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Data of 14 participants in the RCT titled Acute effects of virtual reality exercise bike games on psychophysiological outcomes in college North-African adolescents with cerebral palsy: A randomized clinical trial
<p>It is an Excel file including the numerical data of the 14 participants included in the study titled: <a name="_Hlk151119211"></a><span>Acute effects of virtual reality exercise bike games on psychophysiological outcomes in college North-African adolescents with cerebral palsy: A randomized clinical trial</span></p>
Relative Random Errors in the Convective Atmospheric Boundary Layer Estimated by the Relaxed Filtering Method from Large Eddy Simulations
<p>Data supporting the paper "How representative are uncrewed aircraft system measurements of the convective boundary layer?" by Brian R. Greene, Leia M. Otterstatter, and Scott T. Salesky, submitted to Geophysical Research Letters in 2024. Data are postprocessed from large-eddy simulations of the convective atmospheric boundary layer that are used to produce the figures within the paper. Details on the production of these files are included in the supplementary informatin of this paper.</p>
AlphaFold2-Based Characterization of Apo and Holo Protein Structures and Conformational Ensembles Using Randomized Alanine Sequence Scanning Adaptation: Capturing Shared Signature Dynamics and Ligand-Induced Conformational Changes
<p>Proteins often exist in multiple conformational states, influenced by the binding of ligands or substrates. The study of these states, particularly the apo (unbound) and holo (ligand-bound) forms, is crucial for understanding protein function, dynamics, and interactions. In the current study, we use AlphaFold2 that combines<span> randomized</span> <span><span> </span>alanine<span> </span>sequence masking<span> </span>with shallow multiple sequence alignment<span> </span>subsampling to expand the conformational diversity of the predicted structural<span> </span>ensembles and<span> </span>capture conformational changes between apo and holo protein forms. Using several well-established datasets of<span> </span>structurally diverse apo-holo protein pairs, the proposed approach </span><span>enables<span> </span>robust predictions of apo and holo structures and conformational ensembles, while also displaying notably similar dynamics distributions. These observations are consistent with<span> </span>the view </span><span> </span>that the intrinsic dynamics of allosteric proteins is defined by the structural topology of the fold and favors conserved conformational motions driven by soft modes among orthologs. We also found<span> </span>a significant <span>correlation </span>between conformational flexibility and <span> </span>AlphaFold2 metric of statistical significance pLDDT for the apo-holo pairs in which ligand binding induced local moderate conformational changes. For apo-holo pairs exhibiting larger structural changes, this relationship<span> </span>becomes nonlinear, reflecting inability of AlphaFold2 confidence metrics to identify high energy functional conformations. Our findings support the notion that AlphaFold2 approaches can yield reasonable accuracy in predicting minor conformational adjustments between apo and holo states, especially for proteins with <span> </span>moderate localized changes upon ligand binding. However, for large, hinge-like domain movements, AF2 tends to predict the most stable domain orientation which is typically the apo form rather than the full range of functional conformations characteristic of the holo ensemble. These results indicate that modeling of multiple functional states of proteins may require more accurate detection of flexible region conformations and cannot solely rely on the pLDDT metric as the major determinant of the prediction accuracy in reproducing functional conformational ensembles.<span> </span></p>
Supplementary table for "Deciphering the Relationship Between Circulating Metabolites and Osteoarthritis: A Comprehensive Genetic Correlation and Mendelian Randomization Studies"
Open the record for dataset details and reuse information.
Fig. 2. Forty-one grid cells randomly set within a 10 in Factors limiting the current distribution of the introduced Java sparrow (Lonchura oryzivora) in Bangkok, Thailand
Fig. 2. Forty-one grid cells randomly set within a 10-km radius around Don Muang airport, Bangkok, Thailand, used for surveying Java sparrows. Don Muang was the site where Java sparrows were first recorded in Thailand in 1924. The study area includes three provinces; Bangkok, Pathum Thani, and Nonthaburi. The primary land use was urban, while paddyfields were mostly located on the eastern side of the study area. Different symbols (circles, squares and triangles) represent the number of occasions (out of 5 possible visits to a location) on which the sparrow was detected. Size of symbols of Java sparrow detection points was related to the number of birds detected; smallest size indicated only 1 bird was detected, medium size indicated 2–10 birds were detected, and largest size indicated a group of more than 40 birds was detected.
