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Supplementary material 1 from: Recuero E, Caterino MS (2023) A second species of the pill millipede genus Nearctomeris Wesener, 2012 (Diplopoda, Glomerida) from the Great Smoky Mountains, USA. ZooKeys 1166: 333-349. https://doi.org/10.3897/zookeys.1166.103516
Records of Glomeridae in the eastern United States
Fig. 8 in The integration of MS-based metabolomics and multivariate data analysis allows for improved quality assessment of Zingiber officinale Roscoe
Fig. 8. The influence of drying of ginger on the gingerols and gingerol-related metabolites.
Fig. 6 in The integration of MS-based metabolomics and multivariate data analysis allows for improved quality assessment of Zingiber officinale Roscoe
Fig. 6. The influence of geographical distribution of ginger on metabolites content.
Cascadia Core MS Logs
<p>These files accompany Appendix A of the publication "Turbidite correlation for paleoseismology" by Nieminski et al., 2023 and may be used to reproduce Figure 4 in that paper. The magnetic susceptibility logs used are all obtained from the Oregon State University Marine and Geology Repository (<a href="https://osu-mgr.org/">https://osu-mgr.org/</a>).</p>
Fig. 5. Synchronized 2D in Metabolic fingerprinting of Ganoderma spp. using UHPLC-ESI-QTOF-MS and its chemometric analysis
Fig. 5. Synchronized 2D PCA score plot of all 18 samples of Ganoderma mushroom.
Fig. 4. Synchronized 3D in Metabolic fingerprinting of Ganoderma spp. using UHPLC-ESI-QTOF-MS and its chemometric analysis
Fig. 4. Synchronized 3D PCA plot of all 18 samples of Ganoderma mushroom.
MS-BioGraphs MS200
<p><a href="https://blogs.qub.ac.uk/DIPSA/MS-BioGraphs/">https://blogs.qub.ac.uk/DIPSA/MS-BioGraphs/</a></p> <table> <tbody> <tr> <td>Name</td> <td>MS-BioGraphs – MS200</td> </tr> <tr> <td>URL</td> <td><a href="https://blogs.qub.ac.uk/DIPSA/MS-BioGraphs-MS200">https://blogs.qub.ac.uk/DIPSA/MS-BioGraphs-MS200</a></td> </tr> <tr> <td>Graph Explanation</td> <td>Vertices represent proteins and each edge represents the sequence similarity between its two endpoints</td> </tr> <tr> <td>Edge Weighted</td> <td>Yes</td> </tr> <tr> <td>Directed</td> <td>No</td> </tr> <tr> <td>Number of Vertices</td> <td>1,414,493,449</td> </tr> <tr> <td>Number of Edges</td> <td>502,930,788,612</td> </tr> <tr> <td>Maximum Degree</td> <td>745,735</td> </tr> <tr> <td>Minimum Weight</td> <td>460</td> </tr> <tr> <td>Maximum Weight</td> <td>634,925</td> </tr> <tr> <td>Number of Zero-Degree Vertices</td> <td>0</td> </tr> <tr> <td>Average Degree</td> <td>355.6</td> </tr> <tr> <td>Size of The Largest WCC</td> <td>485,867,547,569</td> </tr> <tr> <td>Number of WCC</td> <td>338,348,495</td> </tr> <tr> <td>Creation Details</td> <td><a href="https://blogs.qub.ac.uk/DIPSA/MS-BioGraphs-Sequence-Similarity-Graph-Datasets/">MS-BioGraphs: Sequency Similarity Graph Datasets</a></td> </tr> <tr> <td>Format</td> <td><a href="https://webgraph.di.unimi.it/">WebGraph</a></td> </tr> <tr> <td>License</td> <td><a href="https://creativecommons.org/licenses/by-nc-sa/2.0/">CC BY-NC-SA</a></td> </tr> <tr> <td>QUB IDF</td> <td>2223-052</td> </tr> <tr> <td>DOI</td> <td><a href="https://doi.org/10.5281/zenodo.7820812">10.5281/zenodo.7820812</a></td> </tr> <tr> <td>Citation</td> <td> <pre> Koohi Esfahani, Mohsen, Boldi, Paolo, Vandierendonck, Hans, Kilpatrick, Peter, Vigna,Sebastiano. (2023). MS-BioGraphs - MS200. https://doi.org/10.5281/zenodo.7820812. http://blogs.qub.ac.uk/DIPSA/MS-BioGraphs-MS200.