cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25934/pr00001163.0
title: Available IPD datapackage for study 'A Randomised, Double-blind, Placebo-controlled, Parallel-group, Multicentre Study to Determine the Efficacy and Safety of 2 Doses of Retigabine Immediate Release (900 mg/Day and 600 mg/Day) Used as Adjunctive Therapy in Adult Asian Subjects With Drug-resistant Partial-onset Seizures.'

description: The immediate release (IR) formulation of retigabine has been shown to be superior to placebo as adjunctive therapy in 3 adequate and well-controlled studies in subjects with drug-resistant partial-onset seizures (POS) who had previously failed to respond to two or more antiepileptic drugs (AEDs) and were still having seizures despite current treatment with 1, 2, or 3 AEDs. However, of 1244 subjects randomly assigned to treatment in these 3 clinical studies, only 10 were Asian subjects and only 5 of these Asian subjects were randomly assigned to treatment with retigabine. Therefore, this Phase III study is being conducted to evaluate the efficacy, safety and tolerability, and health outcomes of retigabine, at doses of 900 mg/day and 600 mg/day, compared with placebo in adult Asian subjects with drug-resistant POS.
DOI: 10.6073/pasta/ca3752772e8467e27f829d23acafe4e2
title: Jornada Basin LTER: Wireless meteorological station at NPP M-NORT site: 30-minute soil volumetric water content data: 2013 - ongoing

description: 30-minute Soil Moisture data at NPP M-NORT met station. Collection of soil volumetric water content data at Jornada LTER NPP sites, New Mexico, supports the environmental monitoring objectives of the Jornada LTER monitoring program that look at plant-soil water dynamics. Volumetric water content, bulk electrical conductivity, soil temperature, and bulk dielectric permittivity are measured every 30 minutes at an automated meteorological station installed at Jornada LTER NPP M-NORT site. Measurements are made every 30 minutes at 10 cm, 20 cm, and 30 cm soil depths. This is an ONGOING dataset.
DOI: 10.6073/pasta/69b59d29f8beda50c81ada008931a411
title: Jornada Basin LTER: Wireless meteorological station at NPP M-NORT site: Daily average soil volumetric water content data: 2013 - ongoing

description: Daily average of 30-minute Volumetric Water Content at NPP M-NORT met station. Collection of soil volumetric water content data at Jornada LTER NPP sites, New Mexico, supports the environmental monitoring objectives of the Jornada LTER monitoring program that look at plant-soil water dynamics. Volumetric water content, bulk electrical conductivity, soil temperature, and bulk dielectric permittivity are measured and calculated at an automated meteorological station installed at Jornada LTER NPP M-NORT site. The daily average at 3 soil depths is calculated from measurements made every 30 minutes at 10 cm, 20 cm, and 30 cm. This is an ONGOING dataset.
DOI: 10.5281/zenodo.6339973
title: Paddy Rice Mapping Learning Material(Sentinel-1 & labeling) in South Korea

description: This dataset includes time series Sentinel-1 images and paddy rice labeling in South Korea for ML/DL model training. It consists of 7,762 training patches and 5,180 validation patches for each patch consists of 256 x 256 pixels. The dataset is saved in hdf5 format separated into training/valdation data, image/labeling, and part number which can be accessed by key: {tr/va}_{im/lb}_{0~4}. According to the phonological stage of paddy rice, the Sentinel-1 images were acquired through 8-time steps from May 10 to October 20 in 20 days’ interval. In order for the images to capture similar features of rice invariant to more or less difference of growth, minimum and maximum value composite were used at transplanting season and ripening season each. The acquisition year for each patch varies from 2017 to 2019 since it was matched to that of labeling source. The paddy rice labeling is a rasterized version of farm map produced by Korean Ministry of Agriculture, Food and Rural Affairs(MAFRA). The original source data was produced by visual interpreted by high-resolution satellite images and aerial photos referring the other national GIS data and it is accessible through the national open data platform (http://data.nsdi.go.kr/dataset/20210707ds00001). As the data is distributed in a vector format, it was converted to 10 m x 10 m raster format which is compatible to the Sentinel-1, and used for labeling the images.
DOI: 10.5281/zenodo.6345555
title: Paddy Rice Mapping Learning Material(Sentinel-1 & labeling) in South Korea

