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zenodo36/100

Molecular simulations matching denaturation experiments for N6-methyladenosine

<p>Dataset relative to Molecular dynamics simulation performed for the work &quot;Molecular simulations matching denaturation experiments for N6-methyladenosine&quot;.<br> <br> The dataset contains data of 73 alchemical simulations and is subdivided in 10 zip files, one for each of the systems considered in this work<br> <br> Folders are named following the scheme: system_configuration_forcefield, or 1M_system_configuration_forcefield for simulation performed at 1 M salt concentrations<br> <br> Each folder contains:<br> - topology files (topol.top, topol_RNA_chain_A.itp, topol_RNA_chain_B.itp)<br> - .mdp files for each replica<br> - index files needed to reconstruct the demuxed trajectories (replica_index.xvg , replica_index.xvg)<br> - 20 .edr files corresponding to energies for the concatenated trajectory computed for 20 set of DeQs drawn from&nbsp; a gaussian distribution<br> - 16 folders, one for each replica (lam0 ... lam15), containing:<br> &nbsp;&nbsp; - final configuration (confout.gro)<br> &nbsp;&nbsp; - log file (md.log)<br> &nbsp;&nbsp; - dhdl.xvg files needed for computing Free Energies via &quot;gmx bar&quot; command<br> &nbsp;&nbsp; - energies relative to the single replica (ener.edr)<br> &nbsp;&nbsp; - energies for the concatenated trajectories recomputed for the realtive replica hamiltonian (ener_trj_conc.edr).</p> <p>&nbsp;</p>

opencc-by-4.0Apr 2022View details →
dryad36/100

Metabolic syndrome for the prognosis of postoperative complications after open pancreatic surgery in Chinese adult: a propensity score matching study

<p><strong>Background: </strong>To investigate the relationship between metabolic syndrome (MS) and postoperative complications in Chinese adults after open pancreatic surgery.</p> <p><strong>Methods: </strong>Relevant data were retrieved from the Medicalsystem® database of Changhai hospital (MDCH). All patients who underwent pancreatectomy from January 2017 to May 2019 were included, and relevant data were collected and analyzed. A propensity score matching (PSM) and a multivariate generalized estimating equation were used to investigate the association between MS and composite compositions during hospitalization. Cox regression model was employed for survival analysis.</p> <p><strong>Results: </strong>1481 patients were finally eligible for this analysis. According to diagnostic criteria of Chinese MS, 235 patients were defined as MS, and the other 1246 patients were controls. After PSM, no association was found between MS and postoperative composite complications (OR: 0.958, 95%CI: 0.715-1.282, P=0.958). But MS was associated with postoperative acute kidney injury (OR: 1.730, 95%CI: 1.050-2.849, P=0.031). Postoperative AKI was associated with mortality in 30 days and 90 days after surgery (P&lt;0.001).</p> <p><strong>Conclusions: </strong>MS is not an independent risk factor correlated with postoperative composite complications after open pancreatic surgery. But MS is an independent risk factor for postoperative AKI of pancreatic surgery in Chinese population, and AKI is associated with survival after surgery.</p>

opencc-zeroMay 2022View details →
dryad36/100

Mandrill mothers associate with infants who look like their own offspring using phenotype matching

<p>Behavioral discrimination of kin is a key process structuring social relationships in animals. In this study, we provide a first example of discrimination towards non-kin by third-parties through a mechanism of phenotype matching. In mandrills, we recently demonstrated increased facial resemblance among paternally-related juvenile and adult females indicating adaptive opportunities for paternal kin recognition. Here, we hypothesize that mothers use offspring's facial resemblance with other infants to guide offspring's social opportunities towards similarly-looking ones. Using deep learning for face recognition in 80 wild mandrill infants, we first show that infants born to the same father or conceived during the tenure of the same alpha male resemble each other the most, independently of their age, sex or maternal origin, extending previous results to the youngest age class. Using long-term behavioral observations on association patterns and controlling for matrilineal origin, maternal relatedness and infant age and sex, we then demonstrate that, as hypothesized, mothers are spatially closer to infants that resemble their own offspring more, thereby facilitating associations among similar-looking infants. Using theoretical modeling, we describe a plausible evolutionary process whereby mothers gain fitness benefits by promoting nepotism among paternally related infants. This mechanism, that we call "second order kin selection", may extend beyond mother-infant interactions and has the potential to explain cooperative behaviors among non-kin in social species, including humans.</p>

