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2023 HamSCI Gladstone Signal Spotting Challenge (GSSC) Data and Scoring Calculations
<p>The ZIP file contains all data sources used in scoring the October 13, 2023 running of the HamSCI GSSC competition: ReverseBeacon.net, WSPRnet.org, PSKReporter.info. There is a ZIP file containing each entrant's data as extracted from the WSPRnet data. Further, it contains the participant entries (in an Apple Mac OS Numbers formatted spreadsheet) along with the scoring calculation file (Numbers format). Included is a description of the scoring methodology (Apple Mac OS Pages format) and the shell scripts used to extract the WSPRnet data. The GSSC 2023 Results Writeup.pdf, as published to the HamSCI.org website, summarizes the entire event. </p> <p>Additional ZIP files, eg gssc2023bonusXX.zip, contain emails and attachments (PDF, jpg, etc) submitted by the entrants for bonus points.</p> <p>The purpose of the GSSC competition was to generate ham radio 'spots' (records of 1- and 2-way amateur radio contacts on the shortware bands, aggregated in the form of transmission and reception reports stored in the data sources referenced above). The 'spot' data is intended for use in studies of radio wave propagation via the ionosphere.</p>
Datasets for AGIMA-Score modeling - latest
<p>This data repositary includes the following datasets.</p> <p>(1) 'training.zip' -- It is a secondary dataset that originates from the Refined Set in PDBbind database (version V2020). When training models like AGIMA-Score, the complexes in the validation/test sets need to be removed. 5007 complexes are included.</p> <p>(2) 'validation.zip' -- It is a secondary dataset that originates from the Core Set (CASF-2016) in PDBbind database (version V2020). It was used as the validation set (for parameter tuning) when building the AGIMA-Score models. Complexes that are similar to those in the training set (protein sequence similarity > 0.3 and ligand similarity > 0.7) were removed. 195 complexes are included.</p> <p>(3) 'test1.zip' -- It is a secondary dataset that originates from CSAR-HiQ1. It was used as the Test1 set for evaluating the AGIMA-Score models. Complexes that are similar to those in the training/validation sets (protein sequence similarity > 0.3 and ligand similarity > 0.7) were removed. 116 complexes are included.</p> <p>(4) 'test2.zip' -- It is a secondary dataset that originates from CSAR-HiQ2. It was used as the Test2 set for evaluating the AGIMA-Score models. Complexes that are similar to those in the training/validation/Test1 sets (protein sequence similarity > 0.3 and ligand similarity > 0.7) were removed. 102 complexes are included.</p> <p>(5) 'indexes.zip' -- It includes the labels (binding affinity data) for the complexes in above (1)~(4) sets.</p> <p>A file 'xxxx_atm_prop.txt' indicates a specific protein-ligand complex in above sets, with 'xxxx' denoting the original complex ID in PDBbind and the data fields showing the following information. Note that here each row in such as file indicates an atom in the binding complex.</p> <p>--------------------------------------------------------------------------------<br>id - atom id with protein atoms starting from 1 and ligand atoms also starting from 1 (integer)</p> <p>atmnum - atomic number (integer)</p> <p>x,y,z - the X, Y, Z coordinates for the atom (float)</p> <p>atmB,atmC,atmN,atmO,atmP,atmS,atmSe - whether the atom is of some specific type, such as B, C, N, O, P, S and Se (binary)</p> <p>atmHalogen - whether the atom is a halogen atom (binary)</p> <p>atmMetal,atmMetallic - whether the atom is metal (binary)</p> <p>hybridization - hybridization type of the atom (integer)</p> <p>heavyneighbors - number of heavy-atom neighbors (integer)</p> <p>heteroneighbors - number of hetero-atom neighbors (integer)</p> <p>hydrophobic,aromatic,acceptor,donor,ring - pharmacophoric properties of the atom (binary)</p> <p>partialCH - paricial charge of the atom (float)</p> <p>posionizable,negionizable - whether the atom is positively ionizable or negatively ionizable (binary)</p> <p>exlvolume - excluded volume of the atom (float)</p> <p>vdwrad - VDW radius of the atom (float)</p> <p>moltype - molecule the atom belongs to (0 for protein and 1 for ligand)</p> <p>"neighbors(nbr:idx--anum--(sbond,dbond,tbond,arombond,ringbond))" - information of the covalent neighboring atoms for the atom<br>--------------------------------------------------------------------------------</p> <p>(6) 'docker.zip' -- A Docker container with the trained AGIMA-Score18 model pre-installed.