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.
1,123
datasets available to search
ShareScore release 0.7.1
Dataset results
1,123 results for “Cis”
The OY-Cis dataset for cis-31P21H2
<p>The dataset is an archive of ExoMol page, https://exomol.com/data/molecules/cis-P2H2/cis-31P2-1H2/OY-Cis.<br>Please check the reference details according to the following description or directly from the website.<br> <strong>NB: The html description skips data which are not included in the current version for the purpose of simplicity. Please check cis-P2H2_cis-31P21H2_OY-Cis.md for detailed information.</strong> <br></p> <strong>Definitions file</strong> <blockquote> <p><strong>cis-31P2-1H2__OY-Cis.def</strong>[8.25 KB]<br></p> <p><strong>References:</strong><br> 1. Tennyson, J., Yurchenko, S. N., Al-Refaie, A. F., Clark, V. H. J., Chubb, K. L., Conway, E. K., Dewan, A., Gorman, M. N., Hill, C., Lynas-Gray, A. E., Mellor, T., McKemmish, L. K., Owens, A., Polyansky, O. L., Semenov, M., Somogyi, W., Tinetti, G., Upadhyay, A., Waldmann, I., Wang, Y., Wright, S., Yurchenko, O. P., "The 2020 release of the ExoMol database: molecular line lists for exoplanet and other hot atmospheres", J. Quant. Spectrosc. Rad. Transf., 255, 107228 (2020). [<a href="https://doi.org/10.1016/j.jqsrt.2020.107228">https://doi.org/10.1016/j.jqsrt.2020.107228</a>]</p> </blockquote> <strong>Spectroscopic Model</strong> <blockquote> <p><a href="https://exomol.com/models/cis-P2H2/cis-31P2-1H2/OY-Cis/">https://exomol.com/models/cis-P2H2/cis-31P2-1H2/OY-Cis/</a><br></p> </blockquote> <strong>OY-Cis: line list</strong> <p><strong>NB: These data are not included in the current version on Zenodo because the data are over Zenodo upload cap, 50GB</strong><br> <strong>Data can be accessed via:</strong> https://exomol.com/data/molecules/cis-P2H2/cis-31P2-1H2/OY-Cis<br></p> <blockquote> <p><strong>References:</strong><br> 1. Owens, A., Yurchenko, S. N., "Theoretical rotation-vibration spectroscopy of cis- and trans-diphosphene (P2H2) and the deuterated species P2HD", Journal of Chemical Physics 150, 194308/1-9 (2019). <a href="[https://doi.org/10.1063/1.5092767]">[https://doi.org/10.1063/1.5092767]</a>[19OwYuxx.P2H2]<br></p> </blockquote> <strong>OY-Cis: partition function</strong> <p><em>OY-Cis ro-vibrational line list for cis-P2H2</em><br></p> <blockquote> <p><strong>cis-31P2-1H2__OY-Cis.pf</strong>[24.41 KB]<br>Partition function produced using the Cis-(31P)2(1H)2 line list.</p> <p><strong>References:</strong><br> 1. Owens, A., Yurchenko, S. N., "Theoretical rotation-vibration spectroscopy of cis- and trans-diphosphene (P2H2) and the deuterated species P2HD", Journal of Chemical Physics 150, 194308/1-9 (2019). <a href="[https://doi.org/10.1063/1.5092767]">[https://doi.org/10.1063/1.5092767]</a>[19OwYuxx.P2H2]<br></p> </blockquote> <strong>OY-Cis: opacity</strong> <p><em>OY-Cis ro-vibrational line list for cis-P2H2</em><br></p> <blockquote> <p><strong>cis-31P2-1H2__OY-Cis.R1000_0.3-50mu.ktable.ARCiS.fits.gz</strong>[295.65 MB]<br>ARCiS k-tables at R= 1000 (0.3-50mu) in fits format (gzipped): OY-Cis (31P)2(1H)2 line list.</p> <p><strong>cis-31P2-1H2__OY-Cis.R1000_0.3-50mu.ktable.NEMESIS.kta</strong>[232.01 MB]<br>NEMESIS k-tables at R= 1000 (0.3-50mu) in NEMESIS-kta format: OY-Cis (31P)2(1H)2 line list.</p> <p><strong>cis-31P2-1H2__OY-Cis.R15000_0.3-50mu.xsec.TauREx.h5</strong>[348.39 MB]<br>TauREx k-tables at R= 15000 (0.3-50mu) in HDF5 format: OY-Cis (31P)2(1H)2 line list.</p> <p><strong>cis-31P2-1H2__OY-Cis.R1000_0.3-50mu.ktable.petitRADTRANS.h5</strong>[370.98 MB]<br>petitRADTRANS k-tables at R= 1000 (0.3-50mu) in HDF5 format: OY-Cis (31P)2(1H)2 line list.</p> <p><strong>References:</strong><br> 1. Owens, A., Yurchenko, S. N., "Theoretical rotation-vibration spectroscopy of cis- and trans-diphosphene (P2H2) and the deuterated species P2HD", Journal of Chemical Physics 150, 194308/1-9 (2019). <a href="[https://doi.org/10.1063/1.5092767]">[https://doi.org/10.1063/1.5092767]</a>[19OwYuxx.P2H2]<br> 2. Chubb, K. L., Rocchetto, M., Yurchenko, S. N., Min, M., Waldmann, I., Barstow, J. K., Molliere, P., Al-Refaie, A. F, Phillips, M. W., Tennyson, J., "The ExoMolOP database: Cross sections and k-tables for molecules of interest in high-temperature exoplanet atmospheres", Astronomy and Astrophysics 646, A21 (2020). <a href="[http://dx.doi.org/10.1051/0004-6361/202038350]">[http://dx.doi.org/10.1051/0004-6361/202038350]</a>[20ChRoYu.]<br></p> </blockquote>
