cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.8419453
title: Data archive: CICT for single cell RNA-seq network inference

description: This archive contains benchmarking input data and results for using single cell gene expression data to infer gene regulatory networks (GRN) by the Causal Inference with Composition of Transactions (CICT) method and a selected set of published methods. This accompanies the manuscript "Robust discovery of gene regulatory networks from single-cell gene expression data by Causal Inference Using Composition of Transactions" (Shojaee and Huang, Brief in Bioinform 2023. DOI: 10.1093/bib/bbad370). The CICT code is available at the GitHub repo (https://github.com/hlab1/scRNAseqWithCICT/).
The original CICT algorithm was described in Shojaee et al. (arXiv:1608.02658, 2016). The benchmarked methods were included in the BEELINE benchmarking pipeline (Pratapa et al., Nat Methods 2020), to which we added DEEPDRIM (Chen et al., Brief Bioinform 2021), SCENIC (Aibar et al., Nat Methods 2017), Inferelator 3.0 (Gibbs et al., Bioinformatics 2022), and CellOracle (Kamimoto et al., Nature 2023). The output directory names are (subdirectories within each dataset):
* CICT_ewMIshrink_RFmaxdepth10_RFntrees20/: CICT for simulated data* CICT_v2/: CICT for experimental data* CELLORACLEDB/: CellOracle for experimental data* DEEPDRIM72_ewMIshrink_RFmaxdepth10_RFntrees20/: DEEPDRIM for simulated data* DEEPDRIM72_v2/: DEEPDRIM for experimental data* INFERELATOR38_ewMIshrink_RFmaxdepth10_RFntrees20/: Inferelator-Prior for simulated data* INFERELATOR38_v2/: Inferelator-Prior for experimental data* INFERELATOR34_ewMIshrink_RFmaxdepth10_RFntrees20/: Inferelator-NoPrior for experimental data* INFERELATOR34_v2/: Inferelator-NoPrior for experimental data* GENIE3/: GENIE3* GRNBOOST2/: GRNBOST2* LEAP/: LEAP* PIDC/: PIDC* PPCOR/: PPCOR* SCENICDB/: SCENIC for experimental data* SCNS/: SCNS* SCODE/: SCODE* SCRIBE/: SCRIBE* SINCERITIES/: SINCERITIES* SINGE/: SINGE* RANDOM/: RANDOM
The methods were benchmarked against two kinds of scRNA-seq datasets:* Simulated datasets produced by the SERGIO simulator from a synthetic network (Dibaeinia et al., Cell Systems 2020), including complete datasets and datasets with dropouts with shape parameter k=6.5 and rate parameter q=10, 30, 50, 70, 80. * Experimental datasets compiled by the BEELINE pipeline, evaluated at three different levels L0, L1 and L2, with three types of ground truth networks.    * Evaluation levels:        * L0: 500 highly varying genes plus TFs        * L1: 1000 highly varying genes plus TFs        * L2: 500 highly varying genes, TFs and 500 genes randomly selected that excluded the 1000 highly varying genes from L1.    * Types of ground truths:        * Cell-type-specific ChIP-seq ground truth (L0, L1, L2)        * Non-specific ChIP-seq ground truth (L0_ns, L1_ns, L2_ns)        * Loss-of-function/gain-of-function ground truth (L0_lofgof, L1_lofgof, L2_lofgof)
The directory structure is organized in accordance with the BEELINE benchmarking pipeline. For complete details please please see the BEELINE documentation (https://murali-group.github.io/Beeline/) and Github repo (https://github.com/Murali-group/Beeline).
DOI: 10.5281/zenodo.8266893
title: 30-m Resolution Bioclimatic Dataset of 1991-2020 Climate Normals for Hubei Province, the Yangtze River Middle Reaches

description: Brief Introduction of the Dataset
The dataset contains 19 30-m resolution average bioclimatic variables during 1991-2020 Climate Normals for Hubei Province (108°21′42″—116°07′50″ E, 29°01′53″—33°6′47″ N), the core region of the Yangtze River middle reaches. The dataset was constructed by statistically downscaling the Climatic Research Unit (CRU) 1-km monthly climate variables (1440 in total), cablirating with ground observation data with 82 weather stations and aggregating based on the defination of 19 bioclimatic variables. The downscaling of four 1-km Climatic Research Unit monthly climate variables including monthly maximum, mean, minimum temperature and precipitation was firstly achieved by random forest model with 30-m resolution terrain and spatial data. Then the interpolation-based geographical differential analysis (GDA) was applied to improve the accuracy of downscaled products based on ground observation data. Finally, the bioclimatic variables were aggregated based on their definitions and averaged for the 30 years. The Yangtze River middle reaches is abundant of forestry, agriculture, biodiversity resources that requires finer bioclimatic data for better understands of these aspects. This dataset will provide higher spatial accuracy, more information and applicability in finer regional studies in the Yangtze River middle reaches.
 
