cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6073/pasta/393b1d8d1e4286a462be92e0538642e6
title: Jornada Basin LTER: Wireless meteorological station at NPP T-WEST site: Daily average soil volumetric water content data: 2013 - ongoing

description: Daily average of 30-minute Volumetric Water Content at NPP T-WEST 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 T-WEST 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.5904313
title: AEPForGTE/ILLOD: Additional Material

description: Additional Material: This repo provides data and evaluation results from our research in abbreviation-expansion pair detection for glossary term extraction (AEPForGTE). It is intended to support the glossary building process for requirement specifications. It also provides an implementation of ILLOD. ILLOD is a binary classifier for abbreviation-expansion detection (it checks Initial Letters, term Lengths, Order, and Distribution of characters). It checks for two given terms whether they are compatible as abbreviation-expansion pair. It extends the algorithm of Schwartz and Hearst [1], that we re-implemented in Python to make it usable for cross-comparisons, where abbreviations and possible expansions appear in different sentences/ requirements. ILLOD is a feature based classifier and proves to be more accurate than approaches based on syntactic or semantic similarity. Therefore, it can be a useful extension for term clustering tools for synonym detection. The notebooks are arranged according to the chapter structure in the paper. The various tables and key figures presented and mentioned in the paper are computed here. [1]: Schwartz, A.S., Hearst, M.A.: A simple algorithm for identifying abbreviation definitions in biomedical text. In: Biocomputing 2003, pp. 451–462. World Scientific(2002)
DOI: 10.6084/m9.figshare.23641995
title: Tree files for animal feed yeast phylogenies

description: Contree files for phylogenies.
DOI: 10.6084/m9.figshare.23641995.v1
title: Tree files for animal feed yeast phylogenies

description: Contree files for phylogenies.
DOI: 10.6084/m9.figshare.22347814
title: Supplemental Information: Figure S1-2, Tables S2, S3, S4, S5 and Text 1

description: Supplemental Information for Exploring shared genetics between maximal oxygen uptake and disease: the HUNT study
DOI: 10.6084/m9.figshare.22347814.v1
title: Supplemental Information: Figure S1-2, Tables S2, S3, S4, S5 and Text 1

description: Supplemental Information for Exploring shared genetics between maximal oxygen uptake and disease: the HUNT study
DOI: 10.6084/m9.figshare.22347805
title: Supplemental Table S7 SAIGE Association Tests Results

description: Summary statistics from all association tests performed with SAIGE in the total, male and female HUNT population. All genomic coordinates are given in NCBI Build 37/UCSC hg19. The calculated q-value (p-value adjusted for multiple testing) is listed together with all output data from SAIGE. All Phecode phenotypes fall within one of three Phecode categories; endocrine/metabolic, mental disorders and circulatory system, and the HUNT3 measurements are shown as a separate category.
DOI: 10.6084/m9.figshare.22347805.v1
title: Supplemental Table S7 SAIGE Association Tests Results

description: Summary statistics from all association tests performed with SAIGE in the total, male and female HUNT population. All genomic coordinates are given in NCBI Build 37/UCSC hg19. The calculated q-value (p-value adjusted for multiple testing) is listed together with all output data from SAIGE. All Phecode phenotypes fall within one of three Phecode categories; endocrine/metabolic, mental disorders and circulatory system, and the HUNT3 measurements are shown as a separate category.
DOI: 10.6084/m9.figshare.22347799
title: Supplemental Table S6 Phecode Prevalence for all populations (total, male, female)

description: Prevalence of all Phecode phenotypes, in the total-, male- and female population. Shows number of individuals in the case group and the control group, as well as the prevalence in percentage.
DOI: 10.6084/m9.figshare.22347799.v1
title: Supplemental Table S6 Phecode Prevalence for all populations (total, male, female)

description: Prevalence of all Phecode phenotypes, in the total-, male- and female population. Shows number of individuals in the case group and the control group, as well as the prevalence in percentage.
DOI: 10.6084/m9.figshare.22347784
title: Supplemental Table S1 BOLT LMM summary statistics from VO2max GWAS Klevjer et al.