</p> <p>--------------------------------------------------------------------------------</p> <p>trained_mdl.keras - the trained AGIMA-Score18 model in keras format</p> <p>Dockerfile-genpropfile and Dockerfile - Docker files for generating the property files from a protein and a ligand file (Dockerfile-genpropfile) and making predictions for an input property file (Dockerfile)</p> <p>requirements-genpropfile.txt and requirements.txt - required packages and their versions for generating the models</p> <p>app-genpropfile.py and app.py - the application files to run the models (indicated in the Docker files)</p> <p>1a9m_ligand.pdb, 1a9m_protein.pdb, 1ax1_atm_prop.txt - example files for demonstration purposes</p> <p>NOTE.txt - this file shows how to run the Docker containers and use the API</p> <p>--------------------------------------------------------------------------------</p> <p>(7) 'predictions_byAGIMAscore18.zip' -- It includes the predictions generated by the AGIMA-Score18 model for the validation and test sets. Three files ('predictions_validation.csv', 'predictions_test1.csv', and 'predictions_test2.csv',) are included.</p>
FIGURE 1. The best scoring phylogram generated from a in Colletotrichum dracaenigenum, a new species on Dracaena fragrans
FIGURE 1. The best scoring phylogram generated from a final MP dataset based on combined ITS, GAPDH, CHS-1, ACT and TUB2 sequence data. Bootstrap support values for maximum parsimony (MP, left) and maximum likelihood (ML, middle) are greater than 60% and Bayesian posterior probabilities (PP, right) equal to or greater than 0.95 are indicated at the nodes. The new taxon is bolded in red.
Visualization results of Kinase-Ligand complex based on deep learning prediction score
<p>It contains all the validation results used in the manuscript "Global analysis of deep learning prediction using large-scale in-house kinome-wide profiling data". "ligand_list.smi" shows the compound structure information for each ligand, and the ligand atom weighting results for each target are stored in the "Targets" folder. PyMol can be used to visualize the results by using "load.py" (see readme for how to run it).</p>
Scores from S.invicta queen supergene pheromone discrimination assays
<p>Ants use chemical signals to communicate for various purposes related to colony function. Social organization in the red imported fire ant, <i>Solenopsis invicta</i>, is determined by the <i>Sb</i> supergene, with colonies of the monogyne (single-queen) form lacking the element and colonies of the polygyne (multiple-queen) form possessing it. Polygyne workers accept new reproductive queens in their nest, but only those carrying <i>Sb</i>; young winged queens lacking this genetic element are executed as they mature sexually in their natal nest or as they attempt to enter a foreign nest to initiate reproduction after mating and shedding their wings. It has been suggested that queen supergene genotype status is signaled to workers by unsaturated cuticular hydrocarbons, while queen reproductive status is signaled by piperidines (venom alkaloids). We used high-throughput behavioral assays to study worker acceptance of paper dummies dosed with fractions of extracts of polygyne queens, or blends of synthetic counterparts of queen cuticular compounds. We show that the queen supergene pheromone comprises a blend of monoene and diene unsaturated hydrocarbons. Our assays also reveal that unsaturated hydrocarbons elicit discrimination by polygyne workers only when associated with additional compounds that signal queen fertility. This synergistic effect was obtained with a polar fraction of queen extracts, but not by the piperidine alkaloids, suggesting that the chemical(s) indicating queen reproductive status are compounds more polar than cuticular hydrocarbons but are not the piperidine alkaloids. Our results advance understanding of the role of chemical signaling that is central to the regulation of social organization in an important invasive pest and model ant species.</p>
Stomach content, biomass, abundance and body score of long-tailed ducks (Clangula hyemalis) from south-eastern Baltic Sea
