cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15121/1632875
title: Cornell Ithaca Campus heat use data for a model year

description: Hourly steam use data for all significant buildings from the fiscal year (FY) 2017 (1 July 2016 - 30 June 2017) are provided. The total annual campus heating load in FY 2017 was about 0.81 trillion Btu (283,000 MWth-hrs). The data are presented as a spreadsheet, detailing on an hourly basis the total steam utilized for all buildings in each of three categories of buildings. Also available are conversions of that steam mass to Megawatts-thermal (MWth). For the same hour, the outdoor temperature, relative humidity, and enthalpy values are listed.
DOI: 10.15121/1633317
title: Utah FORGE: Microseismic Monitoring Geophone Data from Well 78-32

description: This submission includes geophone data collected by Schlumberger from Utah FORGE Phase 2C seismic monitoring well 78-32 during stimulation testing of well 58-32. The data are hosted by the Center for High Performance Computing (CHPC) at the University of Utah, and a script for downloading the data is attached. Additional survey info and tips for running the script are included in the document below.
DOI: 10.6084/m9.figshare.14936037
title: Nature-placemaking at GUI in Singapore: Survey Data

description: Survey data collected from members at Ground-Up Initiative (GUI) in Singapore regarding their engagement and perceptions about nature-placemaking activities held at GUI.<br>
DOI: 10.6084/m9.figshare.14936016
title: Annual cummulative storage of dams

description: The data is the cumulative stprage capacity of dams built on the Yellow River each year. Original data including the year when dam was constructed and completed, and the corresponding reservoir storage capacity and location was obtained from the Yellow River Conservancy Commission.<br>
DOI: 10.15121/1805182
title: Brady's Geothermal Field DASH Resampled in Time

description: This submission includes a link to the DASH (Horizontal distributed acoustic sensing) data files that were resampled in time to 100 samples per second from the original 1000 samples per second files. Data is in 30 second Matlab files organized into directories by day. The README_DASH.pdf file includes details on the contents of the Matlab files. Metadata is the same as the original data files and can be found in GDR submission 980 (see "Original Data Files" link).
DOI: 10.5281/zenodo.5083931
title: Business Process Intelligence Challenge 2019 - Processed

description: This dataset is the pre-processed version of the BPIC19 dataset. It contains potential confounding features, the treatment indicator, and the cycle time.
DOI: 10.5281/zenodo.5083930
title: Business Process Intelligence Challenge 2019 - Processed

description: This dataset is the pre-processed version of the BPIC19 dataset. It contains potential confounding features, the treatment indicator, and the cycle time.
DOI: 10.13139/ornlnccs/1806275
title: Supplemental dataset to "An Approach to High-Throughput X-ray Spectrum Image Mapping" -- Aluminum

description: Supplemental dataset to "An Approach to High-Throughput X-ray Spectrum Image Mapping" -- Aluminum
DOI: 10.13139/ornlnccs/1806276
title: Supplemental dataset to "An Approach to High-Throughput X-ray Spectrum Image Mapping" -- nanoprecipitates

description: Supplemental dataset to "An Approach to High-Throughput X-ray Spectrum Image Mapping" -- nanoprecipitates
DOI: 10.6084/m9.figshare.14936086.v1
title: Additional file 2 of Technical reliability of shipboard technologies for the application of alternative fuels

description: Additional file 2. Detailed list of failure modes.
DOI: 10.6084/m9.figshare.14936086
title: Additional file 2 of Technical reliability of shipboard technologies for the application of alternative fuels

description: Additional file 2. Detailed list of failure modes.
DOI: 10.5517/ccdc.csd.cc27nl8s
title: CCDC 2075365: Experimental Crystal Structure Determination

description: Related Article: Yao Xiao, Neng Wang, Lin-Xi Wan, Xian-Li Zhou, Xiaohuan Li, Feng Gao|2021|J.Nat.Prod.|84|1838|doi:10.1021/acs.jnatprod.0c01363
DOI: 10.5517/ccdc.csd.cc27nw3x
title: CCDC 2075639: Experimental Crystal Structure Determination

