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.
13,064
datasets available to search
ShareScore release 0.9.0
Dataset results
13,064 results for “predictions”
Predicting the physiological effects of multiple drugs using electronic health record
<p><span>Supplementary Data 1. Optimized hyperparameters of the XGBoost classifiers for the 20 selected measurement items.</span></p> <p><span>Supplementary Data 2. Information on 416 active pharmaceutical ingredients (APIs) used to develop the machine learning models for the 20 selected measurement items.</span></p> <p><span>Supplementary Data 3. List of top 20 features with the highest feature importance for each XGBoost classifier according to the SHAP analysis (Fig. 4).</span></p> <p><span>Supplementary Data 4. AUROC of the XGBoost classifiers for the 20 measurement items by using pairwise combinations of feature types as input, and using race-specific and sex-specific MIMIC-IV datasets.</span></p>
Data from: Predicting the spatio-temporal dynamics of biological invasions: Have rapid responses in Europe limited the spread of the Asian yellow-legged hornet (Vespa velutina nigrithorax)?
<p>This data was collated from multiple sources including aktion-wespenschutz.de (Germany), The Biological Records Centre, UKCEH (UK), GBIF, L'Inventaire national du patrimoine naturel (France), iNaturalist (Belgium), StopVelutina (Italy), Waarneming.nl (Netherlands), MAGRAMA. Inventario Español del Patrimonio Natural y la Biodiversidad (Spain). </p> <p>Coordinates of occurence records were obatained from the sources above. These records were used in ecological niche models and mechanistic models to simulate the spread of <em>Vespa velutina nigrithorax</em> in Belgium, Germany, The Netherlands and the United Kingdom. </p> <p>Please be sure to cite and credit the orginal data providers if you intend to use this data. </p>
Using Machine Learning With Supplementary NC Code To Predict Machining Energy - Excel Documents
<p>The Excel Files Housed within this DOI represent the raw data collected during machining each of the test parts, and the excel documents made which prevent model summaries for each model created., during the execution of the, "Using Machine Learning With Supplementary NC Code to Predict Machining Energy. These files were created by Samuel D. Stencel, a Graduate Research Assistant and Purdue University.</p>
Predicting the solubility of amino acids and peptides with the SAFT-γ Mie approach: Neutral and charged models
<p>Calculated data accompanying the IECR 2024 publication "Predicting the Solubility of Amino Acids and Peptides with the SAFT‑γ Mie Approach: Neutral and Charged Models", by Ahmed Alyazidi, Shubhani Paliwal, Felipe A. Perdomo, Amy Mead, Mingxia Guo, Jerry Y. Y. Heng, Thomas Bernet, Andrew Haslam, Claire S. Adjiman, George Jackson, and Amparo Galindo. </p>
AF3 predictions for Taq Ligase and Human DNA Ligase I and III
Open the record for dataset details and reuse information.
Supplementary Data for "Exploring structure-function relationships in engineered receptor performance using computational structure prediction"
<p>These data are supplementary data for the manuscript "<strong>Exploring structure-function relationships in engineered receptor performance using computational structure prediction</strong>", which has been submitted for consideration for publication. These data include protein structure predictions used in this study.</p>
Data for "Supervised machine learning methods for crystal structure prediction of the binary Cs-Te system"
<p>Crystal structures, high-throughput calculations and trained machine learning models presented in the paper "Supervised machine learning methods for crystal structure prediction of the binary Cs-Te system".</p> <ul> <li><em>crystal_datasets </em>contains the input/output data sets of crystal structures for high-throughput calculations and ML models.</li> <li><em>aiida_ht_calculations </em>contains the data regarding the high-throughput DFT calculations.</li> <li><em>ml_models</em> contains the trained ML models.</li> </ul> <p>Eeach zip-archive contains a jupyter-notebook examplifying how the data can be accessed and reused.</p>
Disorder predictions for all reviewed UniProt proteins with "membrane" subcellular localization