<p>The long-tailed duck (<em>Clangula hyemalis</em>) is a vulnerable and declining species wintering in the Baltic Sea. The introduction of the invasive fish, the round goby (<em>Neogobius melanostomus</em>), dramatically impacted the benthic macrofauna in hard-bottom, while no significant changes occurred in soft-bottom benthic macrofauna. Therefore, we aimed to assess the extent to which the diet of long-tailed duck changed in two different bottom types. We analysed the stomach content of 251 long-tailed ducks bycaught in gillnets from 2016 to 2020 in hard- and soft-bottom habitats and compared these results with those published by Žydelis and Ruškyte (2005). The results show that the long-tailed duck experienced a change in diet in hard-bottom habitats, shifting from the blue mussel to Hediste diversicolor, barnacles and fish. In soft-bottom habitats, their diet remained similar over time and was based on H. diversicolor, a few bivalve species and Saduria entomon. There was no evidence of significant differences in diet neither between sex nor age. Despite the above-mentioned changes in diet, the average body condition of the species did not change neither over time nor between habitats. This confirms that long-tailed ducks have high feeding flexibility and quick species response to changes in prey availability, as they are capable of shifting their diet to new prey.</p>
Risset's Score Codes R20_003 TEST
<p>Risset's Sketches Score Code Music IV</p> <p>Audio Reconstruction using Victor Lazzarini and Bill Schotstaed Music V replica</p> <p>Copyright: Fonds Risset, PRISM, CNRS Marseille.</p>
Histology, TNF-alpha, and collagen score, body weight, and ulcer size
<p><strong>Background: </strong>Areca nut (<em>Areca catechu</em> L.) i<span>s the seed of the fruit of the oriental palm that is commonly </span>used among Southeast Asian communities. Chrysanthemum (<em>Dendrathema grandiflora</em>) is a flowering plant originating from East Asia and dominantly grows in China. Both of these plants have strong antioxidant activities. To investigate the mechanism of their wound healing activities, we prepared areca nut and chrysanthemum polyethylene oral gel and performed several <em>in vivo</em> assays using Sprague-Dawley rats.</p> <p><strong>Methods: </strong>Sprague Dawley rats were divided into five groups: Negative control group (rats with base gel treatment), positive control group (rats treated with triamcinolone acetonide), F1 (treatment with 20% areca nut:80% chrysanthemum), F2 (treatment with 50% areca nut:50% chrysanthemum), and F3 (treatment with 80% areca nut:20% chrysanthemum). Traumatic ulcers were performed on the buccal mucosa of all experimental animals that received topical oral gel and triamcinolone acetonide twice a day for seven days. The clinical and histological characteristics were analyzed and scored.</p> <p><strong>Results:</strong> During the six days, the ulcerated area receded linearly over time and was completely cicatrized in F2 and positive control group (Dependent t-test, p<0.05). There were a significant increase in body weight in F2 and positive control groups. There were no significant differences between groups in histology examination (Kruskal Wallis test, p<0.05). The moderate score of TNF-α levels was seen in F2 and positive control groups (ANOVA/Tukey test). Similar results were seen in the collagenases assay.</p> <p><strong>Conclusions: </strong>A balanced combination of areca nut and chrysanthemum extract in the oral gel can optimize the healing of traumatic oral ulcers in rats through the increase of TNF-α and collagen deposition.</p>
Female choice scores and Peak Frequency and Duration in calls from Wood frog chorus recordings
<p>A limitation in bioacoustic studies has been the inability to differentiate individual sonic contributions from group-level dynamics. We present a novel application of acoustic-camera technology to investigate how individual wood frogs calls influence chorus properties, and how variation influences mating opportunities. We recorded mating calls and used playback trials to gauge preference for different chorus types in the laboratory. Males and females preferred chorus playbacks with low variance in dominant frequency. Females preferred choruses with low mean peak frequency. Field studies revealed more egg masses laid in ponds where males chorused with low variance in dominant frequency. We also noted a trend towards more egg masses laid in ponds where males called with low mean frequency. Nearest neighbor distances influenced call timing (neighbors called in succession) and distances increased with variance in chorus frequency. Results highlight the potential fitness implications of individual-level contributions to a bioacoustic signal produced by groups.</p>
Model socio-cultural categories effect on aesthetic score