description: This dataset includes time series Sentinel-1 images and paddy rice labeling in South Korea for ML/DL model training. It consists of 7,762 training patches and 5,180 validation patches for each patch consists of 256 x 256 pixels. The dataset is saved in hdf5 format separated into training/valdation data, image/labeling, and part number which can be accessed by key: {tr/va}_{im/lb}_{0~4}. According to the phonological stage of paddy rice, the Sentinel-1 images were acquired through 8-time steps from May 10 to October 20 in 20 days’ interval. In order for the images to capture similar features of rice invariant to more or less difference of growth, minimum and maximum value composite were used at transplanting season and ripening season each. The acquisition year for each patch varies from 2017 to 2019 since it was matched to that of labeling source. The paddy rice labeling is a rasterized version of farm map produced by Korean Ministry of Agriculture, Food and Rural Affairs(MAFRA). The original source data was produced by visual interpreted by high-resolution satellite images and aerial photos referring the other national GIS data and it is accessible through the national open data platform (http://data.nsdi.go.kr/dataset/20210707ds00001). As the data is distributed in a vector format, it was converted to 10 m x 10 m raster format which is compatible to the Sentinel-1, and used for labeling the images.
DOI: 10.5281/zenodo.6339972
title: Paddy Rice Mapping Learning Material(Sentinel-1 & labeling) in South Korea

description: This dataset includes time series Sentinel-1 images and paddy rice labeling in South Korea for ML/DL model training. It consists of 7,762 training patches and 5,180 validation patches for each patch consists of 256 x 256 pixels. The dataset is saved in hdf5 format separated into training/valdation data, image/labeling, and part number which can be accessed by key: {tr/va}_{im/lb}_{0~4}. According to the phonological stage of paddy rice, the Sentinel-1 images were acquired through 8-time steps from May 10 to October 20 in 20 days’ interval. In order for the images to capture similar features of rice invariant to more or less difference of growth, minimum and maximum value composite were used at transplanting season and ripening season each. The acquisition year for each patch varies from 2017 to 2019 since it was matched to that of labeling source. The paddy rice labeling is a rasterized version of farm map produced by Korean Ministry of Agriculture, Food and Rural Affairs(MAFRA). The original source data was produced by visual interpreted by high-resolution satellite images and aerial photos referring the other national GIS data and it is accessible through the national open data platform (http://data.nsdi.go.kr/dataset/20210707ds00001). As the data is distributed in a vector format, it was converted to 10 m x 10 m raster format which is compatible to the Sentinel-1, and used for labeling the images.
DOI: 10.6084/m9.figshare.19342915
title: Additional file 2 of Resistomes and microbiome of meat trimmings and colon content from culled cows raised in conventional and organic production systems

description: Additional file 2: Data 1. Number of Individual samples within composite sample. Data 2. Carcass Meat Trimmings production system antimicrobial resistance determinants class log2 fold change pairwise differences. Data 3. Carcass Meat Trimmings facility antimicrobials resistance determinant's class log2 fold change pairwise differences. Data 4. Count matrix of raw reads attributed to antibiotic resistance determinant's aggregated by class of resistance. Data 5. Carcass Meat Trimmings production system antimicrobials resistance determinant's mechanism log2 fold change pairwise differences. Data 6. Carcass Meat Trimmings facility antimicrobials resistance determinant's mechanism log2 fold change pairwise differences. Data 7. Count matrix of raw reads attributed to antibiotic resistance determinant's aggregated by mechanism of resistance. Data 8. Colon content facility antimicrobials resistance determinant's class log2 fold change pairwise differences. Data 9. Colon content production system antimicrobials resistance determinant's class log2 fold change pairwise differences. Data 10. Colon content facility antimicrobials resistance determinant's mechanism log2 fold change pairwise differences. Data 11. Colon content production system antimicrobials resistance determinant's mechanism log2 fold change pairwise differences
DOI: 10.6084/m9.figshare.19342915.v1
title: Additional file 2 of Resistomes and microbiome of meat trimmings and colon content from culled cows raised in conventional and organic production systems