opencc-zeroMay 2022View details →
dryad36/100

Data and code from: Fruit bat migration matches green wave in seasonal landscapes

<p><span>Migrating </span><span>grazers and carnivores</span><span> respond to seasonal changes in the environment and often match peaks in resource abundance. However, it is unclear if and how frugivorous animals use phenological events to time migration, especially in the tropics.<strong> </strong></span>The straw-colored fruit bat (<em>Eidolon helvum</em>), Africa's most gregarious fruit bat, forms large seasonal colonies throughout much of sub-Saharan Africa. We hypothesized that aggregations of <em>E. helvum</em> match the timing of their migration with phenologies of plant growth or precipitation.<strong> </strong>Using monthly colony counts from across much of the species' range, we matched peak colony size to landscape phenologies and explored the variation among colonies matching the overall closest phenological event.<strong> </strong>Peak colony size was closest to <span>the </span><span>peak</span><span> instantaneous</span><span> rate of green-up</span><span>,</span><span> and sites with closer temporal matching were associated with higher maximum greenness, short growing season, and larger peak colony size. <em>E</em></span><span><em>idolon</em></span><em><span> helvum</span></em><span> seem to time their migrations to move into highly seasonal landscapes to exploit short-lived explosions of food and may benefit from collective sensing to time migrations.<strong> </strong></span>The link between rapid changes in colony size and phenological match may also imply potential collective sensing of the environment. O<span>verall decreasing bat numbers along with various threats might cause this property of large colonies to be lost</span><span>.<strong> </strong></span>R<span>emote sensing data</span><span>, although, indirectly linked to fruiting events,</span><span> can potentially be used to globally describe and predict the migration of frugivorous species in a changing world</span><span>.</span></p>

opencc-zeroMay 2022View details →
dryad36/100

Data from: Climate matching and anthropogenic factors contribute to the colonisation and extinction of local populations during avian invasions

<p>Concern about the impacts of biological invasions has generated a great deal of interest in understanding factors that determine invasion success. Most of our current knowledge comes from static approaches that use spatial patterns as a proxy of temporal processes. These approaches assume that species are present in areas where environmental conditions are the most favourable. However, this assumption is problematic when applied to dynamic processes such as species expansions when equilibrium has not been reached. In our work, we analyse the roles played by human activities, climatic matching, and spatial connectivity on the two main underlying processes shaping the spread of invasive species (i.e., colonisation and extinction) using a dynamic modelling approach. For this, we used a large dataset that has recorded the occurrence of two invasive bird species -the ring-necked and the monk parakeets-  in the Iberian Peninsula from 1991 to 2016. </p>

opencc-zeroJun 2022View details →
dryad36/100

Beyond sex and aggression: Testosterone rapidly matches behavioral responses to social context and tries to predict the future

<p>Although androgens are widely studied in the context of aggression, androgenic influences on prosocial behaviors have been less explored. We examined testosterone's (T) influence on prosocial and aggressive responses in a positively-valenced social context (interacting with a pairbond partner) and a negatively-valenced context (interacting with an intruder) in socially monogamous Mongolian gerbils. T increased and decreased prosocial responses in the same individuals towards a pairbond partner and an intruder, respectively, both within 30 minutes, but did not affect aggression. T also had persistent effects on prosocial behavior; males in which T initially increased prosocial responses towards a partner continued to exhibit elevated prosocial responses towards an intruder male days later until a second T injection rapidly eliminated those responses. Thus, T surges can rapidly match behavior to current social context, as well as prime animals for positive social interactions in the future. Neuroanatomically, T rapidly increased hypothalamic oxytocin, but not vasopressin, cellular responses during interactions with a partner. Together, our results indicate that T can facilitate and inhibit prosocial behaviors depending on social context, that it can influence prosocial responses across rapid and prolonged time scales, and that it affects oxytocin signaling mechanisms that could mediate its context-dependent behavioral influences.</p>

