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Dataset results
202 results for “transcription regulatory networks”
Predicting placenta transcriptional regulatory interactions based on spatial gene expression data and convolutional neural network
<p><strong>Aims:</strong> The dysfunction of placenta development is correlated to the defects of pregnancy and fetal growth. The detailed molecular mechanism of placenta development is not identified in human due to the lack of material in vivo. Image-based reconstructions of GRN are still very underdeveloped.</p> <p><strong>Methods and Results:</strong> In this study, first-trimester chorionic villus and decidua tissues were collected. Next, we present a machine-learning system to infer gene interaction networks of the human placenta from immunofluorescence images of trophoblast specific transcription factors obtained by a high-resolution scanner.</p> <p><strong>Conclusions:</strong> The experimental results show that deep learning models reveal regulatory roles that have not yet been fully recognized. The spatial expression data reveal new regulatory relationships that traditional experiments have failed to recognize, and has allowed the development of gene regulation networks based on the spatial distribution of gene expression. We demonstrate the effectiveness of this approach in building networks using high-resolution images of the human placenta. Our analysis is of certain significance for further exploration of the development of the placenta and the occurrence of pregnancy-related diseases in the future. The datasets and analysis provide a useful source for the researchers in the field of the maternal-fetal interface and the establishment of pregnancy.</p>
Simulations of gene regulatory networks with transcriptional adaptation
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Systematic dissection of transcriptional regulatory networks by genome-scale and single-cell CRISPR screens
Millions of putative transcriptional regulatory elements (TREs) have been cataloged in the human genome, yet their functional relevance in specific pathophysiological settings remains to be determined. This is critical to understand how oncogenic transcription factors (TFs) engage specific TREs to impose transcriptional programs underlying malignant phenotypes. Here, we combine cutting edge CRISPR screens and epigenomic profiling to functionally survey ≈15,000 TREs engaged by estrogen receptor (ER). We show that ER exerts its oncogenic role in breast cancer by engaging TREs enriched in GATA3, TFAP2C, and H3K27Ac signal. These TREs control critical downstream TFs, among which TFAP2C plays an essential role in ER-driven cell proliferation. Together, our work reveals novel insights into a critical oncogenic transcription program and provides a framework to map regulatory networks, enabling to dissect the function of the noncoding genome of cancer cells.
Data from: Temporal transcriptional logic of dynamic regulatory networks underlying nitrogen signaling and use in plants
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Systematic dissection of transcriptional regulatory networks by genome-scale and single-cell CRISPR screens
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Generation of transcriptional regulatory network of Lgr5+ small and large intestinal stem cells from mouse [scRNA-seq]
GEO Series GSE196915. Mus musculus. 1 samples. Type: Expression profiling by high throughput sequencing.
An experimentally supported model of the Bacillus subtilis global transcriptional regulatory network.
GEO Series GSE67023. Bacillus subtilis. 268 samples. Type: Expression profiling by array.
A Local Regulatory Network Around Three NAC Transcription Factors in Stress Responses and Senescence in Arabidopsis leaves (expression between lines at timepoints).
GEO Series GSE45183. Arabidopsis thaliana. 100 samples. Type: Expression profiling by array.
A coordinated regulatory network of ApiAP2 transcription factors involved in heterochromatic gene expression during Plasmodium falciparum blood-stage development [ChIP-Seq]
GEO Series GSE184658. Plasmodium falciparum. 144 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Characterizing cellular heterogeneity and homeostatic gene regulatory networks in the adult mammalian stria vascularis using single cell and single nucleus transcriptional profiling
GEO Series GSE136196. Mus musculus. 4 samples. Type: Expression profiling by high throughput sequencing.
ConnecTF: A platform to integrate validated transcription factor-target interactions to build and refine gene regulatory networks
GEO Series GSE152405. Arabidopsis thaliana. 56 samples. Type: Expression profiling by high throughput sequencing.
SND1 Transcription Factor-Directed Quantitative Functional Hierarchical Genetic Regulatory Network in Wood Formation in Populus trichocarpa
GEO Series GSE49911. Populus trichocarpa. 18 samples. Type: Expression profiling by high throughput sequencing.
Elucidating microRNA regulatory networks using transcriptional, post-transcriptional and histone modification measurements
GEO Series GSE61035. Mus musculus. 8 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing.
A hierarchical regulatory network ensures stable albumin transcription under various pathophysiological conditions
GEO Series GSE181201. Mus musculus. 12 samples. Type: Expression profiling by high throughput sequencing.
Mapping and dynamics of regulatory DNA and transcription factor networks in A. thaliana
GEO Series GSE53322. Arabidopsis thaliana. 20 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing.
A KMT2A-AFF1 gene regulatory network highlights the role of core transcription factors and reveals the regulatory logic of key downstream target genes [ChIP-seq]
GEO Series GSE151386. Homo sapiens. 15 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Inhibition of SP/KLF transcription regulatory network and histone deacetylases acts synergistically against H3K27M-DIPG
GEO Series GSE255013. Homo sapiens. 16 samples. Type: Expression profiling by high throughput sequencing.
Gene regulatory network analysis predicts cooperating transcription factor regulons required for FLT3-ITD+ AML growth [shRNA-seq]
GEO Series GSE236774. Homo sapiens. 22 samples. Type: Other.
MicroRNAs reinforce repression of PRC2 transcriptional targets independently and through a feed-forward regulatory network with PRC2 [RNA-seq]
GEO Series GSE112241. Homo sapiens. 12 samples. Type: Expression profiling by high throughput sequencing.
Investigation of post-transcriptional gene regulatory networks associated with autism spectrum disorders (ASD) by microRNA expression profiling of lymphoblastoid cell lines
GEO Series GSE21086. Homo sapiens; Mus musculus; Rattus norvegicus. 14 samples. Type: Non-coding RNA profiling by array.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.