</pre> </td> </tr> <tr> <td>Bibtex</td> <td> <pre> @misc{MS-BioGraphs-MS200, year = {2023}, author = {Mohsen Koohi Esfahani and Paolo Boldi and Hans Vandierendonck and Peter Kilpatrick and Sebastiano Vigna}, title = {{MS-BioGraphs - MS200}}, doi = {10.5281/zenodo.7820812}, url = {http://blogs.qub.ac.uk/DIPSA/MS-BioGraphs-MS200}, howpublished= {\url{http://blogs.qub.ac.uk/DIPSA/MS-BioGraphs-MS200}}}</pre> </td> </tr> </tbody> </table>
MS-BioGraphs MSA200
<p><a href="https://blogs.qub.ac.uk/DIPSA/MS-BioGraphs/">https://blogs.qub.ac.uk/DIPSA/MS-BioGraphs/</a></p> <table> <tbody> <tr> <td>Name</td> <td>MS-BioGraphs – MSA200</td> </tr> <tr> <td>URL</td> <td><a href="https://blogs.qub.ac.uk/DIPSA/MS-BioGraphs-MSA200">https://blogs.qub.ac.uk/DIPSA/MS-BioGraphs-MSA200</a></td> </tr> <tr> <td>Graph Explanation</td> <td>Vertices represent proteins and each edge represents the sequence similarity between its two endpoints</td> </tr> <tr> <td>Edge Weighted</td> <td>Yes</td> </tr> <tr> <td>Directed</td> <td>Yes</td> </tr> <tr> <td>Number of Vertices</td> <td>1,757,323,526</td> </tr> <tr> <td>Number of Edges</td> <td>500,444,322,597</td> </tr> <tr> <td>Maximum In-Degree</td> <td>658,879</td> </tr> <tr> <td>Maximum Out-Degree</td> <td>709,176</td> </tr> <tr> <td>Minimum Weight</td> <td>98</td> </tr> <tr> <td>Maximum Weight</td> <td>634,925</td> </tr> <tr> <td>Number of Zero In-Degree Vertices</td> <td>6,437,984</td> </tr> <tr> <td>Number of Zero Out-Degree Vertices</td> <td>7,471,315</td> </tr> <tr> <td>Average In-Degree</td> <td>285.8</td> </tr> <tr> <td>Average Out-Degree</td> <td>286.0</td> </tr> <tr> <td>Size of The Largest Weakly Connected Component</td> <td>496,880,685,957</td> </tr> <tr> <td>Number of Weakly Connected Components</td> <td>221,467,156</td> </tr> <tr> <td>Creation Details</td> <td><a href="https://blogs.qub.ac.uk/DIPSA/MS-BioGraphs-Sequence-Similarity-Graph-Datasets/">MS-BioGraphs: Sequency Similarity Graph Datasets</a></td> </tr> <tr> <td>Format</td> <td><a href="https://webgraph.di.unimi.it/">WebGraph</a></td> </tr> <tr> <td>License</td> <td><a href="https://creativecommons.org/licenses/by-nc-sa/2.0/">CC BY-NC-SA</a></td> </tr> <tr> <td>QUB IDF</td> <td>2223-052</td> </tr> <tr> <td>DOI</td> <td><a href="https://doi.org/10.5281/zenodo.7820815">10.5281/zenodo.7820815</a></td> </tr> <tr> <td>Citation</td> <td> <pre> Koohi Esfahani, Mohsen, Boldi, Paolo, Vandierendonck, Hans, Kilpatrick, Peter, Vigna,Sebastiano. (2023). MS-BioGraphs - MSA200. https://doi.org/10.5281/zenodo.7820815. http://blogs.qub.ac.uk/DIPSA/MS-BioGraphs-MSA200.</pre> </td> </tr> <tr> <td>Bibtex</td> <td> <pre> @misc{MS-BioGraphs-MSA200, year = {2023}, author = {Mohsen Koohi Esfahani and Paolo Boldi and Hans Vandierendonck and Peter Kilpatrick and Sebastiano Vigna}, title = {{MS-BioGraphs - MSA200}}, doi = {10.5281/zenodo.7820815}, url = {http://blogs.qub.ac.uk/DIPSA/MS-BioGraphs-MSA200}, howpublished= {\url{http://blogs.qub.ac.uk/DIPSA/MS-BioGraphs-MSA200}}}</pre> </td> </tr> </tbody> </table>
