cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.22616834
title: Additional file 1 of Gene expressions between obligate bamboo-eating pandas and non-herbivorous mammals reveal converged specialized bamboo diet adaptation

description: Additional file 1: Table S1. Description of the 49 RNA-seq libraries for eight mammals used in this study including giant and red pandas. Table S2. Normalized expression levels of shared 409 DEGs in liver samples of both panda species. Table S3. Normalized expression levels of shared 125 DEGs in pancreas samples of both panda species. Table S4. Significantly enriched GO categories for shared down-regulated DEGs in liver samples of both panda species. Table S5. Significantly enriched KEGG pathways for shared down-regulated DEGs in liver samples of both panda species. Table S6. Significantly enriched GO categories for shared up-regulated DEGs in liver samples of both panda species. Table S7. Significantly enriched KEGG pathways for shared up-regulated DEGs in liver samples of both panda species. Table S8. Significantly enriched GO categories for shared down-regulated DEGs in pancreas samples of both panda species. Table S9. Significantly enriched KEGG pathways for shared down-regulated DEGs in pancreas samples of both panda species. Table S10. Significantly enriched GO categories for shared up-regulated DEGs in pancreas samples of both panda species. Table S11. Significantly enriched KEGG pathways for shared up-regulated DEGs in pancreas samples of both panda species. Table S12. Transcription factors of shared down-regulated DEGs in both panda species. Table S13. Putative NR3C1 and promoter of AASS binding sites, identified by JASPAR. Table S14. RLU radio of firefly luciferase and renilla luciferase in five repeated experiments. Table S15. Shared up-regulated DEGs associated with carbohydrate metabolism and energy production in liver and pancreas of both panda species. The detailed information on gene function, involved pathways and annotations are from GeneCards databases ( https://www.genecards.org/ ). Table S16. Shared down-regulated DEGs related to lysine degradation in liver of both panda species. The detailed information on gene function, involved pathways and annotations are from GeneCards databases ( https://www.genecards.org/ ). Table S17. Shared down-regulated DEGs associated with lipid metabolism in liver and pancreas of both panda species. The detailed information on gene function, involved pathways and annotations are from GeneCards databases ( https://www.genecards.org/ ). Table S18. The samples that used to do RT-qPCR. Table S19.  The primer of RT-qPCR. Table S20.  Relative expression levels of each gene verified by RT-qPCR.
DOI: 10.6084/m9.figshare.14228209.v1
title: Additional file 2 of Identification of potential markers for differentiating epithelial ovarian cancer from ovarian low malignant potential tumors through integrated bioinformatics analysis

description: Additional file 2: Table S2. Top 15 related chemicals screened by cytoHubba according to MCC.
DOI: 10.6084/m9.figshare.25183643
title: 原始数据

description: original data
DOI: 10.6084/m9.figshare.25183643.v1
title: 原始数据

description: original data
DOI: 10.6084/m9.figshare.23665422
title: Additional file 1 of Transcriptomic analysis reveals the mechanism underlying the anthocyanin changes in Fragaria nilgerrensis Schlecht. and its interspecific hybrids

description: Additional file 1. Table S1. All108 metabolites identified from the FN vs BF1 and FN vs BF2 comparisons. Table S2. A total of 6967 co-significant DEGs were mapped into 109 KEGG database pathways. Table S3. Sixteen structural genes were predicted to be associated with anthocyanin biosynthesis. Table S4. 39 transcription factor DEGs were predicted to be associated with anthocyanin biosynthesis. Table S5. Analysis of the correlation between 39 transcription factor DEGs and 16 structural DEGs. Table S6. Analysis of the correlation between 39 transcription factor DEGs and 16 jointly up-regulated anthocyanins. Table S7. Primers used for qRT-PCR analysis.
DOI: 10.6084/m9.figshare.10035299
title: Additional file 1: of Bioinformatics analysis of glial inflammatory responses to air pollution