description: SNPs previously found to be associated with directly measured VO2max. The table contains the GWAS summary statistics from Klevjer et al. (2022) for all SNPs with p-value &lt; 5∙10-6 and MAC&gt;10. All genomic coordinates are given in NCBI Build 37/UCSC hg19. The column P_BOLT_LMM_INF shows the association test p-value and BETA is the effect size.
DOI: 10.6073/pasta/4b99ddd97d4ce5d5a0b1dd4991c5babe
title: Jornada Basin LTER: Wireless substation at NPP C-CALI site: 30-minute soil volumetric water content data: 2013 - ongoing

description: 30-minute Soil Moisture data is measured at 10cm, 20 cm, and 30 cm soil depths at the NPP T-WEST substation located in center of 70m x 70m Jornada LTER NPP T-WEST site. 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. This is an ONGOING dataset.
DOI: 10.6073/pasta/cf1be4c805bbd09dca39140aa16b4248
title: Jornada Basin LTER: Wireless substation at NPP C-GRAV site: 30-minute soil volumetric water content data: 2013 - ongoing

description: 30-minute Soil Moisture data is measured at 10cm, 20 cm, and 30 cm soil depths at the NPP C-GRAV substation located in center of 70m x 70m Jornada LTER NPP C-GRAV site. 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. This is an ONGOING dataset.
DOI: 10.25345/c58w38c48
title: MassIVE MSV000092369 - Pseudomonas putida as saviour for troubled Synechococcus elongatus in a synthetic co-culture: Interaction studies based on a multi-OMICs approach
title: In their natural environments, microbes rarely exist in isolation. Instead, they thrive in consortia where diverse interactions take place. In this study, a defined synthetic coculture of phototrophic S. elongatus cscB, which feeds the heterotrophic P. putida cscRABY with sucrose, was investigated to identify potential interactions. In initial experiments, a remarkable growth-promoting effect brought about by the presence of the heterotrophic partner, on the cyanobacterium was observed, leading to a growth increase of up to 60 percent. Vice versa, the cyanobacterium had a neutral effect on P. putida cscRABY, highlighting the resilience against stress of Pseudomonads and their potential as co-culture partners. A suitable reference process reinforcing the growth-promoting effect was established in a parallel operating photobioreactor system. This set the basis for the analysis of the co-culture at transcriptional, proteomic, and metabolomic level. This multi-OMICs approach revealed several moderate changes, including alterations in the core metabolism, transportation, and stress signalling in both microbes, indicating multi-level interactions. These findings provide valuable insights into the complex dynamics within the co-culture system, suggesting the exchange of further molecules beyond the unidirectional feeding with sucrose.
DOI: 10.6073/pasta/cf6f965b4cb23a9ad9f18a54cc73d105
title: Jornada Basin LTER: Wireless substation at NPP C-SAND site: 30-minute soil volumetric water content data: 2013 - ongoing

description: 30-minute Soil Moisture data is measured at 10cm, 20 cm, and 30 cm soil depths at the NPP C-SAND substation located in center of 70m x 70m Jornada LTER NPP C-SAND site. 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. This is an ONGOING dataset.
DOI: 10.1285/i9788883051968p0
title: Cover
DOI: 10.6084/m9.figshare.23642028
title: VCF collection for phylogenies and comparative genomics