opencc-zeroJun 2022View details →
zenodo36/100

Appendix for "Don't DIY: Automatically transform legacy Python code to support structural pattern matching"

<p>This is the appendix for paper &quot;Don&rsquo;t DIY: Automatically transform legacy Python code to support structural pattern matching&quot; presented in SCAM 2022.</p> <p><strong>Abstract</strong></p> <p><em>As data becomes more and more complex as technology evolves, the need to support more complex data types in programming languages has grown. However, without proper storage and manipulation capabilities, handling such data can result in hard-to-read, difficult-to-maintain code. Therefore, programming languages continuously evolve to provide more and more ways to handle complex data. Python 3.10 introduced structural pattern matching, which serves this exact purpose: we can split complex data into relevant parts by examining its structure, and store them for later processing. Previously, we could only use the traditional conditional branching, which could have led to long chains of nested conditionals. Maintaining such code fragments can be cumbersome. In this paper, we present a complete framework to solve the aforementioned problem. Our software is capable of examining Python source code and transforming relevant conditionals into structural pattern matching. Moreover, it is able to handle nested conditionals and it is also easily extensible, thus the set of possible transformations can be easily increased.</em></p>

opencc-by-4.0Jul 2022View details →
zenodo36/100

Wikary: A Dataset of N-ary Wikipedia Tables Matched to Qualified Wikidata Statements

<p><strong>Wikary: A Dataset of N-ary Wikipedia Tables Matched to Qualified Wikidata Statements</strong></p> <p>Created for The SemTab 2022 Datasets Track challenge.</p> <p><strong>General</strong></p> <p>Explanation of columns names used in both files</p> <p>`lang` - language and Wikipedia version used</p> <p>`pageTitle` - page title</p> <p>`tableIndex` -&nbsp; index where the given table is located on the page</p> <p><strong>Tables file</strong></p> <p>Columns names are used only in the tables file</p> <p>`pageEntity` - Wikidata entity associated with the page</p> <p>`sectionTitle` - the title of the section where the table is located</p> <p>`tableCaption` - caption of the table</p> <p>`headers` - headers of the table</p> <p>`HTML` - HTML of the table</p> <p><strong>Matches file</strong></p> <p>Columns names are used only in the matches file</p> <p>`rowIndex` - index of a row where the match is found for a given table</p> <p>`wikidata_ids` - Wikidata entities in the row including `pageEntity`</p> <p>`entities_index` -&nbsp; indexes in which cell Wikidata entities were found, -1 used for Wikidata entity associated with the page, -9 used for cells that include a date in a cell</p> <p>`entities_anchor` -&nbsp; anchor text of cells where Wikidata entities were found</p> <p>`entities_cell_text` -&nbsp; cell text of cells where Wikidata entities were found</p> <p>`subject` - subject of Wikidata statement</p> <p>`property` - property of Wikidata statement</p> <p>`object` - object of Wikidata statement</p> <p>`property_qualifier` - property qualifier of Wikidata statement</p> <p>`qualifier_value` - qualifier value of Wikidata statement</p> <p>`id_match` - 1 means that row contains *Wikidata identifier match*, 0 means no match</p> <p>`year_match` - 1 means that row contains *Year cell match*, 0 means no match</p> <p>`year_part_match` - 1 means that row contains *Within cell year match*, 0 means no match</p> <p>&nbsp;</p>

opencc-by-4.0Aug 2022View details →
zenodo36/100

Headache in workers. A matched case-control study

<p>Data utilized for the study to be published</p>

opencc-by-4.0Aug 2022View details →
zenodo36/100

Data samples for Flow-matching -- efficient coarse-graining molecular dynamics without forces

