cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc285xyb
title: CCDC 2091072: Experimental Crystal Structure Determination

description: Related Article: Deborah Hartmann, Sven Braner, Lutz Greb|2021|Chem.Commun.|57|8572|doi:10.1039/D1CC03452A
DOI: 10.5517/ccdc.csd.cc285xzc
title: CCDC 2091073: Experimental Crystal Structure Determination

description: Related Article: Deborah Hartmann, Sven Braner, Lutz Greb|2021|Chem.Commun.|57|8572|doi:10.1039/D1CC03452A
DOI: 10.5517/ccdc.csd.cc285y0f
title: CCDC 2091074: Experimental Crystal Structure Determination

description: Related Article: Deborah Hartmann, Sven Braner, Lutz Greb|2021|Chem.Commun.|57|8572|doi:10.1039/D1CC03452A
DOI: 10.5517/ccdc.csd.cc285y1g
title: CCDC 2091075: Experimental Crystal Structure Determination

description: Related Article: Deborah Hartmann, Sven Braner, Lutz Greb|2021|Chem.Commun.|57|8572|doi:10.1039/D1CC03452A
DOI: 10.5517/ccdc.csd.cc285y2h
title: CCDC 2091076: Experimental Crystal Structure Determination

description: Related Article: Deborah Hartmann, Sven Braner, Lutz Greb|2021|Chem.Commun.|57|8572|doi:10.1039/D1CC03452A
DOI: 10.5517/ccdc.csd.cc285y3j
title: CCDC 2091077: Experimental Crystal Structure Determination

description: Related Article: Deborah Hartmann, Sven Braner, Lutz Greb|2021|Chem.Commun.|57|8572|doi:10.1039/D1CC03452A
DOI: 10.5517/ccdc.csd.cc285y4k
title: CCDC 2091078: Experimental Crystal Structure Determination

description: Related Article: Deborah Hartmann, Sven Braner, Lutz Greb|2021|Chem.Commun.|57|8572|doi:10.1039/D1CC03452A
DOI: 10.5517/ccdc.csd.cc285y5l
title: CCDC 2091079: Experimental Crystal Structure Determination

description: Related Article: Deborah Hartmann, Sven Braner, Lutz Greb|2021|Chem.Commun.|57|8572|doi:10.1039/D1CC03452A
DOI: 10.5517/ccdc.csd.cc285y9q
title: CCDC 2091083: Experimental Crystal Structure Determination

description: Related Article: Deborah Hartmann, Sven Braner, Lutz Greb|2021|Chem.Commun.|57|8572|doi:10.1039/D1CC03452A
DOI: 10.5517/ccdc.csd.cc285y8p
title: CCDC 2091082: Experimental Crystal Structure Determination

description: Related Article: Deborah Hartmann, Sven Braner, Lutz Greb|2021|Chem.Commun.|57|8572|doi:10.1039/D1CC03452A
DOI: 10.5517/ccdc.csd.cc28d0tj
title: CCDC 2096927: Experimental Crystal Structure Determination

description: Related Article: Jamila Ben Abdallah, Carlos J. Gόmez-Garcίa, Habib Boughzala|2021|J.Solid State Chem.|303|122504|doi:10.1016/j.jssc.2021.122504
DOI: 10.5517/ccdc.csd.cc283g0w
title: CCDC 2088687: Experimental Crystal Structure Determination

description: Related Article: Haruka Kubo, Ryusei Oketani, Ichiro Hisaki|2021|Chem.Commun.|57|8568|doi:10.1039/D1CC03287A
DOI: 10.5517/ccdc.csd.cc283g1x
title: CCDC 2088688: Experimental Crystal Structure Determination

description: Related Article: Haruka Kubo, Ryusei Oketani, Ichiro Hisaki|2021|Chem.Commun.|57|8568|doi:10.1039/D1CC03287A
DOI: 10.5517/ccdc.csd.cc283g2y
title: CCDC 2088689: Experimental Crystal Structure Determination

description: Related Article: Haruka Kubo, Ryusei Oketani, Ichiro Hisaki|2021|Chem.Commun.|57|8568|doi:10.1039/D1CC03287A
DOI: 10.5517/ccdc.csd.cc283g3z
title: CCDC 2088690: Experimental Crystal Structure Determination