Dataset of "Sensitivity analysis in photodynamics: How the electronic structure controls cis-stilbene photodynamics?"
<p>The techniques of computational photodynamics are increasingly employed to unravel reaction mechanisms and interpret experiments. However, inaccuracies in nonadiabatic dynamics can lead to misinterpretations, particularly when calculated observables exhibit low sensitivity to the underlying dynamics. This issue is exemplified in the photochemistry of cis-stilbene, where similar experimental outcomes have been differently interpreted based on the electronic structures supporting nonadiabatic dynamics. This study examines the predictions of cis-stilbene photochemistry using trajectory surface hopping methods coupled with various electronic structures (OM3-MRCISD, SA2-CASSCF, XMS-SA2-CASPT2, and XMS-SA3-CASPT2) and assesses their ability to interpret experimental observations. Although the excited-state lifetimes show consistency, ranging from 360 fs to 295 fs, the reaction quantum yields vary significantly. The quantum yield for cyclization ranges from nearly zero to 35% while the photoisomerization channel can either exceed 50% or be entirely suppressed completely in the second case. Intriguingly, the calculated photoelectron signal is not strikingly different for different reaction scenarios, making the methods seemingly reliable when treated separately Furthermore, analyzing stationary points on the potential energy surface does not reliably predict simulation outcomes, nor does it aid in selecting a specific method before simulations. Therefore, we advocate for incorporating sensitivity analyses in the simulation protocol. While employing an ensemble of methods is impractical, nonadiabatic simulations with external bias present a resource-efficient approach to achieve this goal.</p>
G-quadruplexes as pivotal components of cis-regulatory elements in the human genome
<p>This repository stores the scripts for analyzing the relationship between G-quadruplexes (G4s) and <em>cis</em>-regulatory elements (CREs), as well as the data generated directly from the manuscript.</p> <p>Manuscript: <a href="https://doi.org/10.1186/s12915-024-01971-5" target="_blank" rel="noopener">G-quadruplexes as pivotal components of <em>cis</em>-regulatory elements in the human genome</a></p> <p>G4Hunter_w25_s1.5_hg38.txt: All potential G-quadruplexes in the human genome predicted by the G4Hunter software. </p> <ul> <li>Genome assembly: hg38.</li> <li>G4Hunter software parameters were set as follows: score threshold 1.5, window size 25.</li> </ul> <p>G4_cCRE_annotation.txt: Annotation file indicating the presence of G4s in cCREs (candidate CREs; from <a title="SCREEN database" href="https://screen.encodeproject.org/" target="_blank" rel="noopener">SCREEN database</a>).</p> <p>scripts.zip: Source code used for data analysis in this project, based on the R language.</p>
Fine-mapped summary statistics for protein coding regions (i.e. cis regions) based on the Olink Explore 1536 and Explore Expansion technologies
<p>This data set contains fine-mapping results performed by SuSie for cis regions ±500kb around the protein coding gene) for protein targets as measured by the Olink Explore 1536 and Explore Expansion technologies in 1,180 individuals from EPIC Norfolk study (https://www.epic-norfolk.org.uk/). Only protein targets where fine-mapping predicted at least one credible set were included in the results. </p>
Hydro-meteorological database for watersheds across the CIS