Text-fig. 1. Result of cumulative random counting of MN 5 localities in central Europe and the Iberian Peninsula. Ten simulations were run for each area. a. Results of the count including the average in bold, showing the clearly lower diversity in IB. b. The average lines standardized, showing similar patterns in the two areas. Note that in the simulation around thirty localities were needed to capture 80 % of the regional diversity. in Generically Speaking, A Survey On Neogene Rodent Diversity At The Genus Level In The Now Database
Text-fig. 1. Result of cumulative random counting of MN 5 localities in central Europe and the Iberian Peninsula. Ten simulations were run for each area. a. Results of the count including the average in bold, showing the clearly lower diversity in IB. b. The average lines standardized, showing similar patterns in the two areas. Note that in the simulation around thirty localities were needed to capture 80 % of the regional diversity.
Quantifying ethnic segregation in cities through random walks
<p><strong>Overview</strong></p> <p>This repository contains the coverage time distributions used to produce the figures and statistics for the paper:</p> <p>S. Sousa, V. Nicosia "Quantifying ethnic segregation in cities through random walks". arXiv: <a href="https://arxiv.org/abs/2010.10462">https://arxiv.org/abs/2010.10462</a></p> <p><strong>Data</strong></p> <p>The <strong>ccp.zip</strong> file contains two subfolders with the coverage time distributions for the US and UK systems. Each file contains a line per node of the network with the format:</p> <pre><code>"Node ID" "[list with the CCT for each fraction c]"</code></pre> <p>Note that each line will always contain 101 columns where the first column identifies the node and the remaining ones represent the average coverage time to reach a fraction c of classes.</p> <p>The <strong>dfa.zip file</strong> contains the following folders:</p> <ul> <li><strong>distances:</strong> each line corresponds to one repetition of the walk, it shows the area travelled by the walker, the length of the trajectory and perimeter.</li> <li><strong>exponents: </strong> The output file contains two columns, respectively for \epsilon and F(\epsilon).</li> <li><strong>results_ids</strong>: Time series of the visited nodes</li> </ul> <p>The <strong>synthetic.zip</strong> file contains the coverage time distributions for the experiment with different lattice sizes (scale-test) and the experiment with distinct spatial patterns for the population distribution (topology-test). The format follows the same as in ccp.zip folder.</p> <p> </p> <p><strong>Code</strong></p> <p>The reader interested in replicating the methods used to create the data can obtain the python scrips in the following repository:</p> <p><a href="https://github.com/segregation-rw/ethnic-segregation-rw">https://github.com/segregation-rw/ethnic-segregation-rw</a></p> <p>Note that the repository also includes the code to simulate the CCT random walks on the adjacency graphs so that the whole simulation can be replicated.</p>
Supplement to "Endogenous DHEAS is causally linked with lumbar spine bone mineral density and forearm fractures in women - A mendelian randomization study"
<p>Supplemental tables to "Endogenous DHEAS is causally linked with lumbar spine bone mineral density and forearm fractures in women - A mendelian randomization study" by Johan Quester, Maria Nethander, Anna Eriksson and Claes Ohlsson.</p>
A new sampling capability for uncertainty quantification in the Ice-sheet and Sea-level System Model v4.19 using Gaussian Markov random fields -- Datasets and results
<p>Data archives for test experiments (Section 3) and Pine Island Glacier application (Section 4) from the manuscript "Kevin Bulthuis and Eric Larour, A new sampling capability for uncertainty quantification in the Ice-sheet and Sea-Level System Model v4.19 using Gaussian Markov random fields"</p> <p>Source code is available at https://doi.org/10.5281/zenodo.5532775.</p>
Mobile for Mothers: a randomized quasi-controlled mobile health intervention to augment maternal health awareness and behavior of pregnant women in tribal societies.