description: Differentially expressed RNAs between â LPS-treatedâ and control groups. (CSV 50 kb)
DOI: 10.6084/m9.figshare.10035299.v1
title: Additional file 1: of Bioinformatics analysis of glial inflammatory responses to air pollution

description: Differentially expressed RNAs between â LPS-treatedâ and control groups. (CSV 50 kb)
DOI: 10.6084/m9.figshare.10035302
title: Additional file 2: of Bioinformatics analysis of glial inflammatory responses to air pollution

description: Differentially expressed RNAs between â nPM-treatedâ and control groups. (CSV 167 kb)
DOI: 10.6084/m9.figshare.10035302.v1
title: Additional file 2: of Bioinformatics analysis of glial inflammatory responses to air pollution

description: Differentially expressed RNAs between â nPM-treatedâ and control groups. (CSV 167 kb)
DOI: 10.25345/c5mp4vz88
title: MassIVE MSV000094037 - WVSU_MitragynaSpeciosaProjectBBRL020824
title: Mitragyna Speciosa leaves were soaked in Methanol and subjected for further analysis.
DOI: 10.15485/2290364
title: Modeled estimates of permafrost hydrology and related fields for pan-Arctic region over the period 1980-2100

description: This dataset contains gridded estimates of total runoff (mm/day); subsurface runoff (mm/day); snow water equivalent (SWE, mm/day); vertical upward water flux of combined surface evaporation, evapotranspiration, and snow sublimation (mm/day); and soil temperature (C) across the pan-Arctic basin from simulations of the Permafrost Water Balance Model (PWBM v4). These data were generated to allow researchers to advance understanding of the changes unfolding in the Arctic's terrestrial water cycle under the influences of climate warming, hydrological cycle intensification, and permafrost thaw. The dataset will enable researchers to address important questions spanning multiple disciplines. For example, how will rising river flows exported to the coast impact critical zone ecosystems, near-shore ice dynamics, and ocean biogeochemical processes. Spatial resolution is 25x25 km with N=39926 grid cells spanning the domain. Three forcing datasets were used to drive simulations at an implicit daily time step over the period 1980-2100. Daily air temperature, precipitation, and wind speed data from the WATCH Forcing Data methodology applied to ERA5 reanalysis (W5E5) were used for meteorological forcings over the period 1980-2019. Simulations for the period 1980-2100 used meteorological data from two global climate models; IPSL-CM6A-LR and MPI-ESM1-2-HR. The PWBM hydrological outputs are organized by grid and month in gzipped ASCII text files within each archived tar file. Soil temperature is organized by grid cell and day of year from DOY 205 to DOY 260. No special software is required to work with these data. The package contains spatial domain and river basin information files. These data are most useful for analyses of the spatial and temporal variations in terrestrial hydrology and soil thermal dynamics. A manuscript describing the model simulations and associated analysis has been accepted for publication in The Cryosphere (Rawlins and Karmalkar, 2024).
DOI: 10.6084/m9.figshare.11607270.v1
title: Structural Variation of Twelve Platinum-Standard Reference Genomes Sequences

description: The SV.zip file contains 2,880 *.bed files describing the Structural Variations (SVs) among 12 Platinum-Standard Reference Genomes Sequences (PSRefSeq). Details were described in file ReadMe.
DOI: 10.6084/m9.figshare.11607270
title: Structural Variation of Twelve Platinum-Standard Reference Genomes Sequences

description: The SV.zip file contains 2,880 *.bed files describing the Structural Variations (SVs) among 12 Platinum-Standard Reference Genomes Sequences (PSRefSeq). Details were described in file ReadMe.
DOI: 10.6084/m9.figshare.22616899.v1
title: Additional file 9 of The plastid genome of twenty-two species from Ferula, Talassia, and Soranthus: comparative analysis, phylogenetic implications, and adaptive evolution

