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231
datasets available to search
ShareScore release 0.9.0
Dataset results
231 results for “functional connections”
Data from: Cognitive correlates of cerebellar resting-state functional connectivity in Parkinson disease.
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Data from: Selective modulation of interhemispheric functional connectivity by HD-tACS shapes perception
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Data from: Contributions of local speech encoding and functional connectivity to audio-visual speech perception
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Data from: Maximizing negative correlations in resting-state functional connectivity MRI by time-lag
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Data from: Habitat connectivity and local conditions shape taxonomic and functional diversity of arthropods on green roofs
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The influence of dopamine on cognitive flexibility is mediated by functional connectivity in young but not older adults
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Sox2 is required for functional chromatin connectivity in brain-derived neural stem cells.
GEO Series GSE90561. Mus musculus. 65 samples. Type: Other; Genome binding/occupancy profiling by high throughput sequencing; Expression profiling by high throughput sequencing.
Dysfunctions in nonsense-mediated decay, protein homeostasis, OXPHOS function, and brain connectivity in ALS-FUS mice with cognitive deficits
GEO Series GSE157713. Mus musculus. 6 samples. Type: Expression profiling by high throughput sequencing.
A functional 3D full-thickness model for comprehending the interaction between airway epithelium and connective tissue in cystic fibrosis.
GEO Series GSE245059. Homo sapiens. 19 samples. Type: Expression profiling by high throughput sequencing.
Altered Neocortical Gene Expression, Brain Overgrowth and Functional Over-Connectivity in Chd8 Haploinsufficient Mice
GEO Series GSE81103. Mus musculus. 12 samples. Type: Expression profiling by high throughput sequencing.
Identification and functional prediction of long noncoding RNA and mRNA related to connective tissue disease-associated interstitial lung diseases
GEO Series GSE192985. Homo sapiens. 7 samples. Type: Expression profiling by array; Non-coding RNA profiling by array.
Systematic mapping of functional enhancer-promoter connections with CRISPR interference
GEO Series GSE87257. Homo sapiens. 24 samples. Type: Expression profiling by high throughput sequencing.
Bulk RNA sequencing of high- and low-functional connectivity glioblastomas
GEO Series GSE223064. Homo sapiens. 7 samples. Type: Expression profiling by high throughput sequencing.
The human cap-binding complex is functionally connected to the nuclear RNA exosome
GEO Series GSE52132. Homo sapiens. 10 samples. Type: Expression profiling by genome tiling array.
Embryonic exposure to an aqueous coal dust extract results in gene expression alterations associated with development and function of connective tissue and the hematological system in zebrafish
GEO Series GSE94997. Danio rerio. 12 samples. Type: Expression profiling by array.
Single-cell RNA sequencing of high- and low-functional connectivity glioblastomas
GEO Series GSE223063. Homo sapiens. 6 samples. Type: Expression profiling by high throughput sequencing.
Data from: Integrated analysis and visualization of group differences in structural and functional brain connectivity: applications in typical ageing and schizophrenia
Structural and functional brain connectivity are increasingly used to identify and analyze group differences in studies of brain disease. This study presents methods to analyze uni- and bi-modal brain connectivity and evaluate their ability to identify differences. Novel visualizations of significantly different connections comparing multiple metrics are presented. On the global level, "bi-modal comparison plots" show the distribution of uni- and bi-modal group differences and the relationship between structure and function. Differences between brain lobes are visualized using "worm plots". Group differences in connections are examined with an existing visualization, the "connectogram". These visualizations were evaluated in two proof-of-concept studies: (1) middle-aged versus elderly subjects; and (2) patients with schizophrenia versus controls. Each included two measures derived from diffusion weighted images and two from functional magnetic resonance images. The structural measures were minimum cost path between two anatomical regions according to the "Statistical Analysis of Minimum cost path based Structural Connectivity" method and the average fractional anisotropy along the fiber. The functional measures were Pearson's correlation and partial correlation of mean regional time series. The relationship between structure and function was similar in both studies. Uni-modal group differences varied greatly between connectivity types. Group differences were identified in both studies globally, within brain lobes and between regions. In the aging study, minimum cost path was highly effective in identifying group differences on all levels; fractional anisotropy and mean correlation showed smaller differences on the brain lobe and regional levels. In the schizophrenia study, minimum cost path and fractional anisotropy showed differences on the global level and within brain lobes; mean correlation showed small differences on the lobe level. Only fractional anisotropy and mean correlation showed regional differences. The presented visualizations were helpful in comparing and evaluating connectivity measures on multiple levels in both studies.
Multi-Omic Integration by Machine Learning (MIMaL) Reveals Protein-Metabolite Connections and New Gene Functions
<p>Metabolomics and proteomics generate large, complex datasets that reflect the state of a biological system. Multi-omics is the integration of these disparate methods and data to gain a clearer picture of the biological state. Multi-omic studies of the proteome and metabolome are becoming more common as mass spectrometry technology continues to be democratized. However, knowledge extraction through integration of these data remains challenging. Here we show that connections between these omic layers can be discovered through a combination of machine learning and model interpretation. We find that SHAP values connecting proteins to metabolites are valid experimentally, and reveal also largely new connections. Further, clustering the magnitudes of protein control over all metabolites enabled prediction of gene five gene functions, each of which was validated experimentally. We accurately predicted that two uncharacterized genes in yeast modulate mitochondrial translation, <em>YJR120W</em> and <em>YLD157C</em>.We also predict and validate functions for several incompletely characterized genes, including <em>SDH9</em>, <em>ISC1</em>, and <em>FMP52</em>. Our work demonstrates that multi-omic analysis with machine learning (MIMaL) is a new lens that reveals new insight from multi-omic data that would not be possible using any omic layer alone.</p>
Effects of a GLP-1 Receptor Agonist on Functional Activation and Connectivity of the Brain
ClinicalTrials.gov study NCT02745470. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Functional Connectivity of the Interoceptive Network in RLS
ClinicalTrials.gov study NCT07001891. IPD Sharing: NO. Countries: 1. Publications: 0.
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.