Description of the 19 Bioclimatic Variables
The dataset contains 19 geotiff files in total. File names and the corresponding full name of bioclimatic variables are described as follows:
Bio1 Mean annual air temperatureBio2 Mean diurnal air temperature rangeBio3 IsothermalityBio4 Temperature seasonalityBio5 Mean daily maximum air temperature of the warmest monthBio6 Mean daily minimum air temperature of the coldest monthBio7 Annual range of air temperatureBio8 Mean daily mean air temperatures of the wettest quarterBio9 Mean daily mean air temperatures of the driest quarterBio10 Mean daily mean air temperatures of the warmest quarterBio11 Mean daily mean air temperatures of the coldest quarterBio12 Annual precipitation amountBio13 Precipitation amount of the wettest monthBio14 Precipitation amount of the driest monthBio15 Precipitation seasonalityBio16 Precipitation amount of the wettest quarterBio17 Precipitation amount of the driest quarterBio18 Precipitation amount of the warmest quarterBio19 Precipitation amount of the coldest quarter
Others
More information related to bioclimatic variables can be found on https://chelsa-climate.org/bioclim/
DOI: 10.48732/vzjt-1634
title: Improved Orthorectification and Empirical Reduction of Topographic Effects in Monostatic Mini-RF S-band Observations of the Moon
DOI: 10.5517/ccdc.csd.cc2b4yhy
title: CCDC 2149710: Experimental Crystal Structure Determination

description: Related Article: Shuang-Shuang Ma, Rui Sun, Zi-Heng Zhang, Peng-Xin Guan, Jin-Qing Lin, Chun-Shan Li, Bao-Hua Xu|2023|Green Chemistry|25|8625|doi:10.1039/D3GC02517A
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2b9mx6
title: CCDC 2154218: Experimental Crystal Structure Determination

description: Related Article: Joschua Helmer, Alexander Hepp, Raphael J. F. Berger, Felicitas Lips|2023|Dalton Trans.|52|14949|doi:10.1039/D2DT03952D
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2b9mz8
title: CCDC 2154220: Experimental Crystal Structure Determination

description: Related Article: Joschua Helmer, Alexander Hepp, Raphael J. F. Berger, Felicitas Lips|2023|Dalton Trans.|52|14949|doi:10.1039/D2DT03952D
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2frxns
title: CCDC 2257316: Experimental Crystal Structure Determination

description: Related Article: Jiali Liu, Mengqi Wu, Lin Wu, Yimin Liang, Zheng-Bin Tang, Liang Jiang, Lifang Bian, Kejiang Liang, Xiaorui Zheng, Zhichang Liu|2023|Angew.Chem.,Int.Ed.|62|e202314481|doi:10.1002/anie.202314481
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2frxpt
title: CCDC 2257317: Experimental Crystal Structure Determination

description: Related Article: Jiali Liu, Mengqi Wu, Lin Wu, Yimin Liang, Zheng-Bin Tang, Liang Jiang, Lifang Bian, Kejiang Liang, Xiaorui Zheng, Zhichang Liu|2023|Angew.Chem.,Int.Ed.|62|e202314481|doi:10.1002/anie.202314481
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2fx92r
title: CCDC 2261514: Experimental Crystal Structure Determination

description: Related Article: Jiang Dai, Wei Xiong, Dong-Yu Li, Zhongzheng Cai, Jian-Bo Zhu|2023|Chem.Commun.|59|12731|doi:10.1039/D3CC04203K
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.21227/f7pt-2823
title: ERA5 derived time series of European country-aggregate electricity demand, wind power generation and solar power generation: hourly data from 1979-2019