description: Additional file 2: Data 1. Number of Individual samples within composite sample. Data 2. Carcass Meat Trimmings production system antimicrobial resistance determinants class log2 fold change pairwise differences. Data 3. Carcass Meat Trimmings facility antimicrobials resistance determinant's class log2 fold change pairwise differences. Data 4. Count matrix of raw reads attributed to antibiotic resistance determinant's aggregated by class of resistance. Data 5. Carcass Meat Trimmings production system antimicrobials resistance determinant's mechanism log2 fold change pairwise differences. Data 6. Carcass Meat Trimmings facility antimicrobials resistance determinant's mechanism log2 fold change pairwise differences. Data 7. Count matrix of raw reads attributed to antibiotic resistance determinant's aggregated by mechanism of resistance. Data 8. Colon content facility antimicrobials resistance determinant's class log2 fold change pairwise differences. Data 9. Colon content production system antimicrobials resistance determinant's class log2 fold change pairwise differences. Data 10. Colon content facility antimicrobials resistance determinant's mechanism log2 fold change pairwise differences. Data 11. Colon content production system antimicrobials resistance determinant's mechanism log2 fold change pairwise differences
DOI: 10.6084/m9.figshare.19342913
title: Additional file 1 of Exposure to Trypanosoma parasites induces changes in the microbiome of the Chagas disease vector Rhodnius prolixus

description: Additional file 1. Genome assemblies obtained from NCBI and used for the pangenomic analysis including information on the bacterial strains and GenBank accession numbers.
DOI: 10.6084/m9.figshare.19342913.v1
title: Additional file 1 of Exposure to Trypanosoma parasites induces changes in the microbiome of the Chagas disease vector Rhodnius prolixus

description: Additional file 1. Genome assemblies obtained from NCBI and used for the pangenomic analysis including information on the bacterial strains and GenBank accession numbers.
DOI: 10.6084/m9.figshare.19342916
title: Additional file 2 of Exposure to Trypanosoma parasites induces changes in the microbiome of the Chagas disease vector Rhodnius prolixus

description: Additional file 2. Genomes obtained from NCBI and used for phylogenomic tree construction of Sp_FE21 including information on GenBank accession numbers.
DOI: 10.6084/m9.figshare.19342916.v1
title: Additional file 2 of Exposure to Trypanosoma parasites induces changes in the microbiome of the Chagas disease vector Rhodnius prolixus

description: Additional file 2. Genomes obtained from NCBI and used for phylogenomic tree construction of Sp_FE21 including information on GenBank accession numbers.
DOI: 10.6084/m9.figshare.19342919
title: Additional file 3 of Exposure to Trypanosoma parasites induces changes in the microbiome of the Chagas disease vector Rhodnius prolixus

description: Additional file 3. NCBI SRA identifiers for the raw sequencing data of each sample (BioProject PRJNA744378). The sample names consist of details on the timepoint after exposure (T0-T7), the pathogen used (control, T. cruzi, T. rangeli) and the intestinal segment (anterior midgut, posterior midgut).
DOI: 10.6084/m9.figshare.19342919.v1
title: Additional file 3 of Exposure to Trypanosoma parasites induces changes in the microbiome of the Chagas disease vector Rhodnius prolixus

description: Additional file 3. NCBI SRA identifiers for the raw sequencing data of each sample (BioProject PRJNA744378). The sample names consist of details on the timepoint after exposure (T0-T7), the pathogen used (control, T. cruzi, T. rangeli) and the intestinal segment (anterior midgut, posterior midgut).
DOI: 10.6084/m9.figshare.19342922
title: Additional file 4 of Exposure to Trypanosoma parasites induces changes in the microbiome of the Chagas disease vector Rhodnius prolixus

description: Additional file 4. Number of metagenomic read pairs per sample after trimming and the removal of insect reads with bowtie2 (v.2.2.5).
DOI: 10.6084/m9.figshare.19342922.v1
title: Additional file 4 of Exposure to Trypanosoma parasites induces changes in the microbiome of the Chagas disease vector Rhodnius prolixus

description: Additional file 4. Number of metagenomic read pairs per sample after trimming and the removal of insect reads with bowtie2 (v.2.2.5).
DOI: 10.6084/m9.figshare.19342925
title: Additional file 5 of Exposure to Trypanosoma parasites induces changes in the microbiome of the Chagas disease vector Rhodnius prolixus

description: Additional file 5. Percentage of reads assigned to a taxonomic group by Kaiju (Menzel et al., 2016) and the proportionate amount of bacterial reads.
DOI: 10.6084/m9.figshare.19342925.v1
title: Additional file 5 of Exposure to Trypanosoma parasites induces changes in the microbiome of the Chagas disease vector Rhodnius prolixus

