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151
datasets available to search
ShareScore release 0.9.0
Dataset results
151 results for “network scaling”
Artificial neural networks enable genome-scale simulations of intracellular signaling
GEO Series GSE202515. Homo sapiens. 190 samples. Type: Expression profiling by high throughput sequencing.
Genome-scale identification of transcription factors that mediate an inflammatory network during breast cellular transformation
GEO Series GSE100259. Homo sapiens. 43 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing.
DeepC: Predicting chromatin interactions using megabase scaled deep neural networks and transfer learning (Tiled-C)
GEO Series GSE137436. Homo sapiens. 2 samples. Type: Other.
Large-Scale Identification of Coregulated Enhancer Networks in the Adult Human Brain
GEO Series GSE40465. Homo sapiens. 151 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
An Integrated Approach to Reconstructing Genome-scale Transcriptional Regulatory Networks [Affymetrix]
GEO Series GSE58553. Cereibacter sphaeroides 2.4.1; Cereibacter sphaeroides. 11 samples. Type: Expression profiling by array.
Factors Driving Diversity in Gene Regulatory Networks at Genome Scale[main]
GEO Series GSE267880. Brachypodium distachyon. 214 samples. Type: Expression profiling by high throughput sequencing.
Transcriptome analyses of reprogrammed feather / scale chimeric explants revealed co-expressed epithelial gene networks during organ specification
GEO Series GSE111101. Gallus gallus. 22 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing.
Large-scale transcriptomic analyses reveal a global co-expression network of cellulase and xylanase genes in filamentous fungi
GEO Series GSE133258. Penicillium oxalicum. 72 samples. Type: Expression profiling by high throughput sequencing.
Factors Driving Diversity in Gene Regulatory Networks at Genome Scale[ASE]
GEO Series GSE267878. Brachypodium distachyon. 24 samples. Type: Expression profiling by high throughput sequencing.
Genome-scale identification of SARS-CoV-2 and pan-coronavirus host factor networks
GEO Series GSE162038. synthetic construct; Homo sapiens. 80 samples. Type: Other.
A Genome-Scale TF-DNA Interaction Network for Transcriptional Regulation of Arabidopsis Primary and Specialized Metabolism
GEO Series GSE137623. Arabidopsis thaliana. 64 samples. Type: Expression profiling by high throughput sequencing.
The ChAHP chromatin remodelling complex regulates a network of neurodevelopmental disorder risk genes to scale the production of neocortical layers (cut&run-seq)
GEO Series GSE255599. Mus musculus. 8 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
The Sweden Canceromics Analysis Network - Breast (SCAN-B) Initiative: a large-scale multicenter infrastructure towards implementation of breast cancer genomic analyses in the clinical routine [RNA-Seq
GEO Series GSE60788. Homo sapiens. 55 samples. Type: Expression profiling by high throughput sequencing.
Genome-scale reconstruction of the sigma factor network in E. coli
GEO Series GSE46737. Escherichia coli str. K-12 substr. MG1655. 6 samples. Type: Expression profiling by high throughput sequencing.
Mapping gene regulatory networks in Drosophila eye development by large-scale transcriptome perturbations and motif inference. [RNA-seq]
GEO Series GSE59059. Drosophila melanogaster. 80 samples. Type: Expression profiling by high throughput sequencing.
Integrating Large-Scale Functional Genomic Data to Dissect the Complexity of Yeast Regulatory Networks
GEO Series GSE11111. Saccharomyces cerevisiae. 9 samples. Type: Expression profiling by array.
Genome-Scale Transcriptional Regulatory Network Models of Psychiatric and Neurodegenerative Disorders
GEO Series GSE102122. Homo sapiens. 16 samples. Type: Expression profiling by array.
Personalized Large-scale Functional Networks in the Adolescent Brain Cognitive Development (ABCD) Children
<ul><li>Data for our paper "<strong>Personalized Large-scale Functional Networks in ABCD Children: Linking Functional Network Topography with Socioeconomic Status</strong>".</li><li>This dataset contains personalized functional networks for <strong>3,921</strong> participants (age 9- and 10-year-olds) who had more than 20 min of high-quality (mean motion < 0.2mm) resting-state fMRI data from the Adolescent Brain Cognitive Development (<strong>ABCD</strong>) Study.</li><li>Using regularized non-negative matrix factorization (<strong>NMF</strong>) and preprocessed resting-state fMRI data from the ABCD-BIDS Community Collection (<strong>https://github.com/ABCD-STUDY/nda-abcd-collection-3165</strong>, NDA Collection 3165), we parcellated the cortex (<strong>fsLR_32k space</strong>) into 17 functional networks for each ABCD participant.</li><li>We provided two kinds of atlas data: discrete network parcellation (<strong>IndivAtlasLabel</strong>) and probabilistic network parcellation (<strong>IndivAtlasLoading</strong>). For discrete network parcellation, each value in the dscalar indicates which network this vertex belongs to; for probabilistic network parcellation, each value indicates the probability that this vertex belongs to each network (<strong>17 in total</strong>). We also provided group atlas label and atlas loading for comparison.</li><li>For dscalars contain individual atlas loading, we separated participants into 10 parts, each has nearly 400 individuals for easily uploading and downloading.</li><li>Each value corresponds with the following key for discrete network parcellation: 1=FP1, 2=AU, 3=VS1, 4=DM1, 5=DA, 6=DM2, 7=DA2, 8=DM3, 9=VS2, 10=SM1, 11=TMP, 12=LB 13=VA1, 14=FP2, 15=SM2, 16=SM3, 17=DA3 (VS: visual; AU: auditory; SM: somatomotor; VA: ventral attention; DA: dorsal attention; FP: fronto-parietal; DM: default mode; TM: temporo-parietal; LB: limbic).</li><li>For each participant, we provide his or her subject-key in the ABCD Study. Other related information can be found at <strong>https://wiki.abcdstudy.org</strong>.</li><li>Relevant analysis scripts can be found in <strong>https://github.com/CuiLabCIBR/SingleFuncParcel_ABCD</strong>.</li></ul>
Flow estimates example for k = 50 - Information-Theoretic Sensor Placement for Large-Scale Sewer Networks
<p>This dataset is used to generate Figure 7 without running the simulations in the paper Information-Theoretic Sensor Placement for Large-Scale Sewer Networks.</p>
Data from: Large-scale network integration in the human brain tracks temporal fluctuations in memory encoding performance
Although activation/deactivation of specific brain regions have been shown to be predictive of successful memory encoding, the relationship between time-varying large-scale brain networks and fluctuations of memory encoding performance remains unclear. Here we investigated time-varying functional connectivity patterns across the human brain in periods of 30-40 s, which have recently been implicated in various cognitive functions. During functional magnetic resonance imaging, participants performed a memory encoding task, and their performance was assessed with a subsequent surprise memory test. A graph analysis of functional connectivity patterns revealed that increased integration of the subcortical, default-mode, salience, and visual subnetworks with other subnetworks is a hallmark of successful memory encoding. Moreover, multivariate analysis using the graph metrics of integration reliably classified the brain network states into the period of high (vs. low) memo ry encoding performance. Our findings suggest that a diverse set of brain systems dynamically interact to support successful memory encoding.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.