description: Related Article: Haruka Kubo, Ryusei Oketani, Ichiro Hisaki|2021|Chem.Commun.|57|8568|doi:10.1039/D1CC03287A
DOI: 10.6073/pasta/5b3a6d80a1c6d3121a2196cb40838849
title: SEV-LTER Plant Traits Database

description: This dataset contains measurements of morphological (leaf, stem, root, and seed), nutrient, and isotopic traits for plant species growing in the Sevilleta National Wildlife Refuge. Approximately 104 species were sampled in or near four core sites of the SEV-LTER (core_blue, core_black, core_creosote, and core_PJ) plus the Sevilleta Field Station between 2017 and 2021. In addition, seed masses were measured from a 2016-era seed collection provided by Jenny Noble and added to the dataset; for these, site = NA.
DOI: 10.5281/zenodo.5259950
title: SIA-BRA: The carbon and nitrogen stable isotope ratios of animals of Brazilian biomes and coastal marine areas

description: SIA-BRA is a compilation of C and N stable isotope ratios of terrestrial and aquatic animals sampled in Brazilian biomes and coastal-marine areas. The SIA-BRA contains 21,832 and 21,551 values of δ<sup>13</sup>C and δ<sup>15</sup>N of 22,419 non-captive wildlife specimens, excluding livestock production or laboratory experiments. They were 14,496 vertebrates and 7,923 invertebrates. There were 11 phyla, with a clear dominance of Chordata (64%) and Arthropoda (29%), 36 classes, 154 orders, 473 families, 894 genera, and 1,157 species. Software format: Data are supplied as delimited text files (.csv).
description: For data use, please contact us.
DOI: 10.5066/p9s8slem
title: Wetland burned area extent derived from Sentinel-2 across the southeastern U.S. (2016-2019)

description: Wildfires and prescribed fires are frequent but under-mapped across wetlands of the southeastern United States . High annual precipitation supports rapid post-fire recovery of wetland vegetation, while associated cloud cover limits clear-sky observations. In addition, the low burn severity of prescribed fires and spectral confusion between fluctuating water levels and burned areas have resulted in wetland burned area being chronically under-estimated across the region. In this analysis, we first quantify the increase in clear-sky observations by using Sentinel-2 in addition to Landsat 8. We then present an approach using the Sentinel-2 archive (2016-2019) to train a wetland burned area algorithm at 20 m resolution. We coupled a Python-derived random forest model with Google Earth Engine to apply the algorithm across the southeastern United States (Greater-than 290,000 km2). The burned area extent was validated (burned, unburned) using points derived from 27 WorldView-2 and WorldView-3 images. The burned area extent was compared to 555 wetland fire perimeters compiled from state and federal agencies. On an annual timestep, combining the Sentinel-2 and Landsat 8 data increased the mean observation count from 17 to 46 in 2016 and from 16 to 78 in 2019. When validating single-scene burned area extent, the Sentinel-2 output had 29% and 30% omission and commission error rates, respectively. We compared this to the U.S. Geological Survey's Landsat 8 Burned Area Product (L8 BA), which had 47% and 8% omission and commission error rates, respectively. Across the four-year period, by count the Sentinel-2 burned area detected 78% of the wetland fire perimeters, compared to the L8 BA which detected 60% of the wetland fire perimeters. By area, Sentinel-2 burned area mapped 48% of the perimeter area as burned, compared to the L8 BA which mapped 32% of the perimeter area as burned. This analysis demonstrated the potential of Sentinel-2 to support efforts to track burned area extent even across challenging ecosystem types, such as wetlands.
DOI: 10.5281/zenodo.5272961
title: Dataset DLVC - Monalisa com variado PSNR

description: Datasets com imagem da Monalisa corrompida por ruído branco gaussiano. Conjunto 1 - PSNR contínuo (dois conjuntos) Conjunto 2 - gap entre baixo e alto PSNR.<br>
DOI: 10.5281/zenodo.5272960
title: Dataset DLVC - Monalisa com variado PSNR

description: Datasets com imagem da Monalisa corrompida por ruído branco gaussiano. Conjunto 1 - PSNR contínuo (dois conjuntos) Conjunto 2 - gap entre baixo e alto PSNR.<br>
DOI: 10.15468/6rvfp2
title: Biogeography and phylogeny of Paraergasilus Markevich, 1937 (Copepoda: Ergasilidae) with descriptions of two new species from the gills of grey mullet

