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139
datasets available to search
ShareScore release 0.9.0
Dataset results
139 results for “dynamic signals”
Data from: Trpc2 Pseudogenization dynamics in bats reveal ancestral vomeronasal signaling, then pervasive loss
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Data from: A RhoG-mediated signaling pathway that modulates invadopodia dynamics in breast cancer cells
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Data from: Control of signaling alignment during the dynamic courtship display of a jumping spider
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Analysis of localized cAMP perturbations within a tissue reveal the effects of a local, dynamic gap junction state on ERK signaling
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Data from: Linking dynamical complexities from activation signals to transcription responses
The transcription of inducible genes involves signaling pathways that induce DNA binding of the downstream transcription factors to form functional promoter states. How the transcription dynamics is linked to the temporal variations of activation signals is far to be fully understood. In this work, we develop a mathematical model with multiple promoter states to address this question. Each promoter state has its own activation and inactivation rates, and is selected randomly with a probability that may change in time. Under the activation of constant signals, our analysis shows that if only the activation rates differ among the promoter states, then the mean transcription level $m(t)$ displays only a monotone or monophasic growth pattern. In a sharp contrast, if the inactivation rates change with the promoter states, then $m(t)$ may display multiphasic growth patterns. Upon the activation of signals that oscillate periodically, $m(t)$ also oscillates later, almost periodically in the same frequency, but the magnitude decreases in the frequency and is almost completely attenuated at large frequencies. This gives a surprising indication that multiple promoter states could filter out the signal oscillation and the noise in the random promoter state selection, as observed in the transcription of a gene activated by p53 in breast carcinoma cells. Our approach may help develop a theoretical framework to integrate coherently the genetic circuit with the promoter states to elucidate the linkage from the activation signal to the temporal profile of transcription outputs.
Data from: Dynamical state transitions into addictive behaviour and their early-warning signals
The theory of critical transitions in complex systems (ecosystems, climate, etc.), and especially its ability to predict abrupt changes by early-warning signals based on analysis of fluctuations close to tipping points, is seen as a promising avenue to study disease dynamics. However, the biomedical field still lacks a clear demonstration of this concept. Here, we used a well-established animal model in which initial alcohol exposure followed by deprivation and subsequent reintroduction of alcohol induces excessive alcohol drinking as an example of disease onset. Intensive longitudinal data (ILD) of rat drinking behaviour and locomotor activity were acquired by a fully automated drinkometer device over 14 weeks. Dynamical characteristics of ILD were extracted using a multi-scale computational approach. Our analysis shows a transition into addictive behaviour preceded by early-warning signals such as instability of drinking patterns and locomotor circadian rhythms, and a resultant increase in low frequency, ultradian rhythms during the first week of deprivation. We find evidence that during prolonged deprivation, a critical transition takes place pushing the system to excessive alcohol consumption. This study provides an adaptable framework for processing ILD from clinical studies and for examining disease dynamics and early-warning signals in the biomedical field.
data for "An unbound proline-rich signaling peptide frequently samples cis conformations in Gaussian accelerated molecular dynamics simulations"
<p>Disordered proline-rich motifs are common across the proteomes of many species and are often involved in protein-protein interactions. Proline is a unique amino acid due to the covalent bond between the backbone nitrogen and the proline side chain. The resulting five-membered ring allows proline to sample the <em>cis</em> state about its peptide bond, which other residues cannot do as readily. Because proline-rich disordered sequences exist as ensembles that likely include structures with the proline peptide bond in <em>cis</em>, a robust methodology to accurately account for these conformations in the overall ensemble is crucial. Observing the <em>cis </em>conformations of proline in a disordered sequence is challenging both experimentally and computationally. Nitrogen-hydrogen NMR spectroscopy cannot directly observe proline residues, which lack an amide bond, and computational methods struggle to overcome the large kinetic barrier between the <em>cis </em>and <em>trans </em>states, since isomerization usually occurs on the order of seconds. In the current work, Gaussian accelerated molecular dynamics was used to overcome this free energy barrier and simulate proline isomerization in a tetrapeptide (KPTP) and in the 12-residue proline-rich SH3 binding peptide, ArkA. We found that Gaussian accelerated molecular dynamics, when combined with a lowered peptide bond dihedral angle potential energy barrier (15 kcal/mol), allowed sufficient sampling of the proline <em>cis </em>and <em>trans </em>states on a microsecond timescale. All ArkA prolines spend a significant fraction of time in <em>cis</em>, leading to a more compact ensemble with less polyproline II helix structure than an ArkA ensemble with all peptide bonds in <em>trans</em>. The ensemble containing <em>cis</em> prolines also matches more closely to <em>in vitro</em> circular dichroism data than the all-<em>trans</em> ensemble. The ability of the ArkA prolines to isomerize likely affects the peptide’s ability to bind its partner SH3 domain, and should be studied further. This is the first molecular dynamics simulation study of proline isomerization in a biologically relevant proline-rich sequence that we know of, and a similar protocol could be applied to study multi-proline isomerization in other proline-containing proteins to improve conformational diversity and agreement with <em>in vitro</em> data.</p>
Data from: Social costs enforce honesty of a dynamic signal of motivation
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Data from: Real-time social selection maintains honesty of a dynamic visual signal in cooperative fish
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Data from: Dynamical state transitions into addictive behaviour and their early-warning signals
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Data from: Linking dynamical complexities from activation signals to transcription responses
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Dynamics of m6A RNA methylome during leukemogenesis reveals a role of PRMT6-MFSD2A signaling axis in maintaining AML stem cells.[RIP-seq]
GEO Series GSE218610. Mus musculus. 4 samples. Type: Expression profiling by high throughput sequencing.
State- and stimulus-specific dynamics of SMAD signaling determine fate decisions in individual cells
GEO Series GSE223670. Homo sapiens. 31 samples. Type: Expression profiling by high throughput sequencing.
Single cell RNA-Seq reveals Fgf signaling dynamics during sensory hair cell regeneration
GEO Series GSE123241. Danio rerio. 3 samples. Type: Expression profiling by high throughput sequencing.
Unveiling the Temporal Dynamics of Mesenchymal Condensations in Tracheal Development through Non-Canonical Wnt Signaling and Notum
GEO Series GSE260707. Mus musculus. 22 samples. Type: Expression profiling by high throughput sequencing.
A Probabilistic Model of Transcription Dynamics applied to Estrogen Signalling in Breast Cancer Cells
GEO Series GSE44800. Homo sapiens. 8 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Zeb1 regulates mammary basal epithelial fate and proliferation dynamics through modulating EMT gene expression and Wnt signaling
GEO Series GSE155636. Mus musculus. 107 samples. Type: Expression profiling by high throughput sequencing.
GR and Klf15 regulate gene expression dynamics and integrate signals through feed forward circuitry
GEO Series GSE44695. Mus musculus. 29 samples. Type: Expression profiling by array.
Dynamic binding of RBPJ is determined by Notch signalling status
GEO Series GSE37184. Mus musculus. 33 samples. Type: Genome binding/occupancy profiling by high throughput sequencing; Expression profiling by high throughput sequencing.
Dynamic developmental signaling logic underlying lineage bifurcations during human endoderm induction and patterning from pluripotent stem cells [Endoderm RNA-seq and ChIP-seq data sets]
GEO Series GSE52657. Homo sapiens. 36 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing.
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.