<h1>IDRs in membrane proteins</h1> <h3>About</h3> <p>The writeup below walks through how to answer the question "what fraction of membrane proteins have IDRs".</p> <p>The tl/dr: on average <strong>55% of membrane proteins [as defined here] have IDRs</strong>.</p> <h3>Data</h3> <p>This directory (WITH the associated sequences), which are not included on GitHub, are deposited on Zenodo.</p> <h2>Steps</h2> <h4>Install software</h4> <p>Install metapredict</p> <div> <pre><code>pip install metapredict</code></pre> </div> <p>Done.</p> <h4>Find the data</h4> <p>Using the "Advanced Search", I downloaded all reviewed proteins on <a href="https://uniprot.org/">UniProt</a> tagged as having a "membrane" subcellular localization.</p> <p>There are, of course, much more detailed ways one could get these data (e.g., requiring transmembrane helices, integral membrane protein filtering etc, etc), but I figured for purposes here, I'd just do this...</p> <h4>Download the data</h4> <p>From this, I downloaded all the FASTA sequences. This triggers the following file to be downloaded:</p> <div> <pre><code>uniprotkb_cc_scl_term_SL_0162_AND_revie_2024_11_09.fasta</code></pre> </div> <h4>Preprocessing the data</h4> <p>Next I wanted to fix any sequences with non-standard amino acids by converting those residues to "standard" amino acids. I did this using <code>pfasta</code>, a commandline tool that's part of <a href="https://protfasta.readthedocs.io/en/latest/">protfasta</a> which comes with metapredict.</p> <p>Did this simply with</p> <div> <pre><code>pfasta --invalid-sequence convert-all -o membrane_proteins.fasta uniprotkb_cc_scl_term_SL_0162_AND_revie_2024_11_08.fasta</code></pre> </div> <ul> <li>The <code>--invalid-sequence</code> flag tells pfasta what to with an invalid sequence, and <code>-o</code> tells it what the ouput file should be called.</li> </ul> <p>Running this (~5 seconds) generates the following output:</p> <div> <pre><code>........................ pfasta version 0.1.13+0.gc1786bd.dirty Please report bugs to: https://github.com/holehouse-lab/protfasta ........................ [INFO]: Reading in the file uniprotkb_cc_scl_term_SL_0162_AND_revie_2024_11_08.fasta [INFO]: Read in file with 1004330 lines [INFO]: Parsed file to recover 117691 sequences [INFO]: Converted 697 sequences to valid sequences [INFO]: Writing new sequence file [membrane_proteins.fasta]...</code></pre> </div> <h4>Predicting all IDRs</h4> <p>Run one of metapredict's command-line utilities to predict all IDRs in these proteins.</p> <div> <pre><code>metapredict-predict-idrs membrane_proteins.fasta -o membrane_protein_idrs.fasta</code></pre> </div> <p>This takes ~20 seconds on my desktop with an A4500 GPU or ~5 min with my Macbook Pro. We're then left with a file called <code>membrane_protein_idrs.fasta</code>. This is a FASTA file that the header format:</p> <div> <pre><code>><HEADER FOR ORIGINAL PROTEIN> IDR_START=<start position> IDR_END=<end_position></code></pre> </div> <p>e.g.</p> <div> <pre><code>>sp|B4R1D8|HH_DROSI Protein hedgehog OS=Drosophila simulans OX=7240 GN=hh PE=3 SV=1 IDR_START=0 IDR_END=94 MDNHSSVPWASAASVTCLSLDAKCHSSSSSCSSKSTASSISASPETQTMRHIAHTQRCLS RLTSLVALLLIVLPMMFSPAHSCGPGRGLGRHRA</code></pre> </div> <h3>Hacky way to get number of proteins with IDRs</h3> <p>Get the number of unique proteins in the main file:</p> <div> <pre><code>cat membrane_proteins.fasta | grep ">" | awk -F "|" {' print $2 '} | sort | uniq |wc</code></pre> </div> <p>Which returns</p> <div> <pre><code>117691 117691 829609</code></pre> </div> <p>So we have 117,691 unique proteins (NB: we could also just have gotten this without the <code>awk -F "|" {' print $2 '} | sort | uniq</code> part BUT we do need that for the number of unique proteins with IDRs so good to be consistent.</p> <div> <pre><code>cat membrane_protein_idrs.fasta | grep ">" | awk -F "|" {' print $2 '} | sort | uniq |wc</code></pre> </div> <p>Which returns</p> <div> <pre><code>64971 64971 458829 </code></pre> </div> <p>So on average <strong>55% of membrane proteins [as defined here] have IDRs</strong>.</p> <h3>Bonus!</h3> <p>In addition we can predict all disorder scores rather than discrete IDRs using</p> <div> <pre><code>metapredict-predict-disorder membrane_proteins.fasta -o membrane_protein_disorder_scores.csv</code></pre> </div> <p>This takes ~5 min on my Macbook Pro. The data for these are included here for completeness/convenience.</p>
Data from: Predicting the spread of all invasive forest pests in the United States
We tested whether a general spread model could capture macroecological patterns across all damaging invasive forest pests in the United States. We showed that a common constant dispersal kernel model, simulated from the discovery date, explained 67.94% of the variation in range size across all pests, and had 68.00% locational accuracy between predicted and observed locational distributions. Further, by making dispersal a function of forest area and human population density, variation explained increased to 75.60%, with 74.30% accuracy. These results indicated that a single general dispersal kernel model was sufficient to predict the majority of variation in extent and locational distribution across pest species and that proxies of propagule pressure and habitat invasibility – well-studied predictors of establishment – should also be applied to the dispersal stage. This model provides a key element to forecast novel invaders and to extend pathway-level risk analyses to include spread.