description: In order to compare our novel isolates with previously described members of various <em>S. cerevisiae</em> clades, including animal husbandry isolates and a Hungarian baker’s yeast, raw sequencing files from literature [Offei, Vandecruys, De Graeve, Foulquié-Moreno, and Thevelein 2019; Peter et al. 2018; Duan, Han, Wang, Liu, Shi, Li, Zhang, and Bai 2018; Imre et al. 2022; Rácz et al. 2021] were downloaded and included in our pipeline. The complete list of genomes used from literature is in Table S1. Using BAM files, local realignment around indels and joint variant calling and filtering for the isolates were performed with GATK 4.1.9.0. [Poplin et al. 2018; Van der Auwera et al. 2013] with regions annotated in the S288c reference as centromeric regions, telomeric regions, or LTRs excluded. First, genomic VCF files were obtained with the Haplotype Caller, and joint genotyping of the gVCF files was applied. Using this initial VCF, we applied base quality score recalibration using GATK and called the BAM files again in gVCF mode. After joint calling, in the resulting VCF files, only SNPs or only INDELS were selected. SNPs were filtered according to the parameters [Fay, Liu, Ong, Dunham, Cromie, Jeffery, Ludlow, and Dudley 2019]: QD &lt; 5.0; QUAL &lt; 30.0; SOR &gt; 3.0; FS &gt; 60.0; MQ &lt; 40.0; MQRankSum &lt; -12.5; ReadPosRankSum &lt; -8.0. INDELS were filtered according to the parameters QD &lt; 5.0; QUAL &lt; 30.0; FS &gt; 60.0; ReadPosRankSum &lt; -20.0. INDELS were then left-aligned. For the final VCF files, INDELS and SNPs were merged, filtered and non-variant sites were removed. This VCF was used for one round of Base Quality Score Recalibration (BQSR), and the whole process of calling was repeated. Cohort calling for the yeast closely related to SILY0002 was also performed with one round of BQSR using the same process, but for the BAM files resulting from mapping to the assembled SILY0002 genome. In the case of allele calling for the SILY0002 mapping, chromosome copy numbers (as determined below) were specified during calling with the HaploType Caller, and regions annotated in the SILY0002 genome by the LRSDAY pipeline as centromeric regions, telomeric regions, or LTRs were excluded. Combined called VCF files were uploaded to FigShare
DOI: 10.6084/m9.figshare.23642028.v1
title: VCF collection for phylogenies and comparative genomics

description: In order to compare our novel isolates with previously described members of various <em>S. cerevisiae</em> clades, including animal husbandry isolates and a Hungarian baker’s yeast, raw sequencing files from literature [Offei, Vandecruys, De Graeve, Foulquié-Moreno, and Thevelein 2019; Peter et al. 2018; Duan, Han, Wang, Liu, Shi, Li, Zhang, and Bai 2018; Imre et al. 2022; Rácz et al. 2021] were downloaded and included in our pipeline. The complete list of genomes used from literature is in Table S1. Using BAM files, local realignment around indels and joint variant calling and filtering for the isolates were performed with GATK 4.1.9.0. [Poplin et al. 2018; Van der Auwera et al. 2013] with regions annotated in the S288c reference as centromeric regions, telomeric regions, or LTRs excluded. First, genomic VCF files were obtained with the Haplotype Caller, and joint genotyping of the gVCF files was applied. Using this initial VCF, we applied base quality score recalibration using GATK and called the BAM files again in gVCF mode. After joint calling, in the resulting VCF files, only SNPs or only INDELS were selected. SNPs were filtered according to the parameters [Fay, Liu, Ong, Dunham, Cromie, Jeffery, Ludlow, and Dudley 2019]: QD &lt; 5.0; QUAL &lt; 30.0; SOR &gt; 3.0; FS &gt; 60.0; MQ &lt; 40.0; MQRankSum &lt; -12.5; ReadPosRankSum &lt; -8.0. INDELS were filtered according to the parameters QD &lt; 5.0; QUAL &lt; 30.0; FS &gt; 60.0; ReadPosRankSum &lt; -20.0. INDELS were then left-aligned. For the final VCF files, INDELS and SNPs were merged, filtered and non-variant sites were removed. This VCF was used for one round of Base Quality Score Recalibration (BQSR), and the whole process of calling was repeated. Cohort calling for the yeast closely related to SILY0002 was also performed with one round of BQSR using the same process, but for the BAM files resulting from mapping to the assembled SILY0002 genome. In the case of allele calling for the SILY0002 mapping, chromosome copy numbers (as determined below) were specified during calling with the HaploType Caller, and regions annotated in the SILY0002 genome by the LRSDAY pipeline as centromeric regions, telomeric regions, or LTRs were excluded. Combined called VCF files were uploaded to FigShare
DOI: 10.1285/i9788883051968pi
title: Title page
DOI: 10.1285/i9788883051968piii
title: Foreword
DOI: 10.1285/i9788883051968p1
title: Index
DOI: 10.1285/i9788883051968p9
title: Program
DOI: 10.1285/i9788883051968p19
title: Abstract book
DOI: 10.1285/i9788883051968p21
title: Invited lecture
DOI: 10.1285/i9788883051968p25
title: Presentations
DOI: 10.1285/i9788883051968p81
title: Posters
DOI: 10.6073/pasta/4706b9d4e5227e76572abfb815d079bb
title: Jornada Basin LTER: Wireless substation at NPP G-BASN site: 30-minute soil volumetric water content data: 2013 - ongoing