description: Related Article: Jin-Fay Tan, Carl Thomas Bormann, Kay Severin, Nicolai Cramer|2021|Chemical Science|12|9140|doi:10.1039/D1SC02583J
DOI: 10.5517/ccdc.csd.cc27nw5z
title: CCDC 2075641: Experimental Crystal Structure Determination

description: Related Article: Jin-Fay Tan, Carl Thomas Bormann, Kay Severin, Nicolai Cramer|2021|Chemical Science|12|9140|doi:10.1039/D1SC02583J
DOI: 10.5517/ccdc.csd.cc27nw60
title: CCDC 2075642: Experimental Crystal Structure Determination

description: Related Article: Jin-Fay Tan, Carl Thomas Bormann, Kay Severin, Nicolai Cramer|2021|Chemical Science|12|9140|doi:10.1039/D1SC02583J
DOI: 10.5517/ccdc.csd.cc27nw71
title: CCDC 2075643: Experimental Crystal Structure Determination

description: Related Article: Jin-Fay Tan, Carl Thomas Bormann, Kay Severin, Nicolai Cramer|2021|Chemical Science|12|9140|doi:10.1039/D1SC02583J
DOI: 10.5517/ccdc.csd.cc27nw82
title: CCDC 2075644: Experimental Crystal Structure Determination

description: Related Article: Jin-Fay Tan, Carl Thomas Bormann, Kay Severin, Nicolai Cramer|2021|Chemical Science|12|9140|doi:10.1039/D1SC02583J
DOI: 10.6084/m9.figshare.14936149
title: Additional file 1 of Phenome-wide analysis highlights putative causal relationships between self-reported migraine and other complex traits

description: Additional file 1: Supplementary File 1. LCV output for migraine.
DOI: 10.6084/m9.figshare.14936149.v1
title: Additional file 1 of Phenome-wide analysis highlights putative causal relationships between self-reported migraine and other complex traits

description: Additional file 1: Supplementary File 1. LCV output for migraine.
DOI: 10.6084/m9.figshare.14936175
title: Additional file 2 of Non-steroidal anti-inflammatory drugs and bone healing in animal models—a systematic review and meta-analysis

description: Additional file 2.
DOI: 10.6084/m9.figshare.14936175.v1
title: Additional file 2 of Non-steroidal anti-inflammatory drugs and bone healing in animal models—a systematic review and meta-analysis

description: Additional file 2.
DOI: 10.6084/m9.figshare.14936178
title: Additional file 3 of Non-steroidal anti-inflammatory drugs and bone healing in animal models—a systematic review and meta-analysis

description: Additional file 3.
DOI: 10.6084/m9.figshare.14936178.v1
title: Additional file 3 of Non-steroidal anti-inflammatory drugs and bone healing in animal models—a systematic review and meta-analysis

description: Additional file 3.
DOI: 10.6084/m9.figshare.14936193
title: Additional file 2 of Evolution of transcriptional control of antigenic variation and virulence in human and ape malaria parasites

description: Additional file 2: Description of individual sequences analyzed. This file provides a description of each sequence analyzed, organized according to species. Specific characteristics for each sequence are provided.
DOI: 10.6084/m9.figshare.14936193.v1
title: Additional file 2 of Evolution of transcriptional control of antigenic variation and virulence in human and ape malaria parasites

description: Additional file 2: Description of individual sequences analyzed. This file provides a description of each sequence analyzed, organized according to species. Specific characteristics for each sequence are provided.
DOI: 10.6084/m9.figshare.14936277.v1
title: Additional file 1 of Translation, transcultural adaptation and validation to Brazilian Portuguese of tools for adverse drug reaction assessment in children

description: Additional file 1. Evaluation of causality and avoidability assessment.
DOI: 10.6084/m9.figshare.14936277
title: Additional file 1 of Translation, transcultural adaptation and validation to Brazilian Portuguese of tools for adverse drug reaction assessment in children

description: Additional file 1. Evaluation of causality and avoidability assessment.
DOI: 10.6084/m9.figshare.14936340
title: Additional file 1 of Molecular and cellular characterization of two patient-derived ductal carcinoma in situ (DCIS) cell lines, ETCC-006 and ETCC-010