description: This dataset contains the digitized treatments in Plazi based on the original journal article El-Rashidy, Hoda, Boxshall, Geoffrey A. (2001): Biogeography and phylogeny of Paraergasilus Markevich, 1937 (Copepoda: Ergasilidae) with descriptions of two new species from the gills of grey mullet. Journal of Natural History 35 (12): 1807-1819, DOI: 10.1080/00222930110101387, URL: http://www.tandfonline.com/doi/abs/10.1080/00222930110101387
DOI: 10.21223/66xot9/opqnbw
title: 02_Material_list_Screening for resistance to late blight in traditional landraces under greenhouse conditions.tab

description: :unav
DOI: 10.21223/66xot9/a9pqme
title: 01_Data_Screening for resistance to late blight in traditional landraces under greenhouse conditions.tab

description: :unav
DOI: 10.21223/66xot9/zl6vwo
title: 03_Datadictionary_Screening for resistance to late blight in traditional landraces under greenhouse conditions.xlsx

description: :unav
DOI: 10.5281/zenodo.5157016
title: Source data for Neutralization of SARS-CoV-2 variants by convalescent and BNT162b2 vaccinated serum

description: This dataset contains the source data used in the publication: "Neutralization of SARS-CoV-2 variants by convalescent and BNT162b2 vaccinated serum" published in Nature communications on August 26, 2021 (10.1038/s41467-021-25479-6).
DOI: 10.5281/zenodo.5157015
title: Source data for Neutralization of SARS-CoV-2 variants by convalescent and BNT162b2 vaccinated serum

description: This dataset contains the source data used in the publication: "Neutralization of SARS-CoV-2 variants by convalescent and BNT162b2 vaccinated serum" published in Nature communications on August 26, 2021 (10.1038/s41467-021-25479-6).
DOI: 10.25810/92fs-gj39
title: FIRED NORTHERN SOUTH AMERICA

description: 

            This is event- and daily-level polygons for the Fire event delineation (FIRED) product for Northern South America from November 2001 to March 2021. It is derived from the MODIS MCD64A1 burned area product (see https://lpdaac.usgs.gov/products/mcd64a1v006/ for more details). The MCD64A1 is a monthly raster grid of estimated burned dates. Firedpy (www.github.com/earthlab/firedpy) is an algorithm that converts these rasters into events by stacking the entire time series into a spatial-temporal data cube, then uses an algorithm to assign event identification numbers to pixels that fit into the same 3-dimensional spatial temporal window. This particular dataset was created using a spatial parameter of 1 pixel and 5 days. The primary benefit to this dataset over others is the ability to calculate fire spread rate. For each of these products (events and daily) the event identification numbers are the same, but the event-level product has only single polygons for each entire event, while the daily product has separate polygons for each date per event.
DOI: 10.6084/m9.figshare.16439055
title: Embryonic stem cell factor FOXD3 (Genesis) defects in gastrointestinal stromal tumors

description: Gastrointestinal stromal tumors (GIST) are mesenchymal neoplasms, believed to originate from the interstitial cells of <i>Cajal</i> (ICC), often caused by overexpression of tyrosine kinase receptors (TKR) KIT or PDGFRA. FOXD3 suppresses KIT expression in human cells; its inactivation led to an increase in ICCs in zebrafish, as well as mice, providing evidence for a functional link between <i>FOXD3</i> defects and KIT overexpression leading to GIST formation.1- MassArray data on different FOXD3 amplicons. Raw data used in FOXD3 methylation analysis of GIST and paraganglioma samples presented in figure 1C.2- Protein quantification in Paraganglioma (PGL) and GIST samples. Measurements of band densitometry to analyze FOXD3 expression in PGL and GIST samples presented in figure 2A.3- Luciferase assay to determine FOXD3 activation. Raw data of Luciferase assay performed to study protein activation in different FOXD3 variants. Data is presented in fig 3A.4- Measurements of band densitometry to analyze FOXD3 and c-Kit protein expression in HEK and NTERA-2 cells after FOXD3 siRNA assay. Raw data used in the HEK293 and NTERA-2 Protein quantification analysis in the fig 3B.5- Positive c-kit cells quantification after c-kit immunostaining in inner circular muscularis and outer longitudinal muscularis of interstitial cells of Cajal of wild type and FOXD3+/- mice. Data is presented in figure 5B. Raw data of muscle thickness measurement of the ileum of wild type and FOXD3+/- mice. Data is presented in figure 5C.
DOI: 10.6084/m9.figshare.16439055.v1
title: Embryonic stem cell factor FOXD3 (Genesis) defects in gastrointestinal stromal tumors