<p>The presented database is a set of hydrological, meteorological, environmental and geometric values for Russia Federation for the period from 2008 to 2020.</p> <p><strong>Database consist of next items:</strong></p> <ul> <li>Point geometry for hydrological observation stations from Roshydromet network across Russia</li> <li>Geometry of the catchment for correspond observation station point</li> <li>Daily hydrological values <ul> <li>Water level <ul> <li>In relative representation (sm)</li> <li>In meters of Baltic system (m)</li> </ul> </li> <li>Water discharge <ul> <li>as an observed value (qms/s)</li> <li>as a layer (mm/day)</li> </ul> </li> </ul> </li> <li>Daily meteorological values <ul> <li>Maximum and minimum daily temperatures (°C) from <a href="https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=form">ERA5</a> and <a href="https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-land?tab=form">ERA5-Land</a></li> <li>Total precipitation (mm/day) from <a href="https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=form">ERA5</a>, <a href="https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-land?tab=form">ERA5-Land</a>, <a href="https://disc.gsfc.nasa.gov/datasets/GPM_3IMERGDF_06/summary">IMERG v06</a>, <a href="https://10.5067/MEASURES/GPCP/DATA305">GPCP v3.2</a> and <a href="https://www.gloh2o.org/mswep/">MSWEP</a></li> <li>Different kind of evaporation (mm/day) corresponded to each variable calculated in <a href="https://www.gleam.eu/">GLEAM</a> model</li> </ul> </li> <li>Set of hydro-environmental characteristics derived from <a href="https://www.hydrosheds.org/hydroatlas">HydroATLAS</a> database</li> </ul> <p>Each variable derived from the grid data was calculated for each watershed, taking into account the intersection weights of the watershed contour geometry and grid cells.</p> <p>Coordinates of hydrological stations were obtained from resource of Federal Agency for Water Resources of Russia Federation—<a href="https://gmvo.skniivh.ru/index.php?id=505">AIS GMVO</a></p> <p>To calculate the contours of the catchment areas, a script was developed that builds the contours in accordance with the rasters of flow directions from <a href="http://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_Hydro/">MERIT Hydro</a>. To assess the quality of the contour construction, the obtained value of the catchment area was compared with the archival value from the corresponded table from AIS GMVO. The average error in determining the area for 2080 catchments is approximately 2%</p> <p>To derive values for different hydro-environmental values from HydroATLAS were developed approach which calculate aggregated values for catchment, leaning on type of variable: qualitative (Land cover classes, Lithological classes etc.) Or quantitive (Air temperature, Snow cover extent etc.). Every quantitive variable were calculated as mode value for intersected sub-basins and target catchment, e.g. most popular attribute from sub-basins will describe whole catchment which are they relating. Quantitative values were calculated as mean value of attribute from each sub-basin. More detail could be found in <a href="http://ceur-ws.org/Vol-2930/paper13.pdf">publication</a>.</p> <p><strong>Files are distributed as follows:</strong></p> <p>Each file has some connection with the unique identifier of the hydrological observation post. Files in netcdf format (hydrological and meteorological series) are named in response to identifier.</p> <p>Every file which describe geometry (point, polygon, static attributes) has and column named gauge_id with same correspondence.</p> <ul> <li>attributes/static_data.csv – results from HydroATLAS aggregation</li> <li>geometry/russia_gauges.gpkg – coordinates of hydrological observation stations <ul> <li> <table> <thead> <tr> <th> </th> <th>gauge_id</th> <th>name_ru</th> <th>name_en</th> <th>geometry</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>49001</td> <td>р. Ковда – пос. Софпорог</td> <td>r.Kovda - pos. Sofporog</td> <td>POINT (31.41892 65.79876)</td> </tr> <tr> <th>1</th> <td>49014</td> <td>р. Корпи-Йоки – пос. Пяозерский</td> <td>r.Korpi-Joki - pos. Pjaozerskij</td> <td>POINT (31.05794 65.77917)</td> </tr> <tr> <th>2</th> <td>49017</td> <td>р. Тумча – пос. Алакуртти</td> <td>r.Tumcha - pos. Alakurtti</td> <td>POINT (30.33082 66.95957)</td> </tr> </tbody> </table> </li> </ul> </li> <li>geometry/russia_ws.gpkg – catchments polygon for each hydrological observation stations <ul> <li> <table> <thead> <tr> <th> </th> <th>gauge_id</th> <th>name_ru</th> <th>name_en</th> <th>new_area</th> <th>ais_dif</th> <th>geometry</th> </tr> </thead> <tbody> <tr> <th>0</th> <td>9002</td> <td>р. Енисей – г. Кызыл</td> <td>r.Enisej - g.Kyzyl</td> <td>115263.989</td> <td>0.230</td> <td>POLYGON ((96.87792 53.72792, 96.87792 53.72708...