description: Additional file 1. Differentially expressed genes in ETCC-006 and ETCC-010 cell lines compared to MCF10A cells as determined by RNAseq. Genes that are over- and under-expressed and are unique to ETCC-006 and ETCC-010 cell lines are listed in separate sheets (ETCC-006_up; ETCC-006_down; ETCC-010_up; ETCC-010_down), as well as genes common between the two lines (Common_up and Common_down). Included in the files are the Ensembl gene identifiers, gene name and differential expression criteria, most notably log2(FC) and p-value. Only genes with a p-value
DOI: 10.6084/m9.figshare.14936340.v1
title: Additional file 1 of Molecular and cellular characterization of two patient-derived ductal carcinoma in situ (DCIS) cell lines, ETCC-006 and ETCC-010

description: Additional file 1. Differentially expressed genes in ETCC-006 and ETCC-010 cell lines compared to MCF10A cells as determined by RNAseq. Genes that are over- and under-expressed and are unique to ETCC-006 and ETCC-010 cell lines are listed in separate sheets (ETCC-006_up; ETCC-006_down; ETCC-010_up; ETCC-010_down), as well as genes common between the two lines (Common_up and Common_down). Included in the files are the Ensembl gene identifiers, gene name and differential expression criteria, most notably log2(FC) and p-value. Only genes with a p-value
DOI: 10.6084/m9.figshare.14936352
title: Additional file 5 of Molecular and cellular characterization of two patient-derived ductal carcinoma in situ (DCIS) cell lines, ETCC-006 and ETCC-010

description: Additional file 5.
DOI: 10.6084/m9.figshare.14936352.v1
title: Additional file 5 of Molecular and cellular characterization of two patient-derived ductal carcinoma in situ (DCIS) cell lines, ETCC-006 and ETCC-010

description: Additional file 5.
DOI: 10.6084/m9.figshare.14936355.v1
title: Additional file 6 of Molecular and cellular characterization of two patient-derived ductal carcinoma in situ (DCIS) cell lines, ETCC-006 and ETCC-010

description: Additional file 6.
DOI: 10.6084/m9.figshare.14936355
title: Additional file 6 of Molecular and cellular characterization of two patient-derived ductal carcinoma in situ (DCIS) cell lines, ETCC-006 and ETCC-010

description: Additional file 6.
DOI: 10.6084/m9.figshare.14936362
title: Additional file 2 of A conditional multi-trait sequence GWAS discovers pleiotropic candidate genes and variants for sheep wool, skin wrinkle and breech cover traits

description: Additional file 2: Table S1. Inflation factor (lambda) for each trait. The inflation of observed chi-squared statistic due to population structure was checked. Table S2. Annotation of pleiotropic effects on individual traits for 178 putative causal variants identified from the multi-trait conditional GWAS. The annotation includes positions, functional classification, rs ID where available and signed significant t-values (|t| &gt; 1.96) were provided for 178 variants across the 16 traits at two ages. Gene names and distances from the nearest genes are also provided if variants are located in or within 100 kb of the gene. Table S3. Annotation of 1510 sequence variants in strong LD with the 178 most significant variants from multi-trait conditional GWAS. The annotation includes the positions, rs ID where available, functional classification and P values of multi-trait $$\chi ^{2}$$ χ 2 statistic. The names of the nearest genes are also provided if variants are located in or within 100 kb of the gene. Table S4. List of 453 published genes previously associated with fibre characteristics in mammals (“Published-Gene set”) used to identify sequence variants to be includes in BayesR and GBLUP analysis. Ensembl identification, name of genes and gene location (chromosome number, start and end position in bp).
DOI: 10.6084/m9.figshare.14936362.v1
title: Additional file 2 of A conditional multi-trait sequence GWAS discovers pleiotropic candidate genes and variants for sheep wool, skin wrinkle and breech cover traits