description: 30-minute Soil Moisture data is measured at 10cm, 20 cm, and 30 cm soil depths at the NPP G-BASN substation located in center of 70m x 70m Jornada LTER NPP G-BASN site. 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. This is an ONGOING dataset.
DOI: 10.1285/i9788883051968p120
title: Colophon
DOI: 10.1285/i9788883051968
title: PALEODAYS - Abstract Book. XXIII Edizione delle Giornate di Paleontologia
DOI: 10.17608/k6.auckland.23642103
title: The Estimated Value for Heaps’ Law across Digital Conditions and Speech Types

description: The confidence intervals cover 95% of the value. Errors are the averaged value from calculating by measuring the distance between the simulated and predicted values using κ and β in log space across the entire sample size.
DOI: 10.17608/k6.auckland.23642103.v1
title: The Estimated Value for Heaps’ Law across Digital Conditions and Speech Types

description: The confidence intervals cover 95% of the value. Errors are the averaged value from calculating by measuring the distance between the simulated and predicted values using κ and β in log space across the entire sample size.
DOI: 10.6073/pasta/898560a6c9bb3fe48e9e8b507d8eb10f
title: Jornada Basin LTER: Wireless substation at NPP G-IBPE site: 30-minute soil volumetric water content data: 2013 - ongoing

description: 30-minute Soil Moisture data is measured at 10cm, 20 cm, and 30 cm soil depths at the NPP G-IBPE substation located in center of 70m x 70m Jornada LTER NPP G-IBPE site. 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. This is an ONGOING dataset.
DOI: 10.17617/4.ch
title: Detection of Few Hydrogen Peroxide Molecules Using Self-Reporting Fluorescent Nanodiamond Quantum Sensors

description: This contains the Raw Data and Processed Data of: Wu, Y., Balasubramanian, P., Wang, Z., Coelho, J. A. S., Prslja, M., Siebert, R., et al. (2022). Detection of Few Hydrogen Peroxide Molecules Using Self-Reporting Fluorescent Nanodiamond Quantum Sensors. Journal of the American Chemical Society, 144(28), 12642-12651. doi:10.1021/jacs.2c01065.
DOI: 10.6073/pasta/49ddbc92e9af4798e401389ef3c0beb7
title: Jornada Basin LTER: Wireless substation at NPP G-SUMM site: 30-minute soil volumetric water content data: 2013 - ongoing

description: 30-minute Soil Moisture data is measured at 10cm, 20 cm, and 30 cm soil depths at the NPP G-SUMM substation located in center of 70m x 70m Jornada LTER NPP G-SUMM site. 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. This is an ONGOING dataset.
DOI: 10.6073/pasta/7937e876870197612fdf12ccc3bb1a2c
title: Jornada Basin LTER: Wireless substation at NPP M-NORT site: 30-minute soil volumetric water content data: 2013 - ongoing

description: 30-minute Soil Moisture data is measured at 10cm, 20 cm, and 30 cm soil depths at the NPP M-NORT substation located in center of 70m x 70m Jornada LTER NPP M-NORT site. 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. This is an ONGOING dataset.
DOI: 10.25934/pr00009070
title: AMR through the eyes of machine learning - Data Challenge 