MS-BioGraphs MSA50
<p><a href="https://blogs.qub.ac.uk/DIPSA/MS-BioGraphs/">https://blogs.qub.ac.uk/DIPSA/MS-BioGraphs/</a></p> <table> <tbody> <tr> <td>Name</td> <td>MS-BioGraphs – MSA50</td> </tr> <tr> <td>URL</td> <td><a href="https://blogs.qub.ac.uk/DIPSA/MS-BioGraphs-MSA50">https://blogs.qub.ac.uk/DIPSA/MS-BioGraphs-MSA50</a></td> </tr> <tr> <td>Graph Explanation</td> <td>Vertices represent proteins and each edge represents the sequence similarity between its two endpoints</td> </tr> <tr> <td>Edge Weighted</td> <td>Yes</td> </tr> <tr> <td>Directed</td> <td>Yes</td> </tr> <tr> <td>Number of Vertices</td> <td>1,757,323,526</td> </tr> <tr> <td>Number of Edges</td> <td>125,312,536,732</td> </tr> <tr> <td>Maximum In-Degree</td> <td>543,117</td> </tr> <tr> <td>Maximum Out-Degree</td> <td>297,981</td> </tr> <tr> <td>Minimum Weight</td> <td>98</td> </tr> <tr> <td>Maximum Weight</td> <td>634,925</td> </tr> <tr> <td>Number of Zero In-Degree Vertices</td> <td>6,437,984</td> </tr> <tr> <td>Number of Zero Out-Degree Vertices</td> <td>8,542,018</td> </tr> <tr> <td>Average In-Degree</td> <td>71.6</td> </tr> <tr> <td>Average Out-Degree</td> <td>71.7</td> </tr> <tr> <td>Size of The Largest Weakly Connected Component</td> <td>117,980,151,055</td> </tr> <tr> <td>Number of Weakly Connected Components</td> <td>363,090,851</td> </tr> <tr> <td>Creation Details</td> <td><a href="https://blogs.qub.ac.uk/DIPSA/MS-BioGraphs-Sequence-Similarity-Graph-Datasets/">MS-BioGraphs: Sequency Similarity Graph Datasets</a></td> </tr> <tr> <td>Format</td> <td><a href="https://webgraph.di.unimi.it/">WebGraph</a></td> </tr> <tr> <td>License</td> <td><a href="https://creativecommons.org/licenses/by-nc-sa/2.0/">CC BY-NC-SA</a></td> </tr> <tr> <td>QUB IDF</td> <td>2223-052</td> </tr> <tr> <td>DOI</td> <td><a href="https://doi.org/10.5281/zenodo.7820821">10.5281/zenodo.7820821</a></td> </tr> <tr> <td>Citation</td> <td> <pre> Koohi Esfahani, Mohsen, Boldi, Paolo, Vandierendonck, Hans, Kilpatrick, Peter, Vigna,Sebastiano. (2023). MS-BioGraphs - MSA50. https://doi.org/10.5281/zenodo.7820821. http://blogs.qub.ac.uk/DIPSA/MS-BioGraphs-MSA50.</pre> </td> </tr> <tr> <td>Bibtex</td> <td> <pre> @misc{MS-BioGraphs-MSA50, year = {2023}, author = {Mohsen Koohi Esfahani and Paolo Boldi and Hans Vandierendonck and Peter Kilpatrick and Sebastiano Vigna}, title = {{MS-BioGraphs - MSA50}}, doi = {10.5281/zenodo.7820821}, url = {http://blogs.qub.ac.uk/DIPSA/MS-BioGraphs-MSA50}, howpublished= {\url{http://blogs.qub.ac.uk/DIPSA/MS-BioGraphs-MSA50}}}</pre> </td> </tr> </tbody> </table>
MS-BioGraphs MSA10