description: Additional file 2: Table S1. Inflation factor (lambda) for each trait. The inflation of observed chi-squared statistic due to population structure was checked. Table S2. Annotation of pleiotropic effects on individual traits for 178 putative causal variants identified from the multi-trait conditional GWAS. The annotation includes positions, functional classification, rs ID where available and signed significant t-values (|t| &gt; 1.96) were provided for 178 variants across the 16 traits at two ages. Gene names and distances from the nearest genes are also provided if variants are located in or within 100 kb of the gene. Table S3. Annotation of 1510 sequence variants in strong LD with the 178 most significant variants from multi-trait conditional GWAS. The annotation includes the positions, rs ID where available, functional classification and P values of multi-trait $$\chi ^{2}$$ χ 2 statistic. The names of the nearest genes are also provided if variants are located in or within 100 kb of the gene. Table S4. List of 453 published genes previously associated with fibre characteristics in mammals (“Published-Gene set”) used to identify sequence variants to be includes in BayesR and GBLUP analysis. Ensembl identification, name of genes and gene location (chromosome number, start and end position in bp).
DOI: 10.6084/m9.figshare.14936431
title: Additional file 1 of The influence of feeding ecology and location on total mercury concentrations in Eurasian perch (Perca fluviatilis)

description: Additional file 1: Table S1. Quality assurance with biota reference material ERM-CE278k and ERM-BB422 within current study; Table S2. Trophic levels found in the available literature; Table S3. Computed ratios of source contribution in the final mixture (perch dorsal muscles), data obtained by means of Bayesian mixing model SIAR; Table S4. List of collected organisms and measured total mercury (THg) concentration, carbon and nitrogen isotopic values; Table S5. Estimated regression parameters (intercept and slope values), standard errors, t-values and P-values for the Gaussian GAM presented in Eqs. (1, 2, 3).
DOI: 10.6084/m9.figshare.14936431.v1
title: Additional file 1 of The influence of feeding ecology and location on total mercury concentrations in Eurasian perch (Perca fluviatilis)

description: Additional file 1: Table S1. Quality assurance with biota reference material ERM-CE278k and ERM-BB422 within current study; Table S2. Trophic levels found in the available literature; Table S3. Computed ratios of source contribution in the final mixture (perch dorsal muscles), data obtained by means of Bayesian mixing model SIAR; Table S4. List of collected organisms and measured total mercury (THg) concentration, carbon and nitrogen isotopic values; Table S5. Estimated regression parameters (intercept and slope values), standard errors, t-values and P-values for the Gaussian GAM presented in Eqs. (1, 2, 3).
DOI: 10.6084/m9.figshare.14936556
title: Additional file 3 of The microbial metabolite p-Cresol induces autistic-like behaviors in mice by remodeling the gut microbiota

description: Additional file 2: Table S1. ANCOM analysis: significant microbial features (from ASV to phylum) discriminating p-Cresol from Control microbiota (relative to Fig. 3).
DOI: 10.6084/m9.figshare.14936556.v1
title: Additional file 3 of The microbial metabolite p-Cresol induces autistic-like behaviors in mice by remodeling the gut microbiota

description: Additional file 2: Table S1. ANCOM analysis: significant microbial features (from ASV to phylum) discriminating p-Cresol from Control microbiota (relative to Fig. 3).
DOI: 10.6084/m9.figshare.14936559
title: Additional file 4 of The microbial metabolite p-Cresol induces autistic-like behaviors in mice by remodeling the gut microbiota

description: Additional file 3: Table S2. ANCOM analysis: significant microbial features (from ASV to phylum) discriminating FMTControl from FMTp-Cresol mice, 3 weeks post-FMT (relative to Fig. 5).
DOI: 10.6084/m9.figshare.14936559.v1
title: Additional file 4 of The microbial metabolite p-Cresol induces autistic-like behaviors in mice by remodeling the gut microbiota

description: Additional file 3: Table S2. ANCOM analysis: significant microbial features (from ASV to phylum) discriminating FMTControl from FMTp-Cresol mice, 3 weeks post-FMT (relative to Fig. 5).
DOI: 10.6084/m9.figshare.14936565
title: Additional file 6 of The microbial metabolite p-Cresol induces autistic-like behaviors in mice by remodeling the gut microbiota