Data from: Functional traits and environmental conditions predict community isotopic niches and energy pathways across spatial scales
1. Despite ongoing research in food web ecology and functional biogeography, the links between food-web structure, functional traits and environmental conditions across spatial scales remain poorly understood. Trophic niches, defined as the amount of energy and elemental space occupied by species and food webs, may help bridge this divide. 2. Here, we ask how the functional traits of species, the environmental conditions of habitats and the spatial scale of analysis jointly determine the characteristics of trophic niches. We used isotopic niches as a proxy of trophic niches, and conducted analyses at spatial scales ranging from local food webs and metacommunities to geographically distant sites. 3. We sampled aquatic macroinvertebrates from 104 tank bromeliads distributed across five sites from Central to South America, and compiled the macroinvertebrates' functional traits and stable isotope values (δ15N and δ13C). We assessed how isotopic niches within each bromeliad were influenced by the functional trait composition of their associated invertebrates and environmental conditions (i.e., habitat size, canopy cover, and detrital concentration). We then evaluated whether the diet of dominant predators and, consequently, energy pathways within food webs, reflected functional and environmental changes among bromeliads across sites. Finally, we determined the extent to which the isotopic niches of macroinvertebrates within each bromeliad contributed to the metacommunity isotopic niches within each site, and compared these metacommunity-level niches over biogeographic scales. 4. At the bromeliad level, isotopic niches increased with the functional richness of species in the food web and the detrital concentration in the bromeliad. The diet of top predators tracked shifts in prey biomass along gradients of canopy cover and detrital concentration. Bromeliads that grew under heterogeneous canopy cover displayed less trophic redundancy and therefore combined to form larger metacommunity isotopic niches. Finally, the size of metacommunity niches depended on within-site heterogeneity in canopy cover. 5. Our results suggest that the trophic niches occupied by food webs can predictably scale from local food webs to metacommunities to biogeographic regions. This scaling process is determined by both the functional traits of species and heterogeneity in environmental conditions.
Data from: Microenvironment and functional-trait context dependence predict alpine plant community dynamics
Predicting the structure and dynamics of communities is difficult. Approaches linking functional traits to niche boundaries, species co‐occurrence and demography are promising, but have so far had limited success. We hypothesized that predictability in community ecology could be improved by incorporating more accurate measures of fine‐scale environmental heterogeneity and the context‐dependent function of traits. We tested these hypotheses using long term whole‐community demography data from an alpine plant community in Colorado. Species distributions along microenvironmental gradients covaried with traits important for below‐ground processes. Positive associations between species distributions across life stages could not be explained by abiotic microenvironment alone, consistent with facilitative processes. Rates of growth, survival, fecundity and recruitment were predicted by the direct and interactive effects of trait, microenvironment, macroenvironment and neighbourhood axes. Synthesis. Context‐dependent interactions between multiple traits and microenvironmental axes are needed to predict fine‐scale community structure and dynamics.