<p>CG samples generated during the training and validation processes in the flow-matching project. Accompanying the preprint &quot;Flow-matching -- efficient coarse-graining molecular dynamics without forces&quot;: https://arxiv.org/abs/2203.11167. Detailed descriptions can be found in the preprint as well as the included README.</p>

opencc-by-4.0Sep 2022View details →
zenodo36/100

Dataset for the Job/Site AI matching problem in GlideinWMS

<p>Dataset used for the&nbsp;time-series analysis and classification analysis.</p>

opencc-by-4.0Sep 2022View details →
zenodo36/100

Conservation networks do not match ecological requirements of amphibians

<p>Supplementary files of the paper Matutini et al. 2023 (https://doi.org/10.1101/2022.07.18.500425)</p> <p>Dataset sample and R script</p>

opencc-by-4.0Jun 2023View details →
zenodo36/100

Exact structure match queries against BindingDB between September 2004 and August 2012

<p>Exact structure match queries against BindingDB between September 2004 and August 2012</p> <p>The queries were generated by users of the BindingDB web interface between September 2004 and mid-August of 2012. Structures were sketched using Marvin.</p> <p>If you use this data set, please cite:</p> <p>&nbsp; Liu T, Lin Y, Wen X, Jorissen RN, Gilson MK.<br> &nbsp; BindingDB: a web-accessible database of experimentally determined<br> &nbsp;&nbsp;&nbsp; protein-ligand binding affinities.<br> &nbsp; Nucleic Acids Res. 2007 Jan;35(Database issue):D198-201.<br> &nbsp; doi: 10.1093/nar/gkl999<br> &nbsp; Epub 2006 Dec 1<br> &nbsp; PMID: 17145705<br> &nbsp; PMCID: PMC1751547<br> &nbsp; https://doi.org/10.1093%2Fnar%2Fgkl999</p> <p>The included files are:</p> <p>README<br> ------</p> <p>A text file with more details about the data sets and their provenance.</p> <p>exact.dat.zstd<br> --------------</p> <p>The processed data set with 3,414,228 queries, one query per line. The file is compressed using Zstandard. The queries are a combination of CXSMILES, non-standard SMILES, and non-SMILES strings.</p> <p>BindingDB_exact.dat<br> -------------------</p> <p>A cleaned-up subset with 119,883 entries, one entry per line. Each entry has two columns, separated by a tab. The first column is the (possibly cleaned-up) CXSMILES from the source data, the second is the number of times the CXSMILES occurs in the source data. Each CXSMILES is present only once in the data set.</p> <p>NOTE: the CXSMILES have not be canonicalized. Canonicalization using RDKit 2021.09.4 results in 94,362 unique queries, but causes the extended CXSMILES annotations to disappear.</p> <p>bindingdb_cleanup.py<br> --------------------</p> <p>The Python program used to convert exact.dat.zstd to BindingDB_exact.dat.</p> <p>History<br> =======</p> <p>15 August 2012<br> --------------</p> <p>Contribution to the SQC.</p> <p>Tiqing Lui</p> <p>18 Aug 2012<br> -----------</p> <p>Initial import into the SQC</p> <p>Andrew Dalke</p> <p>28 Aug 2022<br> -----------</p> <p>Ported bindingdb_cleanup.py to Python 3.</p> <p>Added cleanup methods to add brackets to &quot;(O-)&quot;, &quot;C@@&quot;, &quot;nH&quot;, and &quot;NH&quot; when appropriate.</p> <p>Simplified bindingdb_cleanup.py by dropping support for tools other than RKit.</p> <p>Updated for distribution on Zenodo.</p> <p>Andrew Dalke</p> <p>&nbsp;</p>

opencc-by-4.0Sep 2022View details →
zenodo36/100

Elevated perceived stress in university students due to COVID-19 pandemic: Potential contributing factors in a propensity-score matched sample