description: Gastrointestinal stromal tumors (GIST) are mesenchymal neoplasms, believed to originate from the interstitial cells of <i>Cajal</i> (ICC), often caused by overexpression of tyrosine kinase receptors (TKR) KIT or PDGFRA. FOXD3 suppresses KIT expression in human cells; its inactivation led to an increase in ICCs in zebrafish, as well as mice, providing evidence for a functional link between <i>FOXD3</i> defects and KIT overexpression leading to GIST formation.1- MassArray data on different FOXD3 amplicons. Raw data used in FOXD3 methylation analysis of GIST and paraganglioma samples presented in figure 1C.2- Protein quantification in Paraganglioma (PGL) and GIST samples. Measurements of band densitometry to analyze FOXD3 expression in PGL and GIST samples presented in figure 2A.3- Luciferase assay to determine FOXD3 activation. Raw data of Luciferase assay performed to study protein activation in different FOXD3 variants. Data is presented in fig 3A.4- Measurements of band densitometry to analyze FOXD3 and c-Kit protein expression in HEK and NTERA-2 cells after FOXD3 siRNA assay. Raw data used in the HEK293 and NTERA-2 Protein quantification analysis in the fig 3B.5- Positive c-kit cells quantification after c-kit immunostaining in inner circular muscularis and outer longitudinal muscularis of interstitial cells of Cajal of wild type and FOXD3+/- mice. Data is presented in figure 5B. Raw data of muscle thickness measurement of the ileum of wild type and FOXD3+/- mice. Data is presented in figure 5C.
DOI: 10.25810/g59w-fj89
title: FIRED CENTRAL AMERICA

description: 

            This is event- and daily-level polygons for the Fire event delineation (FIRED) product for Central America from November 2001 to March 2021. It is derived from the MODIS MCD64A1 burned area product (see https://lpdaac.usgs.gov/products/mcd64a1v006/ for more details). The MCD64A1 is a monthly raster grid of estimated burned dates. Firedpy (www.github.com/earthlab/firedpy) is an algorithm that converts these rasters into events by stacking the entire time series into a spatial-temporal data cube, then uses an algorithm to assign event identification numbers to pixels that fit into the same 3-dimensional spatial temporal window. This particular dataset was created using a spatial parameter of 1 pixels and 5 days. The primary benefit to this dataset over others is the ability to calculate fire spread rate. For each of these products (events and daily) the event identification numbers are the same, but the event-level product has only single polygons for each entire event, while the daily product has separate polygons for each date per event.
DOI: 10.6073/pasta/f1bcda23d7e3402441203dba09fc5901
title: Daily measurement summaries from Lake Hoare Meteorological Station (HOEM), McMurdo Dry Valleys, Antarctica (1987-2019, ongoing)

description: As part of the McMurdo Dry Valleys Long Term Ecological Research program, meteorological data are collected from various locations throughout the McMurdo Dry Valleys of Antarctica. This data package contains daily measurement summaries derived from 15-minute data generated by the Lake Hoare Meteorological Station (HOEM), located in Taylor Valley.
DOI: 10.25810/p2b3-ve93
title:  FIRED CARIBBEAN

description: 

