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Supplementary Tables for "Giant virus infection signatures are modulated by euphotic zone depth strata and iron regimes...."
<p>Supplementary Tables S4 and S5</p> <p><strong>Supplementary Table 4.</strong> Project ID's for the individual assemblies available through the JGI data portal</p> <p><strong>Supplementary Table 5</strong>. Overview of giant virus isolate genomes/metagenome-assembled genomes detected across the SOTS in situ dataset</p>
Supplementary Table and Figures
<p>Table and original photos.</p>
Supplementary Table 1. Metadata from the M4B samples.
<p>This data set contains metadata (chemical and technical variables)collected together with the samples from different bioreactors around Germany and the Netherlands.</p>
Supplemental Table S3. Least square means of the digestible (d) AA (Leu, Ile, Arg, Phe, Thr and Val) supply relative to the cow's requirements (%) for the CTRL, MetLys and MetLysHis groups in the depletion, RP-AA and cross-back period of the trial. Calculations based on the actual DMI, MY and BW of the cows during the experiment.
<p><strong>Supplemental Table S3.</strong> Least square means of the digestible (d) AA (Leu, Ile, Arg, Phe, Thr and Val) supply relative to the cow’s requirements (%) for the CTRL, MetLys and MetLysHis groups in the depletion, RP-AA and cross-back period of the trial. Calculations based on the actual DMI, MY and BW of the cows during the experiment.</p>
Supplemental Table S2. Least square means of BW, DMI, milk yield (MY) and fat- and protein-corrected milk yield (FPCMY), milk protein yield (MPY), milk composition (milk fat, milk protein, milk lactose and MUN), milk N efficiency (MNE) and feed efficiency for the CTRL, MetLys and MetLysHis treatment groups in the pre-experimental, depletion and cross-back period.
<p><strong>Supplemental Table S2.</strong> Least square means of BW, DMI, milk yield (MY) and fat- and protein-corrected milk yield (FPCMY), milk protein yield (MPY), milk composition (milk fat, milk protein, milk lactose and MUN), milk N efficiency (MNE) and feed efficiency for the CTRL, MetLys and MetLysHis treatment groups in the pre-experimental, depletion and cross-back period.</p>
Supplemental Table S1. Total AA profile (exclusive Tyr and Trp) (g/kg DM) analysed with HPLC after acid hydrolysis (EC, 1998) for the feed stuffs used in the low protein diet during the experiment.
<p><strong>Supplemental Table S1.</strong> Total AA profile (exclusive Tyr and Trp) (g/kg DM) analysed with HPLC after acid hydrolysis (EC, 1998) for the feed stuffs used in the low protein diet during the experiment.</p>
Tables of the Supplementary Material for Tomás-etal_2023
<p>This folder includes Excel files that contain the information of all the tables of the Supplementary Material of Tomás-etal_2023.</p>
Tough Tables: Carefully Evaluating Entity Linking for Tabular Data