<p><strong>Open Data and Open Materials of: </strong></p> <p><strong>Elevated perceived stress in university students due to COVID-19 pandemic: Potential contributing factors in a propensity-score matched sample.&nbsp;</strong></p> <p><strong><em>Scandinavian Journal Of Psychology</em>.</strong></p> <p><strong>Abstract</strong></p> <p><strong>Objective</strong>: Onset of the Coronavirus Disease 2019 (COVID)-pandemic has increased students&rsquo; perceived burdens. The current study aimed to examine COVID-related changes and to identify potential factors that contribute to students&rsquo; stress.</p> <p><strong>Method</strong>: Adopting a cross-sectional cohort-study design, we examined perceived stress, depressive and anxiety symptoms with a specific focus on the role of study-related variables such as perceived study-related demands, study-related resources, academic procrastination, and stress enhancing beliefs. Two cohorts (<em>N</em><sub>pre-COVID</sub>=2175;<em>N</em><sub>COVID</sub>=959) were recruited at the same university and matched with regard to their propensity score (age, gender, semester).</p> <p><strong>Results</strong>: Compared to the pre-COVID cohort, university students in the COVID-cohort reported more perceived stress, more depressive and anxiety symptoms, more academic procrastination due to fear of failure, more stress-enhancing beliefs, more distress due to the housing situation, and more perceived study-related challenges (Cohen&rsquo;s <em>d</em>=.15&ndash;.45). A stepwise regression analysis identified depressive symptoms, procrastination due to fear of failure, general self-efficacy, increased study demands, perceived difficulties with to self-organised learning, distress due to housing, and stress enhancing beliefs as predictors of perceived stress in the COVID-cohort.</p> <p><strong>Discussion</strong>: Findings suggest that the switch to online-only education increased the study-related burden for students, primarily due to exams being replaced by a greater amount of regular coursework and imposing demands on self-organised learning. Possibly, stress enhancing beliefs and procrastination due to fear of failure might have been elevated due to less opportunity for social referencing and lack of felt social support by peer students.</p> <p><strong>Conclusion</strong>: Experienced increased burden in students during the COVID pandemic was mostly accounted for by the lack of perceived individual resources rather than by the increase in objective study-related demands.</p>

opencc-by-4.0Feb 2024View details →
zenodo36/100

Cell type matching across species using protein embeddings and transfer learning

<p>TACTiCS is a method to transfer and align cell types in cross-species data. This repository contains the protein sequences,&nbsp;protein&nbsp;embeddings, count matrices and trained models for human, mouse and marmoset.</p>

opencc-by-4.0Jan 2023View details →
zenodo36/100

Dataset: Problem-centred interviews results for Matching Data Life Cycle and Research Processes in Engineering Sciences

<p>The authors would like to thank the Federal Government and the Heads of Government of the L&auml;nder, as well as the Joint Science Conference (GWK), for their funding and support within the framework of the NFDI4Ing consortium. Funded by the German Research Foundation (DFG) - project number 442146713.</p>

