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Dataset results
207 results for “Longitudinal data”
Data from: Longitudinal evidence that older parents produce offspring with longer telomeres in a wild social bird
<p>As telomere length (TL) often predicts survival and lifespan, there is considerable interest in the origins of inter-individual variation in TL. Cross-generational effects of parental age on offspring TL are thought to be a key source of variation, but the rarity of longitudinal studies that examine the telomeres of successive offspring born throughout the lives of parents leaves such effects poorly understood. Here, we exploit TL measures of successive offspring produced throughout the long breeding tenures of parents in wild white-browed sparrow weaver (<i>Plocepasser mahali</i>) societies, to isolate the effects of within-parent changes in age on offspring TLs. Our analyses reveal the first evidence to date of a positive within-parent effect of advancing age on offspring TL: as individual parents age they produce offspring with longer telomeres (a modest effect that persists into offspring adulthood). We consider the potential for pre- and post-natal mechanisms to explain our findings. As telomere attrition predicts offspring survival to adulthood in this species, this positive parental age effect could impact parent and offspring fitness if it arose via differential telomere attrition during offspring development. Our findings support the view that cross-generational effects of parental age can be a source of inter-individual variation in TL.</p>
Data from: A longitudinal analysis of the growth rate and mass of tail feathers in a great tit population: ontogeny, genetic effects and relationship between traits
<p class="MsoNoSpacing">Feathers have a diversity of functions in birds and are costly to produce, so their growth rate and mass can be reliable indicators of nutritional condition at the time of production. Despite the potential for feather metrics to advance our understanding of foraging, they are underused in avian ecology. One reason for this is the difficulty of interpreting whether individual variation is driven by ontogenetic, genetic, or environmental effects, which is exacerbated by the fact that most analyses have been done on cross-sectional data. We addressed this deficit using a longitudinal dataset of tail feathers collected from Great tits <em>Parus major</em> to test for ontogenetic and genetic effects on growth rate, mass and length, while controlling for body/feather size differences and other confounding factors. First, we found that the type of moult episode and experimentally-induced replacement differentially affected the length, mass and growth of feathers, providing evidence of an ontogenetic effect that should be considered when comparing these feather traits across individuals as a measure of condition. Second, we detected moderate to high repeatability and heritability values from parent-offspring regression for these three feather traits, which are suggestive of an underlying genetic component of variation. Third, we used a mean centring within-individual approach to test whether feather growth rate and feather mass (length-corrected) are indeed positively correlated with each other as overlapping indicators of body condition in birds, and found that this association, although positive, is weak and only significant between individuals. This suggests that both metrics are not so intimately linked as originally thought, and probably have different sensitivities to variation in foraging performance and ecological conditions. Together with the higher plasticity of feather growth rate compared to feather mass, our results support the idea that feather growth rate is better suited for examining short-term responses to environmental variation.</p>
Data from: Incorporating single-step strategy into random regression model to enhance genomic prediction of longitudinal trait
In prediction of genomic values, single-step method has been demonstrated to outperform multi-step methods. In statistical analyses of longitudinal traits, random regression test-day model (RR-TDM) has clear advantages over other models. Our goal in this study was to evaluate the performance of the model integrating both single-step and RR-TDM prediction methods, called single-step random regression test-day model (SS RR-TDM), in comparison with the pedigree-based RR-TDM and genomic best linear unbiased prediction (GBLUP) model. We performed extensive simulations to exploit potential advantages of SS RR-TDM over the other two models under various scenarios with different level of heritability, the number of QTL as well as the selection scheme. SS RR-TDM was found to achieve the highest accuracy and unbiasedness under all scenarios, exhibiting robust prediction ability in longitudinal trait analyses. Moreover, SS RR-TDM showed better persistency of accuracy over generations than GBLUP model. In addition, we also found that the SS RR-TDM had advantages over RR-TDM and GBLUP in terms of a real dataset of human contributed by the GAW18 workshop. The findings in our study firstly proved the feasibility and advantages of the SS RR-TDM, and further enhanced strategies for the genomic prediction of longitudinal traits in the future.
