentiviral expression system was used to overexpress human telomerase reverse transcriptase (hTERT) and generate single cell-derived immortalised BMSC lines for multi-level analysis of functional markers for BMSC subsets. All clones expressed typical BMSC cell surface antigens, however clones Y101 and Y201 displayed typical BMSC tri-lineage differentiation capacity where clones Y102 and Y202 lacked significant tri-lineage differentiation potential. High quality RNA samples were isolated from all lines, and global gene expression analysis was performed in triplicate arrays (using Agilent SurePrint G3 Human Gene Expression 8x60K v2 Microarrays) in order to identify distinguishing characteristics of these lines, compared to the parental primary BMSCs from which they were derived.
2015-07-23 | E-MTAB-3511 | biostudies-arrayexpress
Project description:We analyzed the effect of Calr deficiency on Mac1 and Gr1 positive bone marrow cells using hematopoietic cell specific Calr knockout (Mx-cre;Calrf/-) mice and control (Mx-cre;Calr+/+) mice.
2020-07-31 | PXD014854 | JPOST Repository
Project description:To solve the heterogeniety of human bone marrow non-hematopoietic cells, we perfomed transcriptomic profiling of bone marrow non-hematopoietic cells using scRNAseq.
2023-03-12 | GSE190965 | GEO