opencc-by-4.0Jun 2024View details →
dryad36/100

At matched loads, aging does not alter ankle, muscle, or tendon stiffness

<p>Older adults have difficulty maintaining balance when faced with postural disturbances, a task that is influenced by the stiffness of the triceps surae and Achilles tendon. Age-related changes in Achilles tendon stiffness have been reported at matched levels of effort, but measures typically have not been made at matched loads, which is important due to age-dependent changes in strength. Moreover, there has been limited investigation into age-dependent changes in muscle stiffness. Here, we investigate how age alters muscle and tendon stiffness and their influence on ankle stiffness. We hypothesized that age-related changes in muscle and tendon contribute to reduced ankle stiffness in older adults and evaluated this hypothesis when either load or effort were matched. We used B-mode ultrasound with joint-level perturbations to quantify ankle, muscle, and tendon stiffness across a range of loads and efforts in seventeen healthy younger and older adults. At matched loads relevant to standing and the stance phase of walking, there was no significant difference in ankle, muscle, or tendon stiffness between groups (all p &gt; 0.13). However, at matched effort, older adults exhibited asignificant decrease in ankle (27%; p = 0.008), muscle (37%; p = 0.02), and tendon stiffness (22%; p = 0.03) at 30% of maximum effort. This is consistent with our finding that older adults were 36% weaker than younger adults in plantarflexion (p = 0.004). Together, these results indicate that, at the loads tested in this study, there are no age-dependent changes in the mechanical properties of muscle or tendon, only differences in strength that result in altered ankle, muscle, and tendon stiffness at matched levels of effort.</p>

opencc-zeroMay 2024View details →
dryad36/100

Physiological state matching in a pair bonded poison frog

<p>More than a century ago, Charles Darwin hypothesized that the empathy-like phenotype is a phylogenetically widespread phenomenon. This idea remains contentious, due to the challenges of empirically examining emotions, and few investigations among non-mammalian vertebrates. We provide support for Darwin's hypothesis by discovering partial evidence for the most ancestral form of empathy, emotional contagion (i.e., matching another individual's emotional state), in the pair bonding mimetic poison frog, Ranitomeya imitator. We found that male corticosterone, a physiological biomarker of stress, positively correlates with female partners in experimental and semi-natural conditions. This does not appear to coincide with behavioral state-matching. However, it is specific to female partners relative to familiar female non-partners, and is independent of effects that commonly confound studies on emotional contagion. Furthermore, this physiological state-matching is irrespective of partnership longevity or lifetime reproductive output. These results physiologically indicate socially selective emotional contagion in a monogamous amphibian, and paradigms that elicit coinciding neural and behavioral indicators and morphogenic co-variation are needed for further corroboration. Further studies on ancestral forms of empathy in non-mammalian vertebrates are warranted.</p>

opencc-zeroJun 2024View details →
zenodo36/100

African wood density database with matches to the taxonomic backbone data sets of World Flora Online (version 2023.12) and the World Checklist of Vascular Plants (version 11)