<p><a href="https://blogs.qub.ac.uk/DIPSA/MS-BioGraphs/">https://blogs.qub.ac.uk/DIPSA/MS-BioGraphs/</a></p> <table> <tbody> <tr> <td>Name</td> <td>MS-BioGraphs – MSA10</td> </tr> <tr> <td>URL</td> <td><a href="https://blogs.qub.ac.uk/DIPSA/MS-BioGraphs-MSA10">https://blogs.qub.ac.uk/DIPSA/MS-BioGraphs-MSA10</a></td> </tr> <tr> <td>Graph Explanation</td> <td>Vertices represent proteins and each edge represents the sequence similarity between its two endpoints</td> </tr> <tr> <td>Edge Weighted</td> <td>Yes</td> </tr> <tr> <td>Directed</td> <td>Yes</td> </tr> <tr> <td>Number of Vertices</td> <td>1,757,323,526</td> </tr> <tr> <td>Number of Edges</td> <td>25,236,632,682</td> </tr> <tr> <td>Maximum In-Degree</td> <td>207,279</td> </tr> <tr> <td>Maximum Out-Degree</td> <td>62,060</td> </tr> <tr> <td>Minimum Weight</td> <td>98</td> </tr> <tr> <td>Maximum Weight</td> <td>634,925</td> </tr> <tr> <td>Number of Zero In-Degree Vertices</td> <td>6,437,984</td> </tr> <tr> <td>Number of Zero Out-Degree Vertices</td> <td>9,926,249</td> </tr> <tr> <td>Average In-Degree</td> <td>14.4</td> </tr> <tr> <td>Average Out-Degree</td> <td>14.4</td> </tr> <tr> <td>Size of The Largest Weakly Connected Component</td> <td>15,576,385,764</td> </tr> <tr> <td>Number of Weakly Connected Components</td> <td>628,505,933</td> </tr> <tr> <td>Creation Details</td> <td><a href="https://blogs.qub.ac.uk/DIPSA/MS-BioGraphs-Sequence-Similarity-Graph-Datasets/">MS-BioGraphs: Sequency Similarity Graph Datasets</a></td> </tr> <tr> <td>Format</td> <td><a href="https://webgraph.di.unimi.it/">WebGraph</a></td> </tr> <tr> <td>License</td> <td><a href="https://creativecommons.org/licenses/by-nc-sa/2.0/">CC BY-NC-SA</a></td> </tr> <tr> <td>QUB IDF</td> <td>2223-052</td> </tr> <tr> <td>DOI</td> <td><a href="https://doi.org/10.5281/zenodo.7820823">10.5281/zenodo.7820823</a></td> </tr> <tr> <td>Citation</td> <td> <pre> Koohi Esfahani, Mohsen, Boldi, Paolo, Vandierendonck, Hans, Kilpatrick, Peter, Vigna,Sebastiano. (2023). MS-BioGraphs - MSA10. https://doi.org/10.5281/zenodo.7820823. http://blogs.qub.ac.uk/DIPSA/MS-BioGraphs-MSA10.</pre> </td> </tr> <tr> <td>Bibtex</td> <td> <pre> @misc{MS-BioGraphs-MSA10, year = {2023}, author = {Mohsen Koohi Esfahani and Paolo Boldi and Hans Vandierendonck and Peter Kilpatrick and Sebastiano Vigna}, title = {{MS-BioGraphs - MSA10}}, doi = {10.5281/zenodo.7820823}, url = {http://blogs.qub.ac.uk/DIPSA/MS-BioGraphs-MSA10}, howpublished= {\url{http://blogs.qub.ac.uk/DIPSA/MS-BioGraphs-MSA10}}}</pre> </td> </tr> <tr> <td> </td> <td> </td> </tr> </tbody> </table>
MS-BioGraphs MS50
<p><a href="https://blogs.qub.ac.uk/DIPSA/MS-BioGraphs/">https://blogs.qub.ac.uk/DIPSA/MS-BioGraphs/</a></p> <table> <tbody> <tr> <td>Name</td> <td>MS-BioGraphs – MS50</td> </tr> <tr> <td>URL</td> <td><a href="https://blogs.qub.ac.uk/DIPSA/MS-BioGraphs-MS50">https://blogs.qub.ac.uk/DIPSA/MS-BioGraphs-MS50</a></td> </tr> <tr> <td>Graph Explanation</td> <td>Vertices represent proteins and each edge represents the sequence similarity between its two endpoints</td> </tr> <tr> <td>Edge Weighted</td> <td>Yes</td> </tr> <tr> <td>Directed</td> <td>No</td> </tr> <tr> <td>Number of Vertices</td> <td>585,603,088</td> </tr> <tr> <td>Number of