</td> </tr> <tr> <th>1</th> <td>9022</td> <td>р. Енисей – пос. Никитино</td> <td>r.Enisej - pos. Nikitino</td> <td>184499.118</td> <td>1.373</td> <td>POLYGON ((96.87792 53.72708, 96.88042 53.72708...</td> </tr> <tr> <th>2</th> <td>9053</td> <td>р. Енисей – пос. Базаиха</td> <td>r.Enisej - pos.Bazaiha</td> <td>302690.417</td> <td>0.897</td> <td>POLYGON ((92.38292 56.11042, 92.38292 56.10958...</td> </tr> </tbody> </table> </li> <li>Column ais_diff is corresponded to % error in area definition</li> </ul> </li> <li>nc_all_q <ul> <li>netcdf files for hydrological observation stations which has no missing values on <em>discharge</em> for 2008-2020 period</li> </ul> </li> <li>nc_all_h <ul> <li>netcdf files for hydrological observation stations which has no missing values on <em>level</em> for 2008-2020 period</li> </ul> </li> <li>nc_all_q_h <ul> <li>netcdf files for hydrological observation stations which has no missing values on <em>discharge and level</em> for 2008-2020 period</li> </ul> </li> <li>nc_concat <ul> <li>data for all available geometry provided in dataset</li> </ul> </li> </ul> <p>More details on processing scripts which were used for development of this database can be found in <a href="https://github.com/dmbrmv/my_dissertation/tree/main/data_builders">folder</a> of GitHub repository where I store results for my PhD dissertation</p> <p><strong>05.04.2023 – Significant data changes</strong>. Removed catchments and related files that have more than ±15% absolute error in calculated area relative to AIS GMVO information. Now these are data for 1886 catchments across the Russia.</p> <p> </p> <p><strong>17.05.2023 – Significant data changes</strong>. Major review of parsing algorithm for AIS GMVO data. Fixed the way of how 0.0xx values were read. Use previous versions with caution.</p> <p><strong>11.10.2023 – Significant data changes</strong>. Added 278 catchments for CIS region from GRDC resource. Calculate meteorological and environmental attributes for each catchment. New folder <em>/nc_all_q_h </em>with no missing observations on discharge and level. Now these are data for 2164 catchments across CIS.</p>
CIS OCR Workshop v1.0: OCR and postcorrection of early printings for digital humanities
<p>The 2-day CIS OCR Workshop on "OCR and postcorrection of early printings for digital humanities" originally held at LMU, Munich 14/15 September 2015 (see http://www.cis.lmu.de/ocrworkshop).</p> <p>Release date: 2016-02-25</p> <p><br /> CIS OCR Workshop by Uwe Springmann, Florian Fink is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.</p>
Data from: Deep mutational scanning of HBV reveals a mechanism for cis preferential reverse transcription
<p>Hepatitis B virus (HBV) is a small double-stranded DNA virus that chronically infects 296 million people. Over half of its compact genome encodes protein in two overlapping reading frames, and during evolution, multiple selective pressures can act on shared nucleotides. This study combines an RNA-based HBV cell culture system with deep mutational scanning to uncouple <em>cis-</em> and <em>trans</em>-acting sequence requirements in the HBV genome. The results support a leaky ribosome scanning model for polymerase translation, provide a fitness map of the HBV polymerase at single nucleotide resolution, and identify conserved prolines adjacent to the HBV polymerase termination codon that stall ribosomes. Further experiments indicated that stalled ribosomes tether the nascent polymerase to its template RNA, ensuring <em>cis</em>-preferential RNA packaging and reverse transcription of the HBV genome.</p>