Data from: Improving genomic prediction for two Yorkshire populations with a limited size using single-step method
In this study, we conducted genomic prediction for two Yorkshire purebred populations (Yichun and Chifeng) from two different provinces of China that both had a limited population size. Two growth traits (age adjusted to 100 kg weight, AGE; back‐fat thickness adjusted to 100 kg weight, BF) and one reproduction trait (total number of piglets born, TNB) were analyzed with four prediction strategies: one‐population BLUP, joint two‐population BLUP, one‐population single‐step BLUP (SSBLUP) and joint two‐population SSBLUP. Our results illustrate that accuracies of genomic estimated breeding values were improved for BF and TNB for the Yichun population and for BF for the Chifeng population by genomic prediction (one‐population SSBLUP and joint two‐population SSBLUP). The accuracy of TNB for the Yichun population was increased two fold when comparing the one‐population SSBLUP to the one‐population BLUP prediction. Meanwhile, prediction biases were dramatically reduced for AGE for the Yichun population and for TNB for the Chifeng population. The conclusions of this study are as follows: first, genomic prediction is useful for improving prediction accuracy for purebred pig breeding farms with a limited population size; second, joint genomic prediction for different populations of the same breed with certain genetic links has the trend to further improve prediction accuracy.
Data from: Rainfall seasonality predicts the germination behaviour of a tropical dry-forest vine
Seed dormancy is considered an adaptive strategy in seasonal and/or unpredictable environments because it prevents germination during climatically favourable periods that are too short for seedling establishment. Tropical dry forests are seasonal environments where seed dormancy may play an important role in plant resilience and resistance to changing precipitation patterns. We studied the germination behaviour of seeds from six populations of the Neotropical vine Dalechampia scandens (Euphorbiaceae) originating from environments of contrasting rainfall seasonality. Seeds produced by second greenhouse-generation plants were measured and exposed to a favourable wet environment at different time intervals after capsule dehiscence and dispersal. We recorded the success and the timing of germination. All populations produced at least some dormant seeds, but seeds of populations originating from more seasonal environments required longer periods of after-ripening before germinating. Within populations, larger seeds tended to require longer after-ripening periods than did smaller seeds. These results indicate among-population genetic differences in germination behaviour and suggest that these populations are adapted to local environmental conditions. They also suggest a role of seed size in germination timing within populations. Ongoing changes in seasonality patterns in tropical dry forests may impose strong selection on these traits.
Data from: Assessing restoration success by predicting time to recovery – but by which metric?
<p><b>1. </b>Restoration of<b> </b>degraded ecosystems may take decades or even centuries. Accordingly, information about the current direction and speed of recovery provided by methods for predicting time to recovery may give important feedback to restoration schemes. While predictions of time to recovery have so far been based mostly upon change in species richness and other univariate predictors, the novel ordination-regression based approach (ORBA) affords a multivariate approach based upon species compositional change.</p> <p><b>2.</b> We used species composition data from four alpine spoil heaps in western Norway, recorded at three time points, to predict time to recovery using ORBA. This approach uses distances between restored plots and reference plots along a successional gradient, represented by a vector in ordination space, to model linear or asymptotic relationships of compositional change as a function of time. Results from ORBA were compared with results from models of more generic univariate attributes, i.e. total cover, species richness and properties of the physical environment as functions of time.</p> <p><b>3.</b> ORBA predictions of time to species compositional recovery varied from less than 60 years with linear models to 115–212 years with asymptotic models. The long estimated time to recovery suggests that the restoration schemes adopted for these spoil heaps are likely to be suboptimal.</p> <p><b>4. </b>Much shorter<b> </b>time to recovery was predicted<b> </b>from some of the more generic univariate attributes, i.e. species richness and total cover, than from species composition. Given the current rates of recovery, most spoil heaps will reach reference levels for total cover and species richness within 50 years while predictions indicate that 67–111 years are needed to restore levels of soil organic matter and pH.</p> <p><b>5.</b> <i>Synthesis and applications</i>. Species composition and soil conditions provide information of generally higher relevance for evaluation of ecosystem recovery processes than the most commonly used metric to assess restoration success, species richness. Species richness is decoupled from species compositional recovery, and likely to be a generally poor measure of restoration success. We therefore encourage further improvement of methods like the ordination-regression based approach that use species compositional data to predict time to recovery.09-Oct-2019</p>