Supplementary Website, Data, and Scripts for the Paper "Hierarchical and Hybrid Organizational Structures in Open-Source Software Projects: A Longitudinal Study"
<p>Supplementary website containing result plots and data, anonymized raw data, and scripts used to produce the results of the paper "Hierarchical and Hybrid Organizational Structures in Open-Source Software Projects: A Longitudinal Study".</p>
Data for Paper "Comparison of Longitudinal Wrinkle Formation During Calendering of NMC811 and LFP Cathodes"
<p>geometry data: laser and 3d scans; bending data; strain data</p>
Data for Fig 5 of PLOS Biology The Cybathlon BCI race: Successful longitudinal mutual learning with two tetraplegic users
<p>SMR feature discriminancy for pilots P1 and P2</p>
Data for Fig 4B of PLOS Biology The Cybathlon BCI race: Successful longitudinal mutual learning with two tetraplegic users
<p>The mat file consists of BCI discriminancy data for pilots P1 and P2</p>
Data for Fig 4A of PLOS Biology The Cybathlon BCI race: Successful longitudinal mutual learning with two tetraplegic users
<p>The mat file consists of BCI discriminancy data for pilots P1 and P2</p>
Data for Fig 3A of PLOS Biology The Cybathlon BCI race: Successful longitudinal mutual learning with two tetraplegic users
<p>The mat file consists of BCI command accuracy datafor pilots P1 and P2</p>
Data for Fig 2 of PLOS Biology The Cybathlon BCI race: Successful longitudinal mutual learning with two tetraplegic users
<p>The mat files consists of the data for pad crossing time throughout training for pilots P1 and P2</p>
Data for Fig 3B of PLOS Biology The Cybathlon BCI race: Successful longitudinal mutual learning with two tetraplegic users
<p>The mat file consists of BCI command accuracy data for pilots P1 and P2</p>
Data for Fig 4C of PLOS Biology The Cybathlon BCI race: Successful longitudinal mutual learning with two tetraplegic users
<p>The mat file consists of SMR feature discriminancy data for pilots P1 and P2</p>
Data for S2 Fig of PLOS Biology The Cybathlon BCI race: Successful longitudinal mutual learning with two tetraplegic users
<p>BCI SMR feature discriminancy per training modality for pilots P1 and P2</p>
Data for S1 Fig of PLOS Biology The Cybathlon BCI race: Successful longitudinal mutual learning with two tetraplegic users
<p>BCI feature discriminancy maps per training month for pilots P1 and P2 after artifact removal.</p>
Data for Fig 6D of PLOS Biology The Cybathlon BCI race: Successful longitudinal mutual learning with two tetraplegic users
<p>BCI SMR feature discriminancy for pilot P1 and different paradigms</p>
Data for Fig 6C of PLOS Biology The Cybathlon BCI race: Successful longitudinal mutual learning with two tetraplegic users
<p>Race completion time for pilot P1 with differnet paradigms</p>
Data for Fig 6B of PLOS Biology The Cybathlon BCI race: Successful longitudinal mutual learning with two tetraplegic users
<p>BCI command accuracy for pilot P1 and different control paradigms</p>
Data for Fig 6A of PLOS Biology The Cybathlon BCI race: Successful longitudinal mutual learning with two tetraplegic users
<p>Pad crossing time with different paradigms for pilot P1</p>
Data for S4 Fig of PLOS Biology The Cybathlon BCI race: Successful longitudinal mutual learning with two tetraplegic users
<p>BCI feature discriminancy maps per training month for pilots P1 and P2 without artifact removal.</p>
Data for S6A Fig of PLOS Biology The Cybathlon BCI race: Successful longitudinal mutual learning with two tetraplegic users
<p>The mat file consists of BCI discriminancy data after artifact removal for pilot P2</p>
ScienceDex guides
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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.