<p>Tough Tables (2T) is a dataset designed to evaluate table annotation approaches in solving the CEA and CTA tasks.<br> The dataset is compliant with the data format used in <a href="https://www.cs.ox.ac.uk/isg/challenges/sem-tab/2019/index.html">SemTab 2019</a>, and it can be used as an additional dataset without any modification. The target knowledge graph is DBpedia 2016-10.<br> Check out the <a href="https://github.com/vcutrona/tough-tables">2T GitHub repository</a> for more details about the dataset generation.</p> <p><strong>New in v3.0:</strong> We release the updated version of 2T! The target knowledge graphs are DBpedia <a href="http://downloads.dbpedia.org/wiki-archive/downloads-2016-10.html">2016-10</a> and Wikidata <a href="https://zenodo.org/record/6643443">20220521</a>. Starting from this version, the dataset is split into valid and test sets.</p> <p>This work is based on the following paper:</p> <blockquote> <p>Cutrona, V., Bianchi, F., Jimenez-Ruiz, E. and Palmonari, M. (2020). Tough Tables: Carefully Evaluating Entity Linking for Tabular Data. ISWC 2020, LNCS 12507, pp. 1–16.</p> </blockquote> <p>Note on License: This dataset includes data from the following sources. Refer to each source for license details:<br> - Wikipedia https://www.wikipedia.org/<br> - DBpedia https://dbpedia.org/<br> - Wikidata https://www.wikidata.org/<br> - SemTab 2019 https://doi.org/10.5281/zenodo.3518539<br> - GeoDatos https://www.geodatos.net<br> - The Pudding https://pudding.cool/<br> - Offices.net https://offices.net/<br> - DATA.GOV https://www.data.gov/</p> <p>THIS DATA IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.<br> <br> <strong>Changelog:</strong></p> <p><em><strong>v3.0</strong></em></p> <ul> <li>Both datasets require SemTab2020 CEA format (tab_id, row_id, col_id, entity). <ul> </ul> </li> <li>Tables IDs and artificial noise values differ from previous versions.</li> <li>Datasets are split into Valid and Test sets of tables.</li> <li>New GT for ToughTables-WD (2T_WD) <ul> <li>Entities Q23772518 and Q7327323 have been removed because they are no longer represented in WD</li> <li>Updated ancestor/descendant hierarchies to evaluate CTA.</li> </ul> </li> <li>Evaluation scripts are provided with the data sets.</li> </ul> <p><em><strong>v2.0</strong></em></p> <ul> <li>New GT for 2T_WD <ul> <li>A few entities have been removed from the CEA GT, because they are no longer represented in WD (e.g., dbr:Devonté points to wd:Q21155080, which does not exist)</li> <li>Tables codes and values differ from the previous version, because of the random noise.</li> <li>Updated ancestor/descendant hierarchies to evaluate CTA.</li> </ul> </li> </ul> <p><em><strong>v1.0</strong></em></p> <ul> <li>New Wikidata version (2T_WD)</li> <li>Fix header for tables CTRL_DBP_MUS_rock_bands_labels.csv and CTRL_DBP_MUS_rock_bands_labels_NOISE2.csv (column 2 was reported with id 1 in target - NOTE: the affected column has been removed from the SemTab2020 evaluation)</li> <li>Remove duplicated entries in tables</li> <li>Remove rows with wrong values (e.g., the Kazakhstan entity has an empty name "''")</li> <li>Many rows and noised columns are shuffled/changed due to the random noise generator algorithm</li> <li>Remove row "Florida","Floorida","New York, NY" from TOUGH_WEB_MISSP_1000_us_cities.csv (and all its NOISE1 variants)</li> <li>Fix header of tables: <ul> <li>CTRL_WIKI_POL_List_of_current_monarchs_of_sovereign_states.csv</li> <li>CTRL_WIKI_POL_List_of_current_monarchs_of_sovereign_states_NOISE2.csv</li> <li>TOUGH_T2D_BUS_29414811_2_4773219892816395776___videogames_developers.csv</li> <li>TOUGH_T2D_BUS_29414811_2_4773219892816395776___videogames_developers_NOISE2.csv</li> </ul> </li> </ul> <p><em><strong>v0.1-pre</strong></em></p> <ul> <li>First submission. It contains only tables, without GT and Targets.</li> </ul>
Table S1. Clinical failure rates in drug development: data sources.