description: ERA5 derived time series of European country-aggregate electricity demand, wind power generation and solar power generation: hourly data from 1979-2019.  The ERA5 reanalysis data (1979-2019) has been used to calculate the hourly country aggregated wind and solar power generation for 28 European countries based on a distribution of wind and solar farms which is considered to be representative of the 2017 situation. In addition a corresponding daily time series of nationally aggregated electricity demand is provided. The datasets have been produced to investigate the inter-annual variability of the three weather-dependent power system components. The dataset  here is an ERA5-derived time series of European country-aggregate elec-tricity wind power generation (Bloomfield et al., 2020). The authors use the ERA5 reanalysis data(Hersbach et al., 2020) to compute the nationally aggregated hourly capacity factor of 28 Europeancountries between 1979 and 2019. The capacity factor of a wind turbine is the ratio of the electricalenergy produced by the turbine for the period of time considered to the total amount of electricalenergy that could have been produced at full power operation during the same period.
DOI: 10.7910/dvn/ih0uck
title: Replication Data for: "Desinstitucionalização e resiliência dos conselhos no governo Bolsonaro"

description: Data from the article "Desinstitucionalização e resiliência dos conselhos no governo Bolsonaro", by Carla Bezerra et al., published in Revista DADOS, v. 67, n. 4 de 2024.
DOI: 10.5281/zenodo.10059294
title: PAPEL DO ENFERMEIRO COMO EDUCADOR UTILIZANDO JOGOS DIDÁTICOS NA ATENÇÃO PRIMÁRIA A SAÚDE

description: Introdução: O enfermeiro possui um papel fundamental na educação em saúde, de modo que busca maneiras de incitar os indivíduos a desenvolverem o senso de responsabilidade pela própria saúde. Neste setor, os jogos lúdicos podem dispor em inúmeras situações, usufruindo como recurso educativo, visando facilitar a socialização, a reflexão sobre a cultura, a importância do autocuidado e prevenção de doenças. Objetivo: Realizar revisão sistemática a fim de identificar a importância do enfermeiro como educador em saúde utilizando jogos didáticos na atenção primária. Metodologia: A metodologia aplicada ao trabalho se deu através de revisão sistemática, buscando publicações disponíveis na literatura científica sobre o papel do enfermeiro como educador utilizando jogos didáticos na atenção primária. Para isso, foram utilizados como fonte as bases de dados: SciELO (Scientific Eletronic Library Online), BVS (Biblioteca Virtual em Saúde), GOOGLE SCHOLAR, e Pubmed. Resultados: É possível demonstrar a importância dos jogos lúdicos na saúde primária, tendo o enfermeiro como o principal provedor dessa ação de educação em saúde. De forma que este profissional e sua equipe proponham soluções práticas no cotidiano de seus pacientes, analisam e formalizam medidas em prol da saúde coletiva, orientando-os na prevenção de doenças, através dos jogos educativos, torna isso um mero entretenimento a fim de gerar a assimilação de novos conceitos e estimular o conhecimento, indo além de somente prestar atendimento clínico para o tratamento da doença. Conclusão: Conclui-se que o uso dos jogos lúdicos é de extrema importância na assistência de enfermagem na atenção primária, pois através do processo educativo a utilização de estratégias facilitam estruturação do aprendizado para recuperação, prevenção e promoção da saúde. Apesar da sua eficiência mediante a educação em saúde, o índice de utilização dos jogos lúdicos é baixa, e atenta para o aprofundamento acerca deste tema.
DOI: 10.5281/zenodo.10059293
title: PAPEL DO ENFERMEIRO COMO EDUCADOR UTILIZANDO JOGOS DIDÁTICOS NA ATENÇÃO PRIMÁRIA A SAÚDE