Data from: Axial symptoms predict mortality in patients with Parkinson disease with subthalamic stimulation
Objective: To characterize how disease progression is associated with mortality in a large cohort of PD patients with long-term follow-up after STN-DBS. Methods: Motor and cognitive disabilities were assessed before, and 1, 2, 5 and 10 years after STN-DBS in 143 consecutive PD patients. We measured motor symptoms Off and On levodopa and STN-DBS, and recorded causes of death. We used linear mixed-models to characterize symptom progression, including interactions between treatment conditions and time to determine how treatments changed efficacy. We used joint models to link progression to mortality. Results: Median observation time was 12 years after surgery, during which akinesia, rigidity and axial symptoms worsened, with mean increases of 8.8 (SD 6.5), 1.8 (3.1) and 5.4 (4.1) points from year 1 to 10 after surgery (On dopamine/On STN-DBS), respectively. Responses to dopaminergic medication and STN-DBS were attenuated with time, but remained effective for all except axial symptoms, for which both treatments and their combination were predicted to be ineffective 20 years after surgery. Cognitive status significantly declined. Forty-one patients died with a median time to death of 9 years after surgery. The current level of axial disability was the only symptom that significantly predicted death (HR=4.30 [SE 1.50] per unit of square-root transformed axial score). Conclusions: We quantified long-term symptom progression and attenuation of dopaminergic medication and STN-DBS treatment efficacy in PD patients, and linked symptom progression to mortality. Axial disability significantly predicts individual risk of death after surgery, which may be useful for planning therapeutic strategies in PD.
Data from: Interpreting and predicting the spread of invasive wild pigs
The eruption of invasive wild pigs (IWPs) Sus scrofa throughout the world exemplifies the need to understand the influences of exotic and non-native species expansions. In particular, the continental USA is precariously threatened by a rapid expansion of IWPs, and a better understanding of the rate and process of spread can inform strategies that will limit the expansion. We developed a spatially and temporally dynamic model to examine three decades (1982–2012) of IWP expansion, and predict the spread of IWPs throughout the continental USA, relative to where IWPs previously inhabited. We used the model to predict where IWPs are likely to invade next. The average rate of northward expansion increased from 6.5 to 12.6 km per year, suggesting most counties in the continental USA could be inhabited within the next 3–5 decades. The spread of IWPs was primarily associated with expansion into areas with similar environmental characteristics as their previous range, with the exception of spreading into colder regions. We identified that climate change may assist spread into northern regions by generating milder winters with less snow. Otherwise, the spread of IWPs was not dependent on agriculture, precipitation, or biodiversity at the county level. The model correctly predicted 86% of counties that were invaded during 2012, and those predictions indicate that large portions of the USA are in immediate danger of invasion. Synthesis and applications. Anti-invasion efforts should focus along the boundaries of current occupied range to stop natural expansion, and anti-invasion policies should focus on stopping anthropogenic transport and release of invasive wild pigs (IWPs). Our results demonstrate the utility of a spatio-temporal examination to inform strategies for limiting the spread of IWPs.
Data from: Carcass predictability but not domestic pet introduction affects functional response of scavenger assemblage in urbanised habitats
<ol> <li><span>Urbanisation alters species richness and composition, but studies of urbanisation effects on ecological functions have often quantified variation in functional traits and changes in functional diversity rather than measuring directly how ecological functions vary between rural and urban assemblages. </span></li> <li><span>Consuming dead animal matter and recycling its nutrients stabilizes and structures food webs and therefore represents a key component of ecosystem functioning. Introduction of free-ranging domestic pet animals adds additional scavenger species to urban habitats, and increased predictability of carcass resources produced by human activities characterizes urban habitats. </span></li> <li><span>Here, we investigate the effect of urbanisation on the composition of diurnal and nocturnal scavenger assemblages and on the ecological function of carcass removal by using a carcass placement experiment in Swiss urban and adjacent rural habitats. </span></li> <li><span>While diurnal and nocturnal scavenger assemblages changed considerably from rural to urban areas by comprising particularly more domestic cats in the latter, carrion consumption rate did not differ between the two habitats. Predictability of carcass occurrence increased carrion consumption rate in both, urban and rural habitats but mainly native scavengers and not introduced domestic pets responded to the repeated placements.</span></li> <li><span>These results suggest that urbanisation shapes scavenger assemblage compositions without affecting their ecological function. The mechanism is likely due to a behavioural change of native scavengers in response to the occurrence of domestic pets resulting in functional plasticity of urban scavenger assemblages. The functional plasticity might be facilitated by the increased carcass predictability and additional anthropogenic food resources in urban habitats exploited by nutritionally flexible native scavenger species.</span></li> </ol>