<p>Supplementary table comprising the data sources used in the manuscript “No Improvement in 60 Years: Drug Failure Rates from the 1960s to the 2010s”.</p>
Data Table - Digital Scholarship, PhD project "Bridging Data Science and Intellectual History: Computing the Nodes and Edges in the Old University of Louvain (1425-1797)"
<p>How were academic networks configured in the premodern world, and how did they change? This doctoral project seeks to offer a data-driven answer by computing networks at and around the Old University of Louvain (1425-1797), a crucial hub for the transfer of knowledge in late medieval and early modern Europe. Drawing upon datasets under construction from the teams of the PIs at KU Leuven and UCLouvain, this project sets out to plot and visualize networks of students, scholars and their ‘books’ over almost four centuries, thus integrating data from demographic, prosopographical and book historical datasets. This will lead to a better understanding of how academic communities evolved in the past, and it will help to assess how their organization and structure promoted or hindered the creation and transfer of knowledge in premodern Europe. Hence, the doctoral research project offers an innovative test case to develop novel understandings of networks (e.g.. new tested ways to define nodes and edges) in datasets on scholars and ‘literati’, and it will be able to compare these new results to interpretations of human capital indices in the past. As such, the project creates a pioneering pilot for integrating data science into the field of intellectual and early modern history. This enhanced collaboration between KU Leuven and UCLouvain on a theme related to their common past is timely in view of 600 years Leuven/Louvain in 2025.</p>
Supplementary tables S1 and S2
<p>Supplementary materials: Moulíková Š, Kolařík M, Lorch JM, et al. 2022. Wild rodents harbour high diversity of<br> <em>Arthroderma</em>. Persoonia.</p>
Table 1
<p>The occurrence time, period of the maximum amplitude, maximum amplitude and vertical wavelength of QTDW events at 90km over KB.</p>
Supplementary Table 1. Antibodies used in the study.
<p>Dasen et al. Supplementary Table 1. Antibodies used in the study.</p> <p> </p>
TMD GRADE assessment tables
<p>sheet 1 for pain; sheet 2 for physical functioning; sheet 3 for adverse events</p>
Figures and tables supplementary
<p>Table S1: Body composition characteristics of included studies with anthropometry.<br> Table S2: Body composition characteristics of included studies with BIA.<br> Table S3. Body composition char-acteristics of included studies with DXA.<br> Figure S1. Forest plot of age according to assessment method.<br> Figure S2. Forest plot of height according to assessment method.<br> Figure S3. Forest plot of weight according to assessment method.<br> Figure S4. Forest plot of fat mass kilograms according to assessment method.<br> Figure S5. Forest plot of fat mass percentage according to assessment method.<br> Figure S6. Forest plot of fat free mass kilograms according to assessment method.<br> Figure S7. Forest plot of fat free mass percentage according to assessment method.<br> Figure S8. Forest plot of muscle mass kilograms according to assessment method.<br> Figure S9. Forest plot of muscle mass percentage according to assessment method.<br> Figure S10. Forest plot of total body water.<br> Figure S11. Forest plot of bone mineral content.<br> Figure S12. Forest plot of bone mineral density.</p>
League tables for the NMA of temporomandibular disorders
<p>sheet 1 for pain; sheet 2 for physical functioning; sheet 3 for adverse events</p>
Table S1 Metadata and antimicrobial data
<p>High prevalence of <em>bla</em><sub>CTX-M-15</sub> type extended spectrum beta-lactamases in Gambian Hooded Vultures (<em>Necrosyrtes monachus</em>) – a threatened species with substantial human interaction</p> <p>Table S1 Metadata and antimicrobial data for all <em>E.coli</em> and <em>K. pneumoniae</em> in this study.</p>
Data from: On the role of water table depth and urbanization on groundwater drought susceptibility
<p>Propagation of meteorological drought to groundwater drought is mediated by a range of natural and human-induced drivers. Using long-term (1978–2020)<em> in-situ</em> groundwater level depth (GWD) time series from 2,928 pairs of monitoring wells, this study assesses the role of two such drivers, viz., GWD and urbanization, on groundwater drought characteristics. Results show that locations with deeper GWD often experience less frequent but more intense groundwater droughts with longer average duration. In contrast, urbanization is generally associated with a reduction in groundwater drought duration and an increase in its frequency. Relative to the influence of GWD, urbanization's imprint on groundwater drought characteristics is muted. These findings can aid in improved assessment of groundwater drought risks, and for devising more effective drought adaptation measures.</p>
Supplementary Tables for Paper "Hidden genetic regulation of human complex traits via brain isoforms"
<p>Supplementary Tables for Paper "Hidden genetic regulation of human complex traits via brain isoforms".</p>
Table 1. Phytochemical Examination Of Ethyl Acetate Subfraction Of Meniran Leaves
<p>Table 1. Phytochemical Examination Of Ethyl Acetate Subfraction Of Meniran Leaves</p>
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.