<p>Model socio-cultural categories effect on aesthetic score</p> <p>see https://github.com/nmouquet/RLS_AESTHE</p>
12 nuclear microsatellite loci scores for 543 adult trees of Tilia cordata in Lithuainia
<p>Genetic signature of the natural genepool of <i>Tilia cordata</i> Mill. in Lithuania: compound evolutionary and anthropogenic effects</p> <p><i>Tilia cordata</i> Mill. is a valuable tree species enriching the ecological values of the coniferous dominated boreal forests in Europe. Following the historical decline, spreading of <i>Tilia</i> sp. is challenged by the elevated inbreeding and habitat fragmentation. We studied the geographical distribution of genetic diversity of <i>Tilia cordata</i> populations in Lithuania. We used 14 genomic microsatellite markers to genotype 543 individuals from 23 wild growing populations. We found that <i>Tilia cordata</i> retained high levels of genetic diversity (population F<sub>is</sub> = 0 to 0.15, H<sub>o </sub>= 0.53 to 0.69, H<sub>e </sub>= 0.56 to 0.75). AMOVA, Bayesian clustering and Monmonier's barrier detection indicate weak but significant differentiation among the populations (F<sub>st</sub> = 0.037***) into geographically interpretable clusters of (a) western Lithuania with high genetic heterogeneity but low genetic diversity, bottleneck effects, (b) relatively higher genetic diversity of <i>Tilia cordata</i> on rich and most soils of midland lowland, and (c) the most differentiated populations on poor soils of the coolest north-eastern highland possessing the highest rare allele frequency but elevated inbreeding and bottleneck effects. Weak genetic differentiation among the <i>Tilia cordata</i> populations in Lithuania implies common ancestry, absence of strong adaptive gradients and effective genetic exchange possible mediated via the riparian networks. A hypothesis on riparian networks as geneflow mediators in <i>Tilia cordata</i> was raised based on results of this study.</p>
FIGURE 1. The best scoring RAxML tree obtained using a in A new species Pseudoplagiostoma dipterocarpicola (Pseudoplagiostomataceae, Diaporthales) found in northern Thailand on members of the Dipterocarpaceae
FIGURE 1. The best scoring RAxML tree obtained using a combined dataset of ITS, LSU, tef1-α and tub2 sequences. The tree is rooted to Togninia minima (AE F56), Togninia novae-zealandiae (CBS 110156) and Phaeoacremonium hungaricum (CBS 123036). ML and MP bootstrap values equal to or greater than 70% and BYPP equal to or greater than 0.95 are given at the nodes (ML/MP/BYPP). Ex-type strains are in black bold and the newly generated sequences are in red bold.
Scoring of 13 microsatellite loci for Tetrastigma loheri in Cebu (Philippines) based on the fragment length size of their respective alleles
<p>Little is known about the effects of habitat fragmentation on the patterns of genetic diversity and genetic connectivity of species in the remaining tropical forests of Southeast Asia. This is particularly evident in Cebu, a Philippine island that has a long history of deforestation and has lost nearly all of its forest cover. To begin filling this gap, data from 13 microsatellite loci developed for Tetrastigma loheri (Vitaceae), a common vine species in Philippine forests, were used to study patterns of genetic diversity and genetic connectivity for the four largest of the remaining forest areas in Cebu. Evidence of relatively high levels of inbreeding was found in all four areas, despite no evidence of low genetic diversity. The four areas are genetically differentiated, suggesting low genetic connectivity. The presence of inbreeding and low genetic connectivity in a commonly encountered species such as T. loheri in Cebu suggests that the impact of habitat fragmentation is likely greater on rare plant species with more restricted distributions in Cebu. Conservation recommendations for the remaining forest areas in Cebu include the establishment of steppingstone corridors between nearby areas to improve the movement of pollinators and seed dispersers among them.</p>
Incorporating family history of disease improves polygenic risk scores in diverse populations
<p>Code relevant to Hujoel et al. "Incorporating family history of disease improves polygenic risk scores in diverse populations"</p>
Comorbid-phenome prediction and phenotype risk scores enhance gene discovery for generalized anxiety disorder and posttraumatic stress disorder
<p>GWAS summary statistics. See ReadMe for column descriptions.</p>
Spatially variant immune infiltration scoring in human cancer tissues