<p>The <strong><span>African Wood Density Database </span></strong><span>provides air-dry wood density data for over 750 tree species grown in Africa.</span></p> <p>This archive provides taxonomic matches with recent versions of <strong>World Flora Online</strong> (WFO; <a href="../records/10425161">version 2023.12 downloaded from Zenodo</a>; Borch et al. <a href="https://onlinelibrary.wiley.com/doi/10.1002/tax.12373">2020</a>) and the <strong>World Checklist of Vascular Plants</strong> (WCVP; <a href="https://sftp.kew.org/pub/data-repositories/WCVP/Archive/">version 11 downloaded from the Kew data depository</a>; Govaerts et al. <a href="https://doi.org/10.1038/s41597-021-00997-6">2021</a>). Matching was done via the <strong>WorldFlora</strong> package (<a href="https://cran.r-project.org/package=WorldFlora">version 1.14-3</a>; Kindt <a href="https://bsapubs.onlinelibrary.wiley.com/doi/full/10.1002/aps3.11388">2020</a>), using similar scripts as documented in this Rpub: <a href="https://rpubs.com/Roeland-KINDT/1134151">https://rpubs.com/Roeland-KINDT/1134151</a>.</p> <p>&nbsp;</p> <ul> <li><span>Carsan, S. Orwa, C. Harwood, C. Kindt, R. Stroebel, A. Neufeldt, H. and Jamnadass, R. 2012. African Wood Density Database. World Agroforestry Centre, Nairobi. <a href="https://apps.worldagroforestry.org/treesnmarkets/wood/">https://apps.worldagroforestry.org/treesnmarkets/wood/#</a> </span></li> <li><span>Borsch, T., Berendsohn, W., Dalcin, E., Delmas, M., Demissew, S., Elliott, A., Fritsch, P., Fuchs, A., Geltman, D., G&uuml;ner, A., Haevermans, T., Knapp, S., le Roux, M.M., Loizeau, P.-A., Miller, C., Miller, J., Miller, J.T., Palese, R., Paton, A., Parnell, J., Pendry, C., Qin, H.-N., Sosa, V., Sosef, M., von Raab-Straube, E., Ranwashe, F., Raz, L., Salimov, R., Smets, E., Thiers, B., Thomas, W., Tulig, M., Ulate, W., Ung, V., Watson, M., Jackson, P.W. and Zamora, N. (2020), World Flora Online: Placing taxonomists at the heart of a definitive and comprehensive global resource on the world's plants. TAXON, 69: 1311-1341. <a href="https://doi.org/10.1002/tax.12373">https://doi.org/10.1002/tax.12373</a></span></li> <li><span>Govaerts, R., Nic Lughadha, E., Black, N. <em>et al.</em> The World Checklist of Vascular Plants, a continuously updated resource for exploring global plant diversity. <em>Sci Data</em> <strong>8</strong>, 215 (2021). <a href="https://doi.org/10.1038/s41597-021-00997-6">https://doi.org/10.1038/s41597-021-00997-6</a></span></li> <li><span>Kindt, R. 2020. WorldFlora: An R package for exact and fuzzy matching of plant names against the World Flora Online taxonomic backbone data. <em>Applications in Plant Sciences</em> 8(9): e11388. <a href="https://doi.org/10.1002/aps3.11388">https://doi.org/10.1002/aps3.11388</a></span></li> </ul> <p>&nbsp;</p> <p>Original funding for the database was provided <span>by the Carbon Benefits Project (CBP) supported by The Global Environment Facility (GEF). Development of the 2024 version </span>was supported by the <strong>Darwin Initiative</strong> to project DAREX001 of <em>Developing a Global Biodiversity Standard certification for tree-planting and restoration</em>, by <strong>Norway&rsquo;s International Climate and Forest Initiative through the Royal Norwegian Embassy in Ethiopia</strong> to the <em>Provision of Adequate Tree Seed Portfolio</em> project in Ethiopia, by the <strong>Green Climate Fund</strong> through the IUCN-led <em>Transforming the Eastern Province of Rwanda through Adaptation</em> project and through the <em>Readiness proposal on Climate Appropriate Portfolios of Tree Diversity for Burkina Faso</em>, by the <strong>Bezos Earth Fund</strong> to the <em>Bezos Quality Tree Seed for Africa in Kenya and Rwanda</em> project and by the <strong>German International Climate Initiative (IKI)</strong> to the regional tree seed programme on <em>The Right Tree for the Right Place for the Right Purpose in Africa</em>. When using <strong>African Wood Density database</strong> in your work, cite the 2012 version (Carsan et al. <a href="https://apps.worldagroforestry.org/treesnmarkets/wood/">2012</a>) as well as this repository using the DOI.</p>

opencc-by-4.0Jun 2024View details →
zenodo36/100

Data set for ODI cricket matches from 1987 to 2023 (extracted from ESPN Cricinfo) and code (R) used for a statistical study

<p>Here I present the data and code that has been used to study the statistical evolution of ODI cricket. The preprint for this research is available at:&nbsp;</p> <div> <div> <div> <table> <tbody> <tr> <td><a href="https://doi.org/10.48550/arXiv.2406.11652">https://doi.org/10.48550/arXiv.2406.11652</a> <div><span>Focus to learn more</span></div> </td> </tr> </tbody> </table> </div> </div> </div> <div>&nbsp;</div>

opencc-by-4.0Jun 2024View details →

ScienceDex guides

Understand access before you commit

These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

Compare curated 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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record

ScienceDex for faculty

Your academic CV and NIH biosketch

Make your CV in your school's format and your NIH biosketch from it, then download both as Word files.