LD reference panel for UKB-PPP cis-pQTL
<p>NEWLOC_protein.txt includes information for 2954 cis-pQTL regions.</p> <p>Each row name in the file follows the format:</p> <p>[GeneSymbol].[GeneSymbol]_[UniProtID]_[OlinkID]_v[Version]_[PanelName]_[Number].[Chromosome]:[StartPosition]-[EndPosition];</p> <p>For example, "A1BG.A1BG_P04217_OID30771_v1_Inflammation_II_2.19:57856549-59864858"<br><br></p> <p>In the "LD.path", it includes LD files, eigenvectors, and eigen matrixes for all local regions, end by "_LDSVD.rda"</p> <p>In the "bim.path", it includes bim files for local regions, which helps to clean the summary statistics data and check if there are multiallelic or duplicated SNPs</p> <p><br><strong><br></strong></p>
[Demo Input Data] for SCAFE: a software suite for analysis of transcribed cis-regulatory elements in single cells
<p>This archive (input.tar.gz) contains the demo data for SCAFE v1.0.0 (on <a href="https://doi.org/10.5281/zenodo.7023163">Zenodo</a> or <a href="https://github.com/chung-lab/SCAFE/releases/tag/v1.0.0">Github</a>)</p> <p><em>SCAFE</em> (Single Cell Analysis of Five-prime Ends) provides an end-to-end solution for processing of single cell 5’end RNA-seq data. It takes a read alignment file (*.bam) from single-cell RNA-5’end-sequencing (e.g. 10xGenomics Chromimum®), precisely maps the cDNA 5'ends (i.e. transcription start sites, TSS), filters for the artefacts and identifies genuine TSS clusters using logistic regression. Based on the TSS clusters, it defines transcribed cis-regulatory elements (tCRE) and annotated them to gene models. It then counts the UMI in tCRE in single cells and returns a tCRE UMI/cellbarcode matrix ready for downstream analyses, e.g. cell-type clustering, linking promoters to enhancers by co-activity <em>etc</em>.</p> <p>For details on installation, usage and test run on demo data, visit <a href="https://github.com/chung-lab/SCAFE">https://github.com/chung-lab/SCAFE</a></p>
Fig. 3. Microdrile oligochaete PIN 5640 in A probable oligochaete from an Early Triassic Lagerstätte of the southern Cis-Urals and its evolutionary implications
Fig. 3. Microdrile oligochaete PIN 5640/212 (A) from the Petropavlovka Formation, Olenekian (Lower Triassic), Petropavlovka III section, Russia and extant Tubifex tubifex (Müller, 1774) (B) from the Khripan' River, Moscow region, Russia, SEM. A. Anterior part with possible prostomium (arrowed) A1). Posterior part of specimen with W-shaped depression (arrowed) and possible genital region (A2). B. Anterior part showing prostomium (arrowed) and arrangement of chaetae (B1). Genital region depicting male pores (arrowed) (B2).
Fig. 1. A in A probable oligochaete from an Early Triassic Lagerstätte of the southern Cis-Urals and its evolutionary implications
Fig. 1. A. Map showing the Lower Triassic locality Petropavlovka III (asterisk) on the Sakmara River valley bank near the village of Petropavlovka ca. 45 km north-east of the town of Orenburg, Russia, in the tectonic context (dashed lines, boundaries of tectonic regions; modified from Minikh and Minikh 1997). B. Combined stratigraphic log of Petropavlovka II–IV sections (modified from Tverdokhlebov 1967).
Fig. 2. Microdrile oligochaete PIN 5640 in A probable oligochaete from an Early Triassic Lagerstätte of the southern Cis-Urals and its evolutionary implications
Fig. 2. Microdrile oligochaete PIN 5640/212 (A) from Petropavlovka Formation, Olenekian (Lower Triassic), Petropavlovka III section, Russia and extant Tubifex tubifex (Müller, 1774) (B) from Khripan' River, Moscow region, Russia. A. Photograph under polarised light (A1) and SEM image depicting main features of the specimen (А2): general outlines (continuous line), W-shaped depression (long dashed line), prominent annuli (dashed line), dissepiments (dotted line), and post-mortem fractures (dash-and-dot line). B. SEM image. Dissepiments (asterisks), segments are numbered, depression in posterior part of genital region (arrow).