            This is event- and daily-level polygons for the Fire event delineation (FIRED) product for the Caribbean from November 2001 to March 2021. It is derived from the MODIS MCD64A1 burned area product (see https://lpdaac.usgs.gov/products/mcd64a1v006/ for more details). The MCD64A1 is a monthly raster grid of estimated burned dates. Firedpy (www.github.com/earthlab/firedpy) is an algorithm that converts these rasters into events by stacking the entire time series into a spatial-temporal data cube, then uses an algorithm to assign event identification numbers to pixels that fit into the same 3-dimensional spatial temporal window. This particular dataset was created using a spatial parameter of 1 pixel and 5 days. The primary benefit to this dataset over others is the ability to calculate fire spread rate. For each of these products (events and daily) the event identification numbers are the same, but the event-level product has only single polygons for each entire event, while the daily product has separate polygons for each date per event.
DOI: 10.6073/pasta/cba740df312039bbbbd969ca5bf71ddc
title: Daily measurement summaries from Miers Valley Meteorological Station (MISM), McMurdo Dry Valleys, Antarctica (2012-2019, ongoing)

description: As part of the McMurdo Dry Valleys Long Term Ecological Research program, meteorological data are collected from various locations throughout the McMurdo Dry Valleys of Antarctica. This data package contains daily measurement summaries derived from 15-minute data generated by the Miers Valley Meteorological Station (MISM), located in Miers Valley.
DOI: 10.6073/pasta/cd1bb590f6fcd83a78eccddb0b19d95a
title: Daily measurement summaries from Taylor Glacier Meteorological Station (TARM), McMurdo Dry Valleys, Antarctica (1994-2019, ongoing)

description: As part of the McMurdo Dry Valleys Long Term Ecological Research program, meteorological data are collected from various locations throughout the McMurdo Dry Valleys of Antarctica. This data package contains daily measurement summaries derived from 15-minute data generated by the Taylor Glacier Meteorological Station (TARM), located in Taylor Valley. TARM was established in 1994, during the 94/95 field season.
DOI: 10.5281/zenodo.4562599
title: SARS-CoV-2 infects kidney cells and causes kidney injury and fibrosis

description: To be announced
DOI: 10.6073/pasta/4e48bd20fa919bb4d06bf37daec250da
title: Daily measurement summaries from Lake Vanda Meteorological Station (VAAM), McMurdo Dry Valleys, Antarctica (1994-2019, ongoing)

description: As part of the McMurdo Dry Valleys Long Term Ecological Research program, meteorological data are collected from various locations throughout the McMurdo Dry Valleys of Antarctica. This package contains daily measurement summaries derived from 15-minute data generated by the Lake Vanda Meteorological Station (VAAM), located in Wright Valley. VAAM was established in 1994, during the 94/95 field season.
DOI: 10.6073/pasta/313ff3554500ee858aa838bee70fc205
title: Daily measurement summaries from Lake Vida Meteorological Station (VIAM), McMurdo Dry Valleys, Antarctica (1995-2019, ongoing)

description: As part of the McMurdo Dry Valleys Long Term Ecological Research program, meteorological data are collected from various locations throughout the McMurdo Dry Valleys of Antarctica. This data package contains daily measurement summaries derived from 15-minute data generated by the Lake Vida Meteorological Station (VIAM), located in Victoria Valley.
DOI: 10.21223/2nyjit/0tg4dv
title: 02_Material_list_Screening for resistance to late blight in Peruvian wild potato species 2019.tab

description: :unav
DOI: 10.21223/2nyjit/vza5fm
title: 03_Data_dictionary_Screening for resistance to late blight in Peruvian wild potato species 2019.xlsx

description: :unav
DOI: 10.21223/2nyjit/nwe1xf
title: 01_Data_Screening for resistance to late blight in Peruvian wild potato species 2019.tab

description: :unav
DOI: 10.5281/zenodo.5270213
title: IWC : Test data for VGP workflows v2.0

description: Test data for VGP workflows in iwc. Pipeline VGP assembly v2.0
DOI: 10.5281/zenodo.5270212
title: IWC : Test data for VGP workflows v2.0

description: Test data for VGP workflows in iwc. Pipeline VGP assembly v2.0
DOI: 10.5281/zenodo.5275054
title: Open source data for microservice partitioning

description: Open-source datasets for microservice partitioning.
DOI: 10.5281/zenodo.5275053
title: Open source data for microservice partitioning

description: Open-source datasets for microservice partitioning.
DOI: 10.6084/m9.figshare.13168220.v3
title: GAMLSS modelling