description: Additional file 5. Percentage of reads assigned to a taxonomic group by Kaiju (Menzel et al., 2016) and the proportionate amount of bacterial reads.
DOI: 10.6084/m9.figshare.19342931.v1
title: Additional file 7 of Exposure to Trypanosoma parasites induces changes in the microbiome of the Chagas disease vector Rhodnius prolixus

description: Additional file 7. Shannon and Pielou indices for each sample describing alpha diversity and species evenness, respectively.
DOI: 10.6084/m9.figshare.19342931
title: Additional file 7 of Exposure to Trypanosoma parasites induces changes in the microbiome of the Chagas disease vector Rhodnius prolixus

description: Additional file 7. Shannon and Pielou indices for each sample describing alpha diversity and species evenness, respectively.
DOI: 10.6084/m9.figshare.19342937
title: Additional file 8 of Exposure to Trypanosoma parasites induces changes in the microbiome of the Chagas disease vector Rhodnius prolixus

description: Additional file 8. Functional modules and genes present in the reconstructed MAGs based on KEGG metabolic pathways. Module definitions, the corresponding hits in the MAGs (kofam_hits_in_module) and module completeness are given.
DOI: 10.6084/m9.figshare.19342937.v1
title: Additional file 8 of Exposure to Trypanosoma parasites induces changes in the microbiome of the Chagas disease vector Rhodnius prolixus

description: Additional file 8. Functional modules and genes present in the reconstructed MAGs based on KEGG metabolic pathways. Module definitions, the corresponding hits in the MAGs (kofam_hits_in_module) and module completeness are given.
DOI: 10.6084/m9.figshare.19342952
title: Additional file 2 of Functional feeds marginally alter immune expression and microbiota of Atlantic salmon (Salmo salar) gut, gill, and skin mucosa though evidence of tissue-specific signatures and host–microbe coadaptation remain

description: Additional file 2: Table S1. Top 50 keystone gut microbiota identified through network analysis; Table S2. Top 50 keystone gill microbiota identified through network analysis; Table S3. Top 50 keystone skin microbiota identified through network analysis; Table S4. Differentially abundant inferred metagenomic KEGG Orthologs (KO) across mucosal tissues; Table S5. Differentially abundant inferred metagenomic KEGG Enzyme Commission (EC) codes across mucosal tissues; Table S6. Differentially abundant inferred metagenomic MetaCyc pathways across mucosal tissues; Table S7. Primer sequences used for RT-qPCR. Primers with listed references were taken from previously published literature, after confirming specificity in-silico, and all other primers were designed using NCBI Primer-BLAST with the listed accession as the target. NCBI accessions are taken from RefSeq where possible, with those accessions denoted by * coming from GenBank.
DOI: 10.6084/m9.figshare.19342952.v1
title: Additional file 2 of Functional feeds marginally alter immune expression and microbiota of Atlantic salmon (Salmo salar) gut, gill, and skin mucosa though evidence of tissue-specific signatures and host–microbe coadaptation remain

description: Additional file 2: Table S1. Top 50 keystone gut microbiota identified through network analysis; Table S2. Top 50 keystone gill microbiota identified through network analysis; Table S3. Top 50 keystone skin microbiota identified through network analysis; Table S4. Differentially abundant inferred metagenomic KEGG Orthologs (KO) across mucosal tissues; Table S5. Differentially abundant inferred metagenomic KEGG Enzyme Commission (EC) codes across mucosal tissues; Table S6. Differentially abundant inferred metagenomic MetaCyc pathways across mucosal tissues; Table S7. Primer sequences used for RT-qPCR. Primers with listed references were taken from previously published literature, after confirming specificity in-silico, and all other primers were designed using NCBI Primer-BLAST with the listed accession as the target. NCBI accessions are taken from RefSeq where possible, with those accessions denoted by * coming from GenBank.
DOI: 10.6084/m9.figshare.19342988
title: Additional file 1 of Expression variations in ectodysplasin-A gene (eda) may contribute to morphological divergence of scales in haplochromine cichlids