Data from: Predicting ground temperatures across European landscapes
1. Ambient temperatures in natural environments can vary widely over short distances, especially on rugged ground where exposure to solar radiation depends on slope and aspect. Temperatures can also fluctuate rapidly, reaching values not revealed by climate data. Such fine-scale variation raises challenges for modelling species distributions under changing climates. 2. To avoid misunderstanding current species distributions and future changes, temperatures must be modelled at high resolutions. Most existing methods either require extensive parameterisation or are pre-parameterised for restricted localities and current conditions; here we describe a more versatile method intended for European landscapes under a wide range of scenarios. 3. The availability of high-resolution topographic data makes possible the use of projected solar irradiation to help predict local diurnal ground temperatures. Using time series from 83 points across Europe, we fitted statistical models for soil surface temperature based on geographical characteristics of the sites along with atmospheric variables obtained from a publicly-available database. The sites ranged from 40°N to 60°N and 2°W to 25°E, and from 43m to 1500m in elevation. 4. We compare models for monthly mean and daily afternoon temperatures, for open and tree-covered habitats. The effect of topography was greatest for the daily predictions, and generally more important in open than in tree-covered sites. Tests with data collected from other European locations in a different time period suggest that our models can predict monthly means with an error standard deviation of 2.7°C. We provide an R function that implements our models on the basis of readily-available data. 5. Our mean-temperatures model should be useful for understanding organisms' niches, dispersal possibilities and community dynamics, and for predicting species' refugia, range shifts and opportunities for adaptation under projected climate change.
Data from: Identifying cryptic diversity with predictive phylogeography
Identifying units of biological diversity is a major goal of organismal biology. An increasing literature has focused on the importance of cryptic diversity, defined as the presence of deeply diverged lineages within a single species. While most discoveries of cryptic lineages proceed on a taxon-by-taxon basis, rapid assessments of biodiversity are needed to inform conservation policy and decision-making. Here, we introduce a predictive framework for phylogeography that allows rapidly identifying cryptic diversity. Our approach proceeds by collecting environmental, taxonomic and genetic data from codistributed taxa with known phylogeographic histories. We define these taxa as a reference set, and categorize them as either harbouring or lacking cryptic diversity. We then build a random forest classifier that allows us to predict which other taxa endemic to the same biome are likely to contain cryptic diversity. We apply this framework to data from two sets of disjunct ecosystems known to harbour taxa with cryptic diversity: the mesic temperate forests of the Pacific Northwest of North America and the arid lands of Southwestern North America. The predictive approach presented here is accurate, with prediction accuracies placed between 65% and 98.79% depending of the ecosystem. This seems to indicate that our method can be successfully used to address ecosystem-level questions about cryptic diversity. Further, our application for the prediction of the cryptic/non-cryptic nature of unknown species is easily applicable and provides results that agree with recent discoveries from those systems. Our results demonstrate that the transition of phylogeography from a descriptive to a predictive discipline is possible and effective.
Data from: Body odour disgust sensitivity predicts authoritarian attitudes
Authoritarianism has resurfaced as a research topic in political psychology, as it appears relevant to explain current political trends. Authoritarian attitudes have been consistently linked to feelings of disgust, an emotion that is thought to have evolved to protect the organism from contamination. We hypothesized that body odour disgust sensitivity (BODS) might be associated with authoritarianism, as chemo-signalling is a primitive system for regulating interpersonal contact and disease avoidance, which are key features also in authoritarianism. We used well-validated scales for measuring BODS, authoritarianism and related constructs. Across two studies, we found that BODS is positively related to authoritarianism. In a third study, we showed a positive association between BODS scores and support for Donald Trump, who, at the time of data collection, was a presidential candidate with an agenda described as resonating with authoritarian attitudes. Authoritarianism fully explained the positive association between BODS and support for Donald Trump. Our findings highlight body odour disgust as a new and promising domain in political psychology research. Authoritarianism and BODS might be part of the same disease avoidance framework, and our results contribute to the growing evidence that contemporary social attitudes might be rooted in basic sensory functions.
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.