description: Additional file 9: Table S6. Synopsis of the morphological information from the 22 species.
DOI: 10.6084/m9.figshare.13180178.v1
title: LowCon: A design-based subsampling approach in a misspecified linear model

description: We consider a measurement constrained supervised learning problem, that is, (1) full sample of the predictors are given; (2) the response observations are unavailable and expensive to measure. Thus, it is ideal to select a subsample of predictor observations, measure the corresponding responses, and then fit the supervised learning model on the subsample of the predictors and responses. However, model fitting is a trial and error process, and a postulated model for the data could be misspecified. Our empirical studies demonstrate that most of the existing subsampling methods have unsatisfactory performances when the models are misspecified. In this paper, we develop a novel subsampling method, called “LowCon”, which outperforms the competing methods when the working linear model is misspecified. Our method uses orthogonal Latin hypercube designs to achieve a robust estimation. We show that the proposed design-based estimator approximately minimizes the so-called “worst-case” bias with respect to many possible misspecification terms. Both the simulated and real-data analyses demonstrate the proposed estimator is more robust than several subsample least squares estimators obtained by state-of-the-art subsampling methods.
DOI: 10.6084/m9.figshare.14228294
title: Additional file 5 of Associations between habitual diet, metabolic disease, and the gut microbiota using latent Dirichlet allocation

description: Additional file 4.
DOI: 10.6084/m9.figshare.22616902.v1
title: Additional file 10 of The plastid genome of twenty-two species from Ferula, Talassia, and Soranthus: comparative analysis, phylogenetic implications, and adaptive evolution

description: Additional file 10: Table S7. The result of  positive selection analysis based on the branch-site model.
DOI: 10.6084/m9.figshare.22616905.v1
title: Additional file 11 of The plastid genome of twenty-two species from Ferula, Talassia, and Soranthus: comparative analysis, phylogenetic implications, and adaptive evolution

description: Additional file 11: Table S8. Information for sample collections and specimen vouchers of the 22 species.
DOI: 10.6084/m9.figshare.13180178.v3
title: LowCon: A Design-based Subsampling Approach in a Misspecified Linear Model

description: We consider a measurement constrained supervised learning problem, that is, (i) full sample of the predictors are given; (ii) the response observations are unavailable and expensive to measure. Thus, it is ideal to select a subsample of predictor observations, measure the corresponding responses, and then fit the supervised learning model on the subsample of the predictors and responses. However, model fitting is a trial and error process, and a postulated model for the data could be misspecified. Our empirical studies demonstrate that most of the existing subsampling methods have unsatisfactory performances when the models are misspecified. In this paper, we develop a novel subsampling method, called “LowCon,” which outperforms the competing methods when the working linear model is misspecified. Our method uses orthogonal Latin hypercube designs to achieve a robust estimation. We show that the proposed design-based estimator approximately minimizes the so-called worst-case bias with respect to many possible misspecification terms. Both the simulated and real-data analyses demonstrate the proposed estimator is more robust than several subsample least-squares estimators obtained by state-of-the-art subsampling methods. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.22616843
title: Additional file 1 of Integrated metabolomic and transcriptomic study unveils the gene regulatory mechanisms of sugarcane growth promotion during interaction with an endophytic nitrogen-fixing bacteria

description: Additional file 1: Table S1. Information of all metabolites identified in this study. Table S2. Information of differentially abundant metabolites in IN-vs-CN. Table S3. Information of differentially abundant metabolites in KN-vs-IN. Table S5. Statistics of RNA-seq data. Table S6. Statistics of transcriptome assembly and unigene annotation. Table S7. Information of differentially expression genes in IN-vs-CN. Table S8. Information of differentially expression genes in KN-vs-IN. Table S9. Information of differentially expression genes in LN-vs-KN. Table S10. The primers used for qRT-PCR.
DOI: 10.6084/m9.figshare.20521197
title: Effect of Simulation-Based Education for Neonatal Resuscitation on Medical students' Technical and Non-technical Skills_data.xlsx