<p>IMC raw dataset for cohort 1 and cohort 2 for the paper: "Spatially variant immune infiltration scoring in human cancer tissues"</p>
Improvements in airflow characteristics and effect on the NOSE score after septoturbinoplasty: A computational fluid dynamics analysis
<p><span>Septoturbinoplasty is a surgical procedure that can improve nasal congestion symptoms in patients with nasal septal deviation and inferior turbinate hypertrophy. However, it is unclear which physical domains of nasal airflow after septoturbinoplasty are related to symptomatic improvement. This work employs computational fluid dynamics modeling to identify the physical variables and domains associated with symptomatic improvement. Sixteen numerical models were generated using eight patients' pre- and postoperative computed tomography scans. Changes in unilateral nasal resistance, surface heat flux, relative humidity, and air temperature and their correlations with improvement in the </span><span>Nasal Obstruction Symptom Evaluation (NOSE) score were analyzed. The NOSE score significantly improved after septoturbinoplasty, from 14.4 ± 3.6 to 4.0 ± 4.2 (p < 0.001). The surgery not only increased the airflow partition </span><span>on the more obstructed side (MOS) from 31.6 ± 9.6 to 41.9 ± 4.7% (p = 0.043), but also reduced the unilateral nasal resistance in the MOS from 0.200 ± 0.095 to 0.066 ± 0.055 Pa/(mL</span><span>×</span><span>s) (p = 0.004). Improvement in the NOSE score correlated significantly with the reduction in unilateral nasal resistance in the preoperative MOS (<em>r</em>=0.81). Also, improvement in the NOSE score correlated better with the increase in surface heat flux in the preoperative MOS region from the nasal valve to the choanae (<em>r</em>=0.87) than in the vestibule area (<em>r</em>=0.63). Therefore, </span><span>unilateral nasal resistance and mucous cooling in the preoperative MOS can explain the perceived improvement in symptoms after septoturbinoplasty. Moreover, the physical domain between the nasal valve and the choanae might be more relevant to patient-reported patency than the vestibule area. </span></p>
Coronary atherosclerotic burden assessed by SYNTAX scores and outcomes in surgical, percutaneous, or medical strategies: A retrospective cohort study
<div><span><strong>Introduction</strong></span></div> <div> </div> <div> <span>Coronary atherosclerotic burden and SYNTAX score (SS) are predictors of cardiovascular events.</span> </div> <div> </div> <div><span><strong>Objectives</strong></span></div> <div> </div> <div> <span>To investigate the value of SYNTAX scores (SS, SSII and residual SS [rSS]) for predicting cardiovascular events in patients with coronary artery disease (CAD).</span> </div> <div> </div> <div><strong><span>Design</span></strong></div> <div> </div> <div> <span>Retrospective cohort study.</span> </div> <div> </div> <div><strong><span>Setting</span></strong></div> <div> </div> <div> <span>Single tertiary centre.</span> </div> <div><strong> </strong></div> <div><strong><span>Participants</span></strong></div> <div> </div> <div> <span>Medicine, Angioplasty or Surgery Study (MASS) database patients with stable multivessel CAD and preserved ejection fraction.</span> </div> <div> </div> <div> <span>Interventions</span><span> CAD patients undergoing coronary artery bypass graft (CABG), percutaneous coronary intervention (PCI), or medical treatment (MT) alone from January 2002 to December 2015.</span> </div> <div> </div> <div> <span>Primary and secondary outcomes</span><span> Primary: 5-year all-cause mortality. Secondary: composite of all-cause death, myocardial infarction, stroke, and subsequent coronary revascularization at 5 years.</span> </div> <div> </div> <div><strong><span>Results</span></strong></div> <div> </div> <div> <span>A total of 1,719 patients underwent PCI (n = 573), CABG (n = 572), or MT (n = 574) alone. </span><span>The SS was not considered an independent predictor of 5-year mortality in the PCI </span><span>(low, intermediate and high SS 6.5%, 6.8% and 4.3%, respectively, p=0.745)</span><span>, CABG </span><span>(low, intermediate and high SS 5.7%, 8.0% and 12.1%, respectively, p=0.194)</span><span> and MT </span><span>(low, intermediate and high SS 6.8%, 6.9% and 6.5%, respectively, p=0.993)</span><span> cohorts. The SSII (low, intermediate and high SSII, 3.6% vs. 7.9% vs. 10.5%, respectively, p <0.001) was associated with a higher mortality risk in the overall population. Within each treatment strategy, SSII was associated with a significant 