description: Introdução: O enfermeiro possui um papel fundamental na educação em saúde, de modo que busca maneiras de incitar os indivíduos a desenvolverem o senso de responsabilidade pela própria saúde. Neste setor, os jogos lúdicos podem dispor em inúmeras situações, usufruindo como recurso educativo, visando facilitar a socialização, a reflexão sobre a cultura, a importância do autocuidado e prevenção de doenças. Objetivo: Realizar revisão sistemática a fim de identificar a importância do enfermeiro como educador em saúde utilizando jogos didáticos na atenção primária. Metodologia: A metodologia aplicada ao trabalho se deu através de revisão sistemática, buscando publicações disponíveis na literatura científica sobre o papel do enfermeiro como educador utilizando jogos didáticos na atenção primária. Para isso, foram utilizados como fonte as bases de dados: SciELO (Scientific Eletronic Library Online), BVS (Biblioteca Virtual em Saúde), GOOGLE SCHOLAR, e Pubmed. Resultados: É possível demonstrar a importância dos jogos lúdicos na saúde primária, tendo o enfermeiro como o principal provedor dessa ação de educação em saúde. De forma que este profissional e sua equipe proponham soluções práticas no cotidiano de seus pacientes, analisam e formalizam medidas em prol da saúde coletiva, orientando-os na prevenção de doenças, através dos jogos educativos, torna isso um mero entretenimento a fim de gerar a assimilação de novos conceitos e estimular o conhecimento, indo além de somente prestar atendimento clínico para o tratamento da doença. Conclusão: Conclui-se que o uso dos jogos lúdicos é de extrema importância na assistência de enfermagem na atenção primária, pois através do processo educativo a utilização de estratégias facilitam estruturação do aprendizado para recuperação, prevenção e promoção da saúde. Apesar da sua eficiência mediante a educação em saúde, o índice de utilização dos jogos lúdicos é baixa, e atenta para o aprofundamento acerca deste tema.
DOI: 10.5281/zenodo.10059250
title: Next-generation Sequencing Data Associated with "Genome Editing Outcomes Reveal Mycobacterial NucS Participates in a Short-Patch Repair of DNA Mismatches"
DOI: 10.5281/zenodo.10059249
title: Next-generation Sequencing Data Associated with "Genome Editing Outcomes Reveal Mycobacterial NucS Participates in a Short-Patch Repair of DNA Mismatches"
DOI: 10.17909/jqqw-ym57
title: test

description: test
DOI: 10.5519/qd.c9mufsxc
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (423 records)
DOI: 10.6084/m9.figshare.20279928.v2
title: Using machine learning to attribute the source of antimicrobial resistant campylobacteriosis in the United States

description: <strong>Background </strong>The construction of large genome datasets of infectious pathogens in combination with advanced bioinformatics methods has the potential to inform public health risk and targeted intervention strategies. In this study, we use the two most common <em>Campylobacter</em> species in human gastrointestinal infection as model organisms to test the use of machine learning methods for probabilistic assignment of genome sequenced cases of campylobacteriosis in the United States between 2009 and 2019 to potential source reservoirs. These enteric bacteria are ubiquitous in the gut of wild and domestic birds, agricultural mammals and commonly infect humans via consumption of contaminated food. Rising incidence and antimicrobial resistance (AMR) are major concerns and there is an urgent need to quantify the main routes to human infection. <strong>Methods</strong> As part of routine US national surveillance (2009 through 2019), 8,889 <em>Campylobacter </em>isolate genomes were sequenced from human infections and 15,924 from possible sources. Targeting genetic variation associated with adaptation to the most recent host, we used machine learning and probabilistic models to attribute the source of human infections and estimate the relative importance of different disease reservoirs. <strong>Findings</strong> Probabilistic attribution identified poultry as the primary infection source of human clinical isolates, responsible for an estimated 72% of cases. Most of the remaining clinical isolates were attributed to cattle (25%), with only a small contribution from wild bird (2%) and pork sources (2%). Fluoroquinolone and aminoglycoside resistant isolates increased overall and among infections attributed to chicken. <strong>Interpretation </strong>National-scale surveillance and quantification of the relative contribution of infection reservoirs can guide policy. Our study suggests that the greatest reductions in human campylobacteriosis in the US will come from interventions that focus on poultry, which may also reduce the spread of AMR strains.
DOI: 10.18739/a2rf5kh42
title: Discrete water samples collected from the Conductivity-Temperature-Depth (CTD) rosette at specific depths, Northern Bering Sea to Chukchi Sea, Sir Wilfrid Laurier 2021