Edges</td> <td>124,783,559,600</td> </tr> <tr> <td>Maximum Degree</td> <td>507,826</td> </tr> <tr> <td>Minimum Weight</td> <td>900</td> </tr> <tr> <td>Maximum Weight</td> <td>634,925</td> </tr> <tr> <td>Number of Zero-Degree Vertices</td> <td>0</td> </tr> <tr> <td>Average Degree</td> <td>213.1</td> </tr> <tr> <td>Size of The Largest WCC</td> <td>102,256,631,195</td> </tr> <tr> <td>Number of WCC</td> <td>155,295,301</td> </tr> <tr> <td>Creation Details</td> <td><a href="https://blogs.qub.ac.uk/DIPSA/MS-BioGraphs-Sequence-Similarity-Graph-Datasets/">MS-BioGraphs: Sequency Similarity Graph Datasets</a></td> </tr> <tr> <td>Format</td> <td><a href="https://webgraph.di.unimi.it/">WebGraph</a></td> </tr> <tr> <td>License</td> <td><a href="https://creativecommons.org/licenses/by-nc-sa/2.0/">CC BY-NC-SA</a></td> </tr> <tr> <td>QUB IDF</td> <td>2223-052</td> </tr> <tr> <td>DOI</td> <td><a href="https://doi.org/10.5281/zenodo.7820819">10.5281/zenodo.7820819</a></td> </tr> <tr> <td>Citation</td> <td> <pre> Koohi Esfahani, Mohsen, Boldi, Paolo, Vandierendonck, Hans, Kilpatrick, Peter, Vigna,Sebastiano. (2023). MS-BioGraphs - MS50. https://doi.org/10.5281/zenodo.7820819. http://blogs.qub.ac.uk/DIPSA/MS-BioGraphs-MS50.</pre> </td> </tr> <tr> <td>Bibtex</td> <td> <pre> @misc{MS-BioGraphs-MS50, year = {2023}, author = {Mohsen Koohi Esfahani and Paolo Boldi and Hans Vandierendonck and Peter Kilpatrick and Sebastiano Vigna}, title = {{MS-BioGraphs - MS50}}, doi = {10.5281/zenodo.7820819}, url = {http://blogs.qub.ac.uk/DIPSA/MS-BioGraphs-MS50}, howpublished= {\url{http://blogs.qub.ac.uk/DIPSA/MS-BioGraphs-MS50}}}</pre> </td> </tr> </tbody> </table>
MS-BioGraphs MSA500
<p><a href="https://blogs.qub.ac.uk/DIPSA/MS-BioGraphs/">https://blogs.qub.ac.uk/DIPSA/MS-BioGraphs/</a></p> <table> <tbody> <tr> <td>Name</td> <td>MS-BioGraphs – MSA500</td> </tr> <tr> <td>URL</td> <td><a href="https://blogs.qub.ac.uk/DIPSA/MS-BioGraphs-MSA500">https://blogs.qub.ac.uk/DIPSA/MS-BioGraphs-MSA500</a></td> </tr> <tr> <td>Graph Explanation</td> <td>Vertices represent proteins and each edge represents the sequence similarity between its two endpoints</td> </tr> <tr> <td>Edge Weighted</td> <td>Yes</td> </tr> <tr> <td>Directed</td> <td>Yes</td> </tr> <tr> <td>Number of Vertices</td> <td>1,757,323,526</td> </tr> <tr> <td>Number of Edges</td> <td>1,244,904,754,157</td> </tr> <tr> <td>Maximum In-Degree</td> <td>229,442</td> </tr> <tr> <td>Maximum Out-Degree</td> <td>814,461</td> </tr> <tr> <td>Minimum Weight</td> <td>98</td> </tr> <tr> <td>Maximum Weight</td> <td>634,925</td> </tr> <tr> <td>Number of Zero In-Degree Vertices</td> <td>6,437,984</td> </tr> <tr> <td>Number of Zero Out-Degree Vertices</td> <td>16,843,087</td> </tr> <tr> <td>Average In-Degree</td> <td>711.0</td> </tr> <tr> <td>Average Out-Degree</td> <td>715.3</td> </tr> <tr> <td>Size of The Largest Weakly Connected Component</td> <td>1,244,203,865,823</td> </tr> <tr> <td>Number of Weakly Connected Components</td> <td>148,861,367</td> </tr> <tr> <td>Creation Details</td> <td><a href="https://blogs.qub.ac.uk/DIPSA/MS-BioGraphs-Sequence-Similarity-Graph-Datasets/">MS-BioGraphs: Sequency Similarity Graph Datasets</a></td> </tr> <tr> <td>Format</td> <td><a href="https://webgraph.di.unimi.it/">WebGraph</a></td> </tr> <tr> <td>License</td> <td><a href="https://creativecommons.org/licenses/by-nc-sa/2.0/">CC BY-NC-SA</a></td> </tr> <tr> <td>QUB IDF</td> <td>2223-052</td> </tr> <tr> <td>DOI</td> <td><a href="https://doi.org/10.5281/zenodo.7820810">10.5281/zenodo.7820810</a></td> </tr> <tr> <td>Citation</td> <td> <pre> Koohi Esfahani, Mohsen, Boldi, Paolo, Vandierendonck, Hans, Kilpatrick, Peter, Vigna,Sebastiano. (2023). MS-BioGraphs - MSA500. https://doi.org/10.5281/zenodo.7820810. http://blogs.qub.ac.uk/DIPSA/MS-BioGraphs-MSA500.</pre> </td> </tr> <tr> <td>Bibtex</td> <td> <pre> @misc{MS-BioGraphs-MSA500, year = {2023}, author = {Mohsen Koohi Esfahani and Paolo Boldi and Hans Vandierendonck and Peter Kilpatrick and Sebastiano Vigna}, title = {{MS-BioGraphs - MSA500}}, doi = {10.5281/zenodo.7820810}, url = {http://blogs.qub.ac.uk/DIPSA/MS-BioGraphs-MSA500}, howpublished= {\url{http://blogs.qub.ac.uk/DIPSA/MS-BioGraphs-MSA500}}}</pre> </td> </tr> </tbody> </table>
Fig. 4 in Chemotaxonomic investigation of Apocynaceae for retronecine-type pyrrolizidine alkaloids using HPLC-MS/MS
Fig. 4. Fragmentation patterns according to esterification pattern in retronecine-type PAs.
Fig. 1 in Chemotaxonomic investigation of Apocynaceae for retronecine-type pyrrolizidine alkaloids using HPLC-MS/MS
Fig. 1. Varied necine base structures found in pyrrolizidine alkaloids.
Fig. 3 in Chemotaxonomic investigation of Apocynaceae for retronecine-type pyrrolizidine alkaloids using HPLC-MS/MS
Fig. 3. Subtypes of lycopsamine-type PAs containing a retronecine core.
Fig. 5 in Alkaloids from Lepidium meyenii (Maca), structural revision of macaridine and UPLC-MS/MS feature-based molecular networking
Fig. 5. Results of three channel MRM scans using UPLC conditions for the TQD system.
Fig. 1 in Alkaloids from Lepidium meyenii (Maca), structural revision of macaridine and UPLC-MS/MS feature-based molecular networking
Fig. 1. Structure of isolated imidazole, amidine and β-carboline alkaloids.
Fig. 3 in Alkaloids from Lepidium meyenii (Maca), structural revision of macaridine and UPLC-MS/MS feature-based molecular networking
Fig. 3. Structures of the proposed 'macaridine' (left) and macapyrrolin C (right).
Fig. 2. Key COSY and HMBC correlations observed for lepidiline E in Alkaloids from Lepidium meyenii (Maca), structural revision of macaridine and UPLC-MS/MS feature-based molecular networking
Fig. 2. Key COSY and HMBC correlations observed for lepidiline E (1) F (2) and G (3).
Supplementary material 1 from: Thaung R, Frechette J, Luskin MS, Amir Z (2023) Combining Camera Trap Data and Environmental Data to Estimate the Effects of Environmental Gradients on Abundance of the Asian Elephant Elephas maximus in Cambodia. Biodiversity Information Science and Standards 7: e112100. https://doi.org/10.3897/biss.7.112100
Environmental Variables Used in the study
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.