description: Additional file 1. Information about qPCR primers and raw expression data.
DOI: 10.6084/m9.figshare.19342988.v1
title: Additional file 1 of Expression variations in ectodysplasin-A gene (eda) may contribute to morphological divergence of scales in haplochromine cichlids

description: Additional file 1. Information about qPCR primers and raw expression data.
DOI: 10.6084/m9.figshare.19342994.v1
title: Additional file 1 of Genetic analysis toward more nutritious barley grains for a food secure world

description: Additional file 1: Table S1. Phenotypic data of grain micronutrient concentration values among 2 years (2019/2020) and BLUEs for 216 barley genotypes. Table S2. Analysis of variance (ANOVA) and heritability of Micronutrient concentration in 216 barley accessions among two environments. Table S3. Marker trait associated with the studied traits. The physical position of markers which are passing -log10 (p value) of 3. Table S4. Marker trait associated with the multi traits. The physical position of markers which are passing -log10 (p value) of 3. Table S5. The list of genomic regions based on the linkage disequilibrium of multi-traits associated marker. Table S6. The list of candidate genes based on the linkage disequilibrium of multi-traits associated marker.
DOI: 10.6084/m9.figshare.19342994
title: Additional file 1 of Genetic analysis toward more nutritious barley grains for a food secure world

description: Additional file 1: Table S1. Phenotypic data of grain micronutrient concentration values among 2 years (2019/2020) and BLUEs for 216 barley genotypes. Table S2. Analysis of variance (ANOVA) and heritability of Micronutrient concentration in 216 barley accessions among two environments. Table S3. Marker trait associated with the studied traits. The physical position of markers which are passing -log10 (p value) of 3. Table S4. Marker trait associated with the multi traits. The physical position of markers which are passing -log10 (p value) of 3. Table S5. The list of genomic regions based on the linkage disequilibrium of multi-traits associated marker. Table S6. The list of candidate genes based on the linkage disequilibrium of multi-traits associated marker.
DOI: 10.6084/m9.figshare.19343003
title: Additional file 2 of Unsupervised explainable AI for molecular evolutionary study of forty thousand SARS-CoV-2 genomes

description: Additional file 2:
DOI: 10.6084/m9.figshare.19343003.v1
title: Additional file 2 of Unsupervised explainable AI for molecular evolutionary study of forty thousand SARS-CoV-2 genomes

description: Additional file 2:
DOI: 10.6084/m9.figshare.19343074.v1
title: Additional file 4 of Seasonal movements in caribou ecotypes of Western Canada

description: Additional file 4. Supplemental data.
DOI: 10.6084/m9.figshare.19343074
title: Additional file 4 of Seasonal movements in caribou ecotypes of Western Canada

description: Additional file 4. Supplemental data.
DOI: 10.6073/pasta/f9f87e86ea3a65d7c678f49f81699ab1
title: Jornada Basin LTER: Wireless meteorological station at NPP M-RABB site: 5-minute summary wind and air temperature data: 2013 - ongoing

description: 5-minute summary data at NPP M-RABB met station. Average air temperature, wind speed and wind direction are measured and calculated based on 1-second scan rate of all sensors located at an automated meteorological station installed at Jornada LTER NPP M-NORT site. Wind speed is measured at 75 cm, 150 cm, and 300 cm, wind direction at approximately 3m, and air temperature at approximate 2.5m. This climate station is operated by the Jornada LTER Program. This is an ONGOING dataset.
DOI: 10.15468/dl.67qwtv
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Dionaea muscipula J.Ellis ex L., 1771)",
 "Year is greater than or equal to 1900",
 "Year is less than or equal to 2021",
 "HasGeospatialIssue is false",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024396-210914110416597/datasets/export for details.
DOI: 10.15468/dl.bcwksm
title: Occurrence Download

description: A dataset containing 161 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Facciolella oxyrhyncha (Bellotti, 1883)"
 ]
}

 The dataset includes 161 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0036161-231002084531237/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.x3zbgq
title: Occurrence Download

description: A dataset containing 1692 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Axonopus aureus P.Beauv.",
 "BasisOfRecord is Specimen"
 ]
}

 The dataset includes 1692 records from 84 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007039-160623103540712/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.bax6bt
title: Occurrence Download

description: A dataset containing 512 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Brazil",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Eremanthus glomerulatus Less."
 ]
}

 The dataset includes 512 records from 68 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0038045-231002084531237/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.