Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
37
datasets available to search
ShareScore release 0.9.0
Dataset results
37 results for “Individual signatures”
Dataset: Sex differences in the impact of social relationships on individual vocal signatures in grey mouse lemurs
<p>Dataset used in the statistical analysis of the publication "Sex differences in the impact of social relationships on individual vocal signatures in grey mouse lemurs (<em>Microcebus murinus</em>)"</p> <p><strong>Abstract</strong></p> <p>Vocali<span>z</span>ations coordinate social interactions between conspecifics by conveying information concerning the individual or group identity of the sender. Social accommodation is a form of vocal learning where social affinity is signalled by converging or diverging vocali<span>z</span>ations to those of conspecifics. To investigate whether social accommodation is linked to the social lifestyle of the sender, we investigated sex-specific differences in social accommodation in a dispersed living primate, the grey mouse lemur, where females form stable sleeping groups whereas males live solitarily. We used 482 trill calls of 36 individuals from our captive breeding colony to compare acoustic dissimilarity between individuals with genetic relatedness, social contact time and body weight. Our results showed that female trills become more similar the more time females spen<span>d</span> with each other independent of genetic relationship, suggesting vocal convergence. In contrast, male trills were affected more by genetic than social factors. However, focus<span>s</span>ing only on sociali<span>z</span>ed males, male trills diverged from each other the more time males were cage partners. Thus, grey mouse lemurs show the capacity for social accommodation, with females converging their trills to signal social closeness to sleeping group partners, whereas males do not adapt or diverge their trills to signal individual distinctiveness. </p> <p> </p> <p>For details concerning the recording of the trills confer to the publication at doi: 10.1098/rstb.2023.0193</p>
Individual high-quality reads (dd-RADsequencing) from: Genomic signatures of clonality in the deep water kelp Laminaria rodriguezii
Open the record for dataset details and reuse information.
Dataset associated with "Thermoelectric signature of individual skyrmions"
<p>Dataset for the article: A. Fernández Scarioni, C. Barton, H. Corte-León, S. Sievers, X. Hu, F. Ajejas, W. Legrand, N. Reyren, V. Cros, O. Kazakova, H. W. Schumacher, “Thermoelectric signature of individual skyrmions,” Phys. Rev. Lett.</p> <p>The data is divided in figures and for each figure we report the raw data.</p> <p>For more information follow the Readme.txt file</p> <p>.</p>
Individual or group signatures in spotted hyena whoops
<p>In animal societies, identity signals mediate interactions within groups, and allow individuals to discriminate group-mates from out-group competitors. However, individual recognition becomes increasingly challenging as group size increases and as signals must be transmitted over greater distances. Group vocal signatures appear to evolve when successful in-group/out-group distinctions are at the crux of fitness-relevant decisions, but individual-based recognition systems may be favored when differentiated within-group relationships are important for decision-making. Spotted hyenas are social carnivores that live in stable clans of <125 individuals composed of multiple unrelated matrilines. Clan members cooperate to defend resources and communal territories from neighboring clans and other mega carnivores; this collective defense is mediated by long-range (up to 5 km range) recruitment vocalizations, called whoops. Here, we use machine learning to determine that spotted hyena whoops contain individual but not group signatures, and that fundamental frequency features that propagate well are critical for individual discrimination. For effective clan-level cooperation, hyenas face the cognitive challenge of remembering and recognizing individual voices at long range. We show that serial redundancy in whoop bouts increases individual classification accuracy and thus extended call bouts used by hyenas likely evolved to overcome the challenges of communicating individual identity at long distance.</p>
A small vocal repertoire during the breeding season expresses complex behavioral motivations and individual signature in the Common Coot
<p><b>Backgroun</b><b>d:</b> Although acoustic communication plays an essential role in the social interactions of Rallidae, our knowledge of how Rallidae encode diverse types of information using simple vocalizations is limited. We recorded and examined the vocalizations of a Common Coot (<i>Fulica atra</i>) population during the breeding season to test the hypotheses that 1) different call types can be emitted under different behavioral contexts, and 2) variation in the vocal structure of a single call type may be influenced both by behavioral motivations and individual signature. We measured a total of 61 recordings of 30 adults while noting the behavioral activities in which individuals were engaged. We compared several acoustic parameters of the same call type emitted under different behavioral activities to determine how frequency and temporal parameters changed depending on behavioral motivations and individual differences.</p> <p><b>Results: </b>We found that adult Common Coots had a small vocal repertoire, including 4 types of call, composed of a single syllable that was used during 9 types of behaviors. The 4 calls significantly differed in both frequency and temporal parameters and can be clearly distinguished by discriminant function analysis. Minimum frequency of fundamental frequency (F<sub>0min</sub>) and duration of syllable (T) contributed the most to acoustic divergence between calls. Call <i>a</i> was the most commonly used (in 8 of the 9 behaviors detected), and maximum frequency of fundamental frequency (F<sub>0max</sub>) and interval of syllables (TI) contributed the most to variation in call <i>a</i>. Duration of syllable (T) in a single call <i>a</i> can vary with different behavioral motivations after individual vocal signature being controlled.</p> <p><b>Conclusions:</b> These results demonstrate that several call types of a small repertoire, and a single call with function-related changes in the temporal parameter in Common Coots could potentially indicate various behavioral motivations and individual signature. This study advances our knowledge of how Rallidae use "simple" vocal systems to express diverse motivations and provides new models for future studies on the role of vocalization in avian communication and behavior.</p>
A small vocal repertoire during the breeding season expresses complex behavioral motivations and individual signature in the Common Coot
Open the record for dataset details and reuse information.