5-year mortality rate, especially in CABG patients with higher SSII (</span><span>low, intermediate and high SSII, </span><span>1.8%, 9.7% and 10.0%, respectively, </span><span>p = 0.004) and in MT patients with high SSII (</span><span>low, intermediate and high SSII, 5.0%, 4.7% and 10.8%, respectively,</span><span> p = 0.031). </span><span>SSII demonstrated a better predictive accuracy for mortality compared with SS and rSS </span><span>(c-index = 0.62)</span><span>. </span> </div> <div> </div> <div><span><strong>Conclusions</strong></span></div> <div> </div> <div><span>Coronary atherosclerotic burden alone was not associated with significantly increased risk of all-cause mortality. The SSII better discriminates the risk of death. </span></div>
Porting DB12 to Python3: Analysis of the scores
<p><a href="https://github.com/DIRACGrid/DB12">DB12</a> has been originally conceived with Python2 to estimate the power of a given CPU to run HEP applications. However, since January 2020, Python2 is no <a href="https://www.python.org/doc/sunset-python-2/">longer maintained</a> and we decided to port the code to Python3, which contains several optimizations.</p> <p>In October 2021, we effectively ported DB12 to Python3.9, but the optimizations brought by the language generated discrepancies in the norm score, which is a critical component to evaluate the power of CPUs. We build an analysis tool to mitigate these discrepancies.</p> <p><strong>Current situation</strong></p> <p>The current analysis assess the impact of the changes on the norm score and propose 3 different solutions to resolve the issue:</p> <ul> <li>Find a constant value that would transform a python3 score into a python2 one: 1.18 seems fine. <ul> <li>Pros: simple</li> <li>Cons: not accurate. does fit well with scores computed on Intel, not so well with scores computed on AMD</li> </ul> </li> <li>Find one constant value per processor type (Intel/AMD): 1.16 fits well with scores computed on Intel, 1.4 also fits well with scores computed on AMD . <ul> <li>Pros: accurate</li> <li>Cons: need to maintain a table and update it with new types of processors, and maybe also with new versions of python</li> </ul> </li> <li>Compute a simple linear regression: <ul> <li>Pros: accurate</li> <li>Cons: need to run it with many examples to get an accurate model</li> </ul> </li> </ul> <p>To keep it simple and accurate, we chose to apply the second solution: one constant value per processor type.<br> These constants are part of the code and are located in <em>src/db12/factors.json</em>.</p> <p>These values will need to be updated through time, according to the evolution of the CPUs and Python.<br> If you need to get an accurate DB12 norm score using a Python version or a CPU that has not be taken into account,<br> then you have to run the analysis with new data following the next steps.</p> <p><strong>Run the analysis</strong></p> <p>Execute the Jupyter Notebook:</p> <pre><code class="language-bash">jupyter notebook DB12Analysis.ipynb</code></pre> <p> </p> <p><strong>Include new data using DIRAC</strong></p> <ul> <li>Install a DIRAC client:</li> </ul> <pre><code class="language-bash">lb-dirac lhcb-proxy-init</code></pre> <ul> <li>Go to <em>resources/tools</em> and submit jobs:</li> </ul> <pre><code class="language-bash">./submit.sh <number of jobs> <list of sites></code></pre> <ul> <li>Once the jobs are done, add their IDs in `jobIDs.csv` to get the results:</li> </ul> <pre><code class="language-bash">python getDB12Scores.py</code></pre> <ul> <li>You will obtain `results.json`, you can sort the file to get a better look at it with `jq`:</li> </ul> <pre><code class="language-bash">cat results.json | jq . > results_sorted_<date>.json</code></pre> <ul> <li>You can finally remove the jobs that are still pending in the queues</li> </ul>
FIGURE 1. The best-scoring RAxML tree constructed from a concatenated ITS, tef1 in Combination of morphological and molecular data support Pestalotiopsis eleutherococci (Sporocadaceae) as a new species
FIGURE 1. The best-scoring RAxML tree constructed from a concatenated ITS, tef1-α, and tub2 dataset of Pestalotiopsis species. The tree is rooted with Truncatella laurocerasi (ICMP 11214) and T. angustata (CBS 144025). The asterisk at P. jesteri indicates its ambiguous status on Index Fungorum (2022). The type delivered sequences are indicated in bold and marked with T. The new isolates are in blue. The asterisk at P. intermedia indicates a misidentification.
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.