description: The Pacific sector of the Arctic Ocean is experiencing major reductions in seasonal sea ice extent and increases in sea surface temperatures. One of the key uncertainties in this region is how the marine ecosystem will respond to seasonal shifts in the timing of spring sea ice retreat and/or delays in fall sea ice formation. Variations in upper ocean water hydrography, planktonic production, pelagic-benthic coupling and sediment carbon cycling are all influenced by sea ice and temperature change. To more systematically track the broad biological response to sea ice retreat and associated environmental change, an international consortium of scientists have developed a coordinated Distributed Biological Observatory (DBO) that includes selected biological measurements at multiple trophic levels, along with satellite and mooring measurements. The DBO currently focuses on five regional biological "hotspot" locations along a latitudinal gradient that allows for consistent sampling and monitoring at five biologically productive locations across a latitudinal gradient: DBO 1 (SLIP)-south of St. Lawrence Island (SLI), DBO2 (Chirikov)-north of SLI, DBO3 (southern Chukchi Sea), DBO4-NE Chukchi Sea,and DBO5-Barrow Canyon.
DOI: 10.18739/a2mp4vp9t
title: Discrete water samples collected from the Conductivity-Temperature-Depth (CTD) rosette at specific depths, Northern Bering Sea to Chukchi Sea, Sir Wilfrid Laurier 2022

description: The Pacific sector of the Arctic Ocean is experiencing major reductions in seasonal sea ice extent and increases in sea surface temperatures. One of the key uncertainties in this region is how the marine ecosystem will respond to seasonal shifts in the timing of spring sea ice retreat and/or delays in fall sea ice formation. Variations in upper ocean water hydrography, planktonic production, pelagic-benthic coupling and sediment carbon cycling are all influenced by sea ice and temperature change. To more systematically track the broad biological response to sea ice retreat and associated environmental change, an international consortium of scientists have developed a coordinated Distributed Biological Observatory (DBO) that includes selected biological measurements at multiple trophic levels, along with satellite and mooring measurements. The DBO currently focuses on five regional biological "hotspot" locations along a latitudinal gradient that allows for consistent sampling and monitoring at five biologically productive locations across a latitudinal gradient: DBO 1 (SLIP)-south of St. Lawrence Island (SLI), DBO2 (Chirikov)-north of SLI, DBO3 (southern Chukchi Sea), DBO4-NE Chukchi Sea,and DBO5-Barrow Canyon.
DOI: 10.6084/m9.figshare.23841123
title: Supporting Information for "The effects of host ecology and phylogeny on gut microbiota (non)parallelism across birds and mammals"

description: R scripts and data files used for investigating (non)parallelism of changes in gut microbiota taxonomic composition and inferred metagenome function across 53 mammalian and 50 avian host species based on multivariate vector analysis. The files are supporting information for our manuscript titled: "Supporting Information for "The effects of host ecology and phylogeny on gut microbiota (non)parallelism across birds and mammals".
DOI: 10.6084/m9.figshare.23841123.v1
title: Supporting Information for "The effects of host ecology and phylogeny on gut microbiota (non)parallelism across birds and mammals"

description: R scripts and data files used for investigating (non)parallelism of changes in gut microbiota taxonomic composition and inferred metagenome function across 53 mammalian and 50 avian host species based on multivariate vector analysis. The files are supporting information for our manuscript titled: "Supporting Information for "The effects of host ecology and phylogeny on gut microbiota (non)parallelism across birds and mammals".
DOI: 10.34740/kaggle/dsv/6847951
title: Exports of goods and services (% of GDP)
DOI: 10.18739/a2c53f31n
title: PM2.5 metals, OC/EC and oxidative potential measurement at House sampling site in Fairbanks during ALPACA 2022

description: This work is part of the Alaskan Layered Pollution And Chemical Analysis (ALPACA) field experiment, which was a collaborative study designed to improve understanding of pollution sources and chemical processes during winter (cold climate and low-photochemical conditions), to investigate indoor pollution, and to study the dispersion of pollution as affected by frequent temperature inversions. In this specific work, the oxidative potential (OP) of outdoor particulate matter up to 0.25 microns in diameter (PM2.5), in wintertime Fairbanks, Alaska, is investigated. Approximately 40 filter samples of ambient PM2.5 collected from January 17th to February 25th, 2022 at a Fairbanks residential site (House site) were analyzed for OP and various chemical components of PM, including organic carbon (OC), elemental carbon (EC), brown carbon (BrC) and metals. The sensitivity of OP assay to specific aerosol components and sources can provide insights beyond PM2.5 mass concentration when assessing air quality.
DOI: 10.5519/qd.3fuwbl4r
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (19 records)
DOI: 10.34740/kaggle/dsv/6848007
title: Balochi Language to English Translation Dataset
DOI: 10.34740/kaggle/dsv/6837727
title: Wreath dataset