Individual or group signatures in spotted hyena whoops
Open the record for dataset details and reuse information.
Data from: Gut microbiota signatures predict host and microbiota responses to dietary interventions in obese individuals
Background: Interactions between the diet and intestinal microbiota play a role in health and disease, including obesity and related metabolic complications. There is great interest to use dietary means to manipulate the microbiota to promote health. Currently, the impact of dietary change on the microbiota and the host metabolism is poorly predictable and highly individual. We propose that the responsiveness of the gut microbiota may depend on its composition, and associate with metabolic changes in the host. Methodology: Our study involved three independent cohorts of obese adults (n = 78) from Belgium, Finland, and Britain, participating in different dietary interventions aiming to improve metabolic health. We used a phylogenetic microarray for comprehensive fecal microbiota analysis at baseline and after the intervention. Blood cholesterol, insulin and inflammation markers were analyzed as indicators of host response. The data were divided into four training set – test set pairs; each intervention acted both as a part of a training set and as an independent test set. We used linear models to predict the responsiveness of the microbiota and the host, and logistic regression to predict responder vs. non-responder status, or increase vs. decrease of the health parameters. Principal Findings: Our models, based on the abundance of several, mainly Firmicute species at baseline, predicted the responsiveness of the microbiota (AUC = 0.77–1; predicted vs. observed correlation = 0.67–0.88). Many of the predictive taxa showed a non-linear relationship with the responsiveness. The microbiota response associated with the change in serum cholesterol levels with an AUC of 0.96, highlighting the involvement of the intestinal microbiota in metabolic health. Conclusion: This proof-of-principle study introduces the first potential microbial biomarkers for dietary responsiveness in obese individuals with impaired metabolic health, and reveals the potential of microbiota signatures for personalized nutrition.
Individual signatures outweigh social group identity in contact calls of a communally nesting parrot
Despite longstanding interest in the evolutionary origins and maintenance of vocal learning, we know relatively little about how social dynamics influence vocal learning processes in natural populations. The "social group membership" hypothesis proposes that socially learned calls evolved and are maintained as signals of group membership. However, in fission-fusion societies, individuals can interact in social groups across various social scales. For learned calls to signal group membership over multiple social scales, they must contain information about group membership over each of these scales, a concept termed "hierarchical mapping". Monk parakeets (Myiopsitta monachus), small parrots native to South America, exhibit vocal mimicry in captivity and fission-fusion social dynamics in the wild. We examined patterns of contact call acoustic similarity in Uruguay to test the hierarchical mapping assumption of the signaling group membership hypothesis. We also asked whether geographic variation patterns matched regional dialects or geographic clines that have been documented in other vocal learning species. We used visual inspection, spectrographic cross-correlation and random forests, a machine learning approach, to evaluate contact call similarity. We compared acoustic similarity across social scales and geographic distance using Mantel tests and spatial autocorrelation. We found high similarity within individuals, and low, albeit significant, similarity within groups at the pair, flock and site social scales. Patterns of acoustic similarity over geographic distance did not match mosaic or graded patterns expected in dialectal or clinal variation. Our findings suggest that monk parakeet social interactions rely more heavily upon individual recognition than group membership at higher social scales.
An Individual-specific Synchrony Signature
ClinicalTrials.gov study NCT06749392. IPD Sharing: NO. Countries: 1. Publications: 1.
PredictEndTB Signature for Individualizing Treatment in Multidrug-Resistant Tuberculosis
ClinicalTrials.gov study NCT04783727. IPD Sharing: NO. Countries: 4. Publications: 2.
Individual Metabolism and Physiology Signature Study
ClinicalTrials.gov study NCT02298725. IPD Sharing: NO. Countries: 1. Publications: 9.
Data from: Gut microbiota signatures predict host and microbiota responses to dietary interventions in obese individuals
Open the record for dataset details and reuse information.
Individual signatures outweigh social group identity in contact calls of a communally nesting parrot
Open the record for dataset details and reuse information.
Data from: An eighteen serum cytokine signature for discriminating glioma from normal healthy individuals
Open the record for dataset details and reuse information.
Transcriptional Signature Associated with Early Rheumatoid Arthritis and Healthy Individuals at high risk to develop the disease.
GEO Series GSE100191. Homo sapiens. 19 samples. Type: Expression profiling by array.
Individual-specific and allele-specific chromatin signatures in diverse human populations
GEO Series GSE19622. Homo sapiens. 26 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Gene expression signatures but not cell cycle checkpoint functions distinguish AT carriers from normal individuals and AT patients
GEO Series GSE45850. Homo sapiens. 88 samples. Type: Expression profiling by array.
Induced Mesenchymal stromal cells derived from iPS cells from aged individuals acquire a rejuvenation signature and a MSC-specific secretome
GEO Series GSE97311. Homo sapiens. 18 samples. Type: Expression profiling by array.
Molecular signatures of aging and flu vaccine response in Healthy and HIV infected individuals
GEO Series GSE178670. Homo sapiens. 95 samples. Type: Expression 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.