description: This is the raw data excel file of the paper on " Effect of simulation-based education for neonatal resuscitation on medical students’ technical and non-technical skills" in PLOS ONE journal.
DOI: 10.6084/m9.figshare.25163684.v1
title: BTR dataset

description: This spreadsheet contains a portion of the PRECISE and MAS datasets utilized in our article "Exploring the Link between Brain Topological Resilience and Cognitive Performance in the Context of Aging and Vascular Risk Factors: A Cross-Ethnicity Population-Based Study." The data include the sample IDs used and the BTR values after our processing. Due to data ethical restrictions, the full datasets can only be accessed via the following link:PRECISE dataset: http://paper.ncrcnd.ttctrc.com/default/project-detail?id=297&lang=enMAS dataset: https://cheba.unsw.edu.au/research-projects/sydney-memory-and-ageing-study
DOI: 10.6084/m9.figshare.14229797
title: Supplementary Material

description: Attachment material to the article "Screening and interaction analysis identify genes related to anther dehiscence in Solanum melongena L."
DOI: 10.6084/m9.figshare.10035536
title: MOESM2 of Disruption of the Golgi protein Otg1 gene causes defective hormone secretion and aberrant glucose homeostasis in mice

description: Additional file 2: Table S1. Genotypes of new born animals.
DOI: 10.6084/m9.figshare.10035536.v1
title: MOESM2 of Disruption of the Golgi protein Otg1 gene causes defective hormone secretion and aberrant glucose homeostasis in mice

description: Additional file 2: Table S1. Genotypes of new born animals.
DOI: 10.6084/m9.figshare.24191338
title: Water quality of the southern Tibetan Plateau: hydrogeochemistry assessment of the Yarlungzangbo River

description: Tables S1–S3.
DOI: 10.6084/m9.figshare.24191338.v1
title: Water quality of the southern Tibetan Plateau: hydrogeochemistry assessment of the Yarlungzangbo River

description: Tables S1–S3.
DOI: 10.6084/m9.figshare.22617304.v1
title: Additional file 1 of SETD8 inhibits ferroptosis in pancreatic cancer by inhibiting the expression of RRAD

description: Additional file 1. The original figures of the western blot.
DOI: 10.6084/m9.figshare.22617304
title: Additional file 1 of SETD8 inhibits ferroptosis in pancreatic cancer by inhibiting the expression of RRAD

description: Additional file 1. The original figures of the western blot.
DOI: 10.6084/m9.figshare.13180178.v2
title: LowCon: A Design-based Subsampling Approach in a Misspecified Linear Model

description: We consider a measurement constrained supervised learning problem, that is, (i) full sample of the predictors are given; (ii) the response observations are unavailable and expensive to measure. Thus, it is ideal to select a subsample of predictor observations, measure the corresponding responses, and then fit the supervised learning model on the subsample of the predictors and responses. However, model fitting is a trial and error process, and a postulated model for the data could be misspecified. Our empirical studies demonstrate that most of the existing subsampling methods have unsatisfactory performances when the models are misspecified. In this paper, we develop a novel subsampling method, called “LowCon,” which outperforms the competing methods when the working linear model is misspecified. Our method uses orthogonal Latin hypercube designs to achieve a robust estimation. We show that the proposed design-based estimator approximately minimizes the so-called worst-case bias with respect to many possible misspecification terms. Both the simulated and real-data analyses demonstrate the proposed estimator is more robust than several subsample least-squares estimators obtained by state-of-the-art subsampling methods. Supplementary materials for this article are available online.
DOI: 10.15156/bio/sh2032342.08fu
title: SH2032342.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1352112.08fu
title: SH1352112.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1352113.08fu
title: SH1352113.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh2032343.08fu
title: SH2032343.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh2032344.08fu
title: SH2032344.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1352114.08fu
title: SH1352114.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.