<p>The files contain anonymized raw baseline and end-line data. Anyone using the data must cite the original studies given in the references</p>
GTEX BioBombe Results - Randomly Permuted Data
<p>BioBombe analysis applied to <strong>randomly permuted </strong>gene expression data from The Genotype-Tissue Expression (GTEx) project. Method and results described in https://github.com/greenelab/BioBombe</p>
Wikidata 3 Topical Subsets (Gene Wiki, Music, Ships) and 4 Random Subsets
<p>This dataset contains the N-Triples files of 3 Wikidata topical subsets corresponding to 3 Wikidata WikiProject: Gene Wiki, Music, and Ships along with 4 random subsets in different sizes: two of 100K items, one 500K items, and one 1M items. Subsets are extracted from the <a href="https://academictorrents.com/details/229cfeb2331ad43d4706efd435f6d78f40a3c438">3 January 2022 dump</a>. All subsets have been extracted with <a href="https://github.com/seyedahbr/wdumper">WDumper</a> using these <a href="https://github.com/seyedahbr/RQSS_Evaluation/tree/main/WDumper%20Specification%20Files">JSON specification files</a>. The files are:</p> <ul> <li>GeneWiki.zip: contains 25 `.nt.gz` RDF files each of which corresponds to one of the main Gene Wiki WikiProject classes, e.g. protein, gene, chemical compound, etc.</li> <li>music.nt.gz: the RDF file corresponding to the Music WikiProject.</li> <li>ships.nt.gz: the RDF file corresponding to the Ships WikiProject.</li> <li>Random100K_1.zip: contains 2 `nt.gz` RDF files each of which includes (about) 50,000 random Wikidata items, 100,000 items in total.</li> <li>Random100K_2.zip: contains 2 `nt.gz` RDF files each of which includes (about) 50,000 random Wikidata items, 100,000 items in total.</li> <li>Random500K.zip: contains 10 `nt.gz` RDF files each of which includes (about) 50,000 random Wikidata items, 500,000 items in total.</li> <li>Random1M.zip: contains 20 `nt.gz` RDF files each of which includes (about) 50,000 random Wikidata items, 1,000,000 items in total.</li> </ul> <p> </p>
Output files of the RQSS extractor and framework on 3 Topical (Gene Wiki, Music, Ships) subsets and 4 Random Subsets
<p>This dataset contains the `.csv` output files of the Referencing Quality Scoring System - RQSS performed on 3 topical subsets (Gene Wiki, Music, Ships) and 4 random subsets. Subset RDF files are in <a href="https://doi.org/10.5281/zenodo.7332161">this dataset</a>.</p>
Data and Code Supplement to: "Processes of change in a randomized clinical trial of Radically Open Dialectical Behavior Therapy (RO DBT) for adults with treatment refractory depression"
<p>Dataset to support secondary analyses reported in "Processes of change in a randomized clinical trial of Radically Open Dialectical Behavior Therapy (RO DBT) for adults with treatment refractory depression" in the Journal of Consulting and Clinical Psychology</p>
Data from: Predicting primate-parasite associations with exponential random graph models
<p>Ecological associations between hosts and parasites are influenced by host exposure and susceptibility to parasites, and by parasite traits, such as transmission mode. Advances in network analysis allow us to answer questions about the causes and consequences of traits in ecological networks in ways that could not be addressed in the past.</p> <p>We used a network-based framework (exponential random graph models, or ERGMs) to investigate the biogeographic, phylogenetic, and ecological characteristics of hosts and parasites characteristics that affect the probability of interactions among nonhuman primates and their parasites. Parasites included arthropods, bacteria, fungi, protozoa, viruses, and helminths.</p> <p>We investigated existing hypotheses, along with new predictors and an expanded host-parasite database that included 213 primate nodes, 763 parasite nodes, and 2,319 edges among them. Analyses also investigated phylogenetic relatedness, sampling effort, and spatial overlap among hosts.