description: As antimicrobial resistance (AMR) emerges as a formidable global challenge, it calls for prompt, insightful strategies. We humbly present a small stride towards understanding AMR through a three-dimensional predictive model, employing machine learning to analyze pertinent datasets.
Within our model, we introduce nodes that represent categories within the dataset. A node can symbolize a country, bacterial strain, or an antibiotic. To measure the relationships between these nodes, we cautiously utilize p-values and various factors drawn from the dataset. These relationships, known as edges between nodes, are vital as they represent connections between different elements. With nodes and edges, we create a network within a region or between regions. Graph Neural Networks (GNN) facilitate a thorough analysis of these relationships, while visualization tools like hierarchical edge bundling and adjacency matrices provide a comprehensible representation. 

We also care to examine drug-pathogen relationships assigning them nodes. For instance, consider S.pneumoniae. Our model processes a cluster of nodes revolving around S.pneumoniae, where each node may represent an antibiotic like penicillin. These relationships are multi-dimensional, encompassing various aspects such as dosage availability and Minimum Inhibitory Concentration (MIC).
Furthermore, we posit that tracking the spread of resistance genes is pivotal. By considering plasmids as entities that transport resistance genes, our model might help trace the dissemination pattern of these genes. 
Through simulation, the model might also aid in foreseeing trends, allowing for adjustments that could modestly contribute to AMR mitigation. Additionally, one potential application we approach with enthusiasm and caution involves assisting in identifying effective combinations of antibiotics to counter specific bacteria, potentially considering regional variations.
We acknowledge that our initiative is but a modest contribution to the expansive challenge that AMR represents. We aspire with your support, to add a nuanced perspective in the concerted global effort against AMR.
DOI: 10.6073/pasta/16acb4b76f9e64e4c67d64a682685b31
title: Jornada Basin LTER: Wireless substation at NPP M-WELL site: 30-minute soil volumetric water content data: 2013 - ongoing

description: 30-minute Soil Moisture data is measured at 10cm, 20 cm, and 30 cm soil depths at the NPP M-WELL substation located in center of 70m x 70m Jornada LTER NPP M-WELL site. 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. This is an ONGOING dataset.
DOI: 10.5281/zenodo.8124120
title: Adiar 1.2.0 : Experiment Data

description: In our experiments for <em>Adiar</em> v1.2 we have tried to uncover the two separate questions below. The code for the benchmarks can be found at https://github.com/SSoelvsten/bdd-benchmark. <strong>Alice: Which version proposed for Adiar v1.2.0 is the best in terms of performance? In other words, what granularity is enough to solve Adiar v1.0's performance issues at the least cost?</strong> The machine <em>Alice</em> is a consumer-grade laptop. <strong>Grendel: How has the use of maximum cuts improved Adiar's performance?</strong> To this end, we have run all of our benchmarks once more but with all three versions of Adiar. These experiments were run on the computation nodes of the Grendel cluster (phys.au.dk/forskning/cscaa/).
DOI: 10.5281/zenodo.8124119
title: Adiar 1.2.0 : Experiment Data

description: In our experiments for <em>Adiar</em> v1.2 we have tried to uncover the two separate questions below. The code for the benchmarks can be found at https://github.com/SSoelvsten/bdd-benchmark. <strong>Alice: Which version proposed for Adiar v1.2.0 is the best in terms of performance? In other words, what granularity is enough to solve Adiar v1.0's performance issues at the least cost?</strong> The machine <em>Alice</em> is a consumer-grade laptop. <strong>Grendel: How has the use of maximum cuts improved Adiar's performance?</strong> To this end, we have run all of our benchmarks once more but with all three versions of Adiar. These experiments were run on the computation nodes of the Grendel cluster (phys.au.dk/forskning/cscaa/).
DOI: 10.6084/m9.figshare.23642157
title: Fernandez-Arellano etal 2023. Mixed-Species flocks in tropical savanas

description: Data and codes to assess flocking structure and organization.
DOI: 10.6084/m9.figshare.23642157.v1
title: Fernandez-Arellano etal 2023. Mixed-Species flocks in tropical savanas

description: Data and codes to assess flocking structure and organization.