description: This folder contains:<br>= the R code used to generate the data set used in the GAMLSS analysis and the generated data set (data_preparation.Rmd)<br>= the data set for the GAMLSS analysis (dataset_assessment_5_wide_format_2020_10_03.csv)<br>= the R code for the GAMLSS analysis (GAMLSS-EDM.Rmd)
DOI: 10.5517/ccdc.csd.cc272jql
title: CCDC 2058019: Experimental Crystal Structure Determination

description: Related Article: Jessica E. Waters, Georg Berger, Andrew J. Peel, Raúl García-Rodríguez, Andrew D. Bond, Dominic S. Wright|2021|Chem.-Eur.J.|27|12036|doi:10.1002/chem.202101291
DOI: 10.5517/ccdc.csd.cc272jrm
title: CCDC 2058020: Experimental Crystal Structure Determination

description: Related Article: Jessica E. Waters, Georg Berger, Andrew J. Peel, Raúl García-Rodríguez, Andrew D. Bond, Dominic S. Wright|2021|Chem.-Eur.J.|27|12036|doi:10.1002/chem.202101291
DOI: 10.5517/ccdc.csd.cc272jsn
title: CCDC 2058021: Experimental Crystal Structure Determination

description: Related Article: Jessica E. Waters, Georg Berger, Andrew J. Peel, Raúl García-Rodríguez, Andrew D. Bond, Dominic S. Wright|2021|Chem.-Eur.J.|27|12036|doi:10.1002/chem.202101291
DOI: 10.5517/ccdc.csd.cc272jtp
title: CCDC 2058022: Experimental Crystal Structure Determination

description: Related Article: Jessica E. Waters, Georg Berger, Andrew J. Peel, Raúl García-Rodríguez, Andrew D. Bond, Dominic S. Wright|2021|Chem.-Eur.J.|27|12036|doi:10.1002/chem.202101291
DOI: 10.5517/ccdc.csd.cc272jvq
title: CCDC 2058023: Experimental Crystal Structure Determination

description: Related Article: Jessica E. Waters, Georg Berger, Andrew J. Peel, Raúl García-Rodríguez, Andrew D. Bond, Dominic S. Wright|2021|Chem.-Eur.J.|27|12036|doi:10.1002/chem.202101291
DOI: 10.3886/e119446v121
title: COVID-19 US State Policy Database

description: For questions or comments about the database please contact:<br>Alexandra Skinner <br>skinnera@bu.edu <br>Research Fellow & Database Manager<br>Department of Health Law, Policy & Management <br>Boston University School of Public Health<br><br>Database of state policies on closures, shelter-in-place orders, housing protections, changes to Medicaid and SNAP, physical distancing closures, reopening, and more created by researchers at the Boston University School of Public Health. Policies included are state-wide directives or mandates, not guidance or recommendations. In order for a policy to be included, it must apply to the entire state. We are working quickly to go through state government websites to make the policy database as complete and accurate as possible in a rapidly changing policy context. If you use data on a given policy, we encourage you to triangulate based on additional sources of policy data and to review the source documentation to consider the coding decisions that are right for your work. Of course, please email us if you note a discrepancy so we can improve the database for everyone. State policy source documentation can be found at: tinyurl.com/statepolicysources.
description: State policies. Smallest Geographic Unit: State
description: other; Contributors: Megan Cole Brahim, Noa Krawczyk, Carolyn Hoffman, Claire Corkish, Elizabeth Ferrara, Elizabeth Long, Emily Baroni, Faith Contador, Hannah Simon, Morgan Simko, Rachel Scheckman, Sarah Brewer, Sue Kulkarni, Felicia Heykoop, Manish Patel, Aishwarya Vidyasagaran, Andrew Chiao, Cara Safon, Samantha Burkhart, Harry Jung, Victor Lee, Marina MacKinnon, Aarohi Rede, Marie Vearling, Sophie Li, Christina Wang, Tim Levengood, María Jordán P. Emma Chistolini
DOI: 10.5281/zenodo.5275189
title: Assessing reproduciblity of Inherited Variants Detected with Short-read Whole Genome Sequencing

description: This dataset is part of the following study: https://www.fda.gov/science-research/bioinformatics-tools/microarraysequencing-quality-control-maqcseqc The raw sequencing data can be downloaded from SRA: https://www.ncbi.nlm.nih.gov/bioproject/PRJNA723125 and NODE: https://www.biosino.org/node/project/detail/OEP0018966