</p> <p>In addition to supporting some previous findings, our ERGM approach demonstrated that more threatened hosts had fewer parasites, and notably, that this effect was independent of threatened hosts also having a smaller geographic range. Despite having fewer parasites, threatened host species shared more parasites with other hosts, consistent with the loss of specialist parasites and threats arising from generalist parasites that can be maintained in other, non-threatened hosts. Viruses, protozoa, and helminths had broader host ranges than bacteria or fungi, and parasites that infect non-primates had a higher probability of infecting more primate species.</p> <p>The value of the ERGM approach for investigating the processes structuring host-parasite networks provided a more complete view of the biogeographic, phylogenetic, and ecological traits that influence parasite species richness and parasite sharing among hosts. The results supported some previous analyses and revealed new associations that warrant future research, thus revealing how hosts and parasites interact to form ecological networks.</p>
FIGURE 1 in RANDOM SPATIAL DISTRIBUTION OF SCHISTOSOMA MANSONI AND HOOKWORM INFECTIONS AMONG SCHOOL CHILDREN WITHIN A SINGLE VILLAGE
FIGURE 1. Spatial distribution of different infection intensity levels of Schistosoma mansoni among school children living in the village of Fagnampleu, western Côte d'Ivoire.
FIGURE 2 in RANDOM SPATIAL DISTRIBUTION OF SCHISTOSOMA MANSONI AND HOOKWORM INFECTIONS AMONG SCHOOL CHILDREN WITHIN A SINGLE VILLAGE
FIGURE 2. Spatial distribution of different infection intensity levels of hookworm among school children living in the village of Fagnampleu, western Côte d'Ivoire.
Dataset related to article "Harmonization of sensorimotor deficit assessment in a registered multicentre pre-clinical randomized controlled trial using two models of ischemic stroke"
<p>https://figshare.com/search?q=10.6084%2Fm9.figshare.21346731</p>
Identification of high-wind features within extratropical cyclones using a probabilistic random forest - Part 2: Climatology - Video Supplement
<p>These videos provide examples of application of RAMEFI (RAndom-forest based MEsoscale wind Feature Identification) for winter storm cases between 2000 and 2019 and an animation of cyclone-relative occurrence (cf. Fig. 7 of 10.5194/wcd-2023-10).</p>
Non-random mating within an island rookery of Hawaiian hawksbill turtles: demographic discontinuity at a small coastline scale
<p>Hawksbill sea turtles (<em>Eretmochelys</em> <em>imbricata</em>) from the Hawaiian archipelago form a small and genetically isolated population, consisting of only a few tens of individuals breeding annually. Most females nest on the island of Hawai'i, but little is known about the demographics of this rookery. This study used genetic relatedness, inferred from 135 microhaplotype markers, to determine breeding sex-ratios, estimate female nesting frequency, and assess relationships between individuals nesting on different beaches. Samples were collected during the 2017 nesting season and final data included 13 nesting females and 1,002 unhatched embryos, salvaged from 41 nests, of which 13 had no observed mother. Results show that most females used a single nesting beach laying 1–5 nests each. From female and offspring alleles the paternal genotypes of 12 breeding males were reconstructed and many showed high relatedness to their mates. Pairwise relatedness of offspring revealed one instance of polygyny but otherwise suggest a 1:1 breeding-sex ratio. Relatedness analysis and spatial-autocorrelation of genotypes indicate non-random mating among complexes of nesting beaches, for both sexes, suggesting strong natal philopatry. Nesting complexes also showed unique patterns of inbreeding across loci, further indicating that Hawaiian hawksbill turtles have demographically discontinuous nesting populations on a fine spatial scale.</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.