Results from Interpreting Cis-Regulatory Interactions from Large-Scale Deep Neural Networks for Genomics
Open the record for dataset details and reuse information.
Mapa 1 in Una nueva especie del género Cis Latreille, 1796 de la comarca de Osona, Cataluña, España (Coleoptera: Tenebrionoidea: Ciidae).
Mapa 1.- Ubicación de la finca Mas Pere Riera en la comarca de Osona. El punto rojo indica el lugar de recolección de los Fomitopsis pinicola.
Fig. 7.- Cis onyosi n in Una nueva especie del género Cis Latreille, 1796 de la comarca de Osona, Cataluña, España (Coleoptera: Tenebrionoidea: Ciidae).
Fig. 7.- Cis onyosi n. sp. a.- Antena del macho. b.- Funículo de la antena de la hembra. c.- Palpo maxilar. d.- Ala. e.- Protibia. f.- Edeago. g.- Vaina. h.- Lóbulo medio. Escala: a = 0,1 mm; b = 0,05 mm; c = 0,5 mm; d = 0,05 mm; e = 0,05 mm.
Figure 3 in Amino acids L-phenylalanine and L-lysine involvement in trans and cis piperamides biosynthesis in two Piper species
Figure 3. The incorporation of the amino acid L-lysine in C –C5 piperidine amide (4,5-dihydropiperine, 2) and two C -C 6 6 3 dihydropyridinone amides (trans-piplartine, 7 and cis-piplartine, 8).
Figure 2 in Amino acids L-phenylalanine and L-lysine involvement in trans and cis piperamides biosynthesis in two Piper species
Figure 2. HPLC analysis of the enzymatic reactions (L-phenylalanine + enzymatic extract of P. tuberculatum leaves). Chromatogram A shows the formation of the cinnamic acid product after incubation of the amino acid L-phenylalanine with the enzymatic extract. Chromatogram B show the the blank for comparison (L-phenylalanine + enzymatic extract of P. tuberculatum leaves, previously treated with 6M hydrochloric acid for enzyme inactivation). Chromatogram C shows the retention time of the phenylpropanoid cinnamic acid (standard). In addition to the amino acidL-phenylalanine, L-tyrosine was also used as a possible precursor to phenylpropanoids, but no conversion to p-coumaric acid was observed.The same results were observed for P. arboreum.
Figure 1 in Amino acids L-phenylalanine and L-lysine involvement in trans and cis piperamides biosynthesis in two Piper species
Figure 1. Piperine (1), 4,5-dihydropiperine (2), fagaramide (4), piperlonguminine (5), 4,5-dihydropiperlonguminine (6), trans-piplartine (7), cis-piplartine (8), and dihydropiplartine (9) are piperamides biosynthesized by P. tuberculatum; 4,5-dihydropiperiline (3) is biosynthesized by P. arboreum.
Fig.9 in A new species of Todites (Pteridophyta) with in situ spores from the Upper Permian of Pechora Cis-Urals (Russia)
Fig.9.Spores of Osmundacidites type, extracted from the matrix containing the holotype of Todites lobulatus sp.nov.,GIN 4846/102. A–C.Different indi − vidual spores, × 1500. D–F. Granulate sculpture of spore surface, × 3000.
Fig.6 in A new species of Todites (Pteridophyta) with in situ spores from the Upper Permian of Pechora Cis-Urals (Russia)
Fig.6. Todites lobulatus sp.nov.Intinskian Formation, Ufimian, Upper Permian.Macromorphology and in situ spores, based on holotype GIN 4846/102. A, B.Fertile pinnule reconstruction, upper (adaxial, A) and lower (abaxial, B) view, numerous sporangia attached to lower side of the pinnule surface (B). C.Individual sporangium with thick−walled cells on the top area. D.Granulate microstructure of the spore surface. E.General view on the isolated spore. F, G.Spore mass extracted from the sporangia, note different sizes (relatively small spores 1 and 2 and big spores 3 and 4 of F) and different outlines of the spores (round spores 2 and ovoid 1, 3 and 4 of F; round spore 1, rounded subtriangular spore 2 and ovoid spore 3 of G).Scale bars: A, B, 5 mm; C, 0.1 mm; E, F, G, 50 µm; D, 5 µm.
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.