description: Additional file 5: Table S4. Details on ASV sequences and taxonomic affiliation.
DOI: 10.6084/m9.figshare.14936562
title: Additional file 5 of The microbial metabolite p-Cresol induces autistic-like behaviors in mice by remodeling the gut microbiota

description: Additional file 4: Table S3. Output of blast sequence analysis for ThiH, Tyr and HpdA/B/C enzymes involved in p-Cresol synthesis (relative to Table 1).
DOI: 10.6084/m9.figshare.14936562.v1
title: Additional file 5 of The microbial metabolite p-Cresol induces autistic-like behaviors in mice by remodeling the gut microbiota

description: Additional file 4: Table S3. Output of blast sequence analysis for ThiH, Tyr and HpdA/B/C enzymes involved in p-Cresol synthesis (relative to Table 1).
DOI: 10.6084/m9.figshare.14936565.v1
title: Additional file 6 of The microbial metabolite p-Cresol induces autistic-like behaviors in mice by remodeling the gut microbiota

description: Additional file 5: Table S4. Details on ASV sequences and taxonomic affiliation.
DOI: 10.6084/m9.figshare.14936568
title: Additional file 7 of The microbial metabolite p-Cresol induces autistic-like behaviors in mice by remodeling the gut microbiota

description: Additional file 6: Table S6. Compilation of ANOVA statistics for behavioral data analyses and PERMANOVA statistics for 16S rRNA gene sequencing-based richness and diversity analyses.
DOI: 10.6084/m9.figshare.14936568.v1
title: Additional file 7 of The microbial metabolite p-Cresol induces autistic-like behaviors in mice by remodeling the gut microbiota

description: Additional file 6: Table S6. Compilation of ANOVA statistics for behavioral data analyses and PERMANOVA statistics for 16S rRNA gene sequencing-based richness and diversity analyses.
DOI: 10.6084/m9.figshare.14936524.v1
title: Additional file 10 of High-grade serous tubo-ovarian cancer refined with single-cell RNA sequencing: specific cell subtypes influence survival and determine molecular subtype classification

description: Additional file 10: Table S8. List and distribution of the 809 transcriptomic markers.
DOI: 10.6084/m9.figshare.14936524
title: Additional file 10 of High-grade serous tubo-ovarian cancer refined with single-cell RNA sequencing: specific cell subtypes influence survival and determine molecular subtype classification

description: Additional file 10: Table S8. List and distribution of the 809 transcriptomic markers.
DOI: 10.6084/m9.figshare.14936527
title: Additional file 11 of High-grade serous tubo-ovarian cancer refined with single-cell RNA sequencing: specific cell subtypes influence survival and determine molecular subtype classification

description: Additional file 11: Table S9. Results of the meta-analysis of Cox proportional hazards regression model based on Subcluster-Specific Z-scores.
DOI: 10.6084/m9.figshare.14936527.v1
title: Additional file 11 of High-grade serous tubo-ovarian cancer refined with single-cell RNA sequencing: specific cell subtypes influence survival and determine molecular subtype classification

description: Additional file 11: Table S9. Results of the meta-analysis of Cox proportional hazards regression model based on Subcluster-Specific Z-scores.
DOI: 10.6084/m9.figshare.14936533
title: Additional file 12 of High-grade serous tubo-ovarian cancer refined with single-cell RNA sequencing: specific cell subtypes influence survival and determine molecular subtype classification

description: Additional file 12: Table S10. Results of the meta-analysis of Cox proportional hazards regression model based on the xCell enrichment scores.
DOI: 10.6084/m9.figshare.14936533.v1
title: Additional file 12 of High-grade serous tubo-ovarian cancer refined with single-cell RNA sequencing: specific cell subtypes influence survival and determine molecular subtype classification

description: Additional file 12: Table S10. Results of the meta-analysis of Cox proportional hazards regression model based on the xCell enrichment scores.
DOI: 10.6084/m9.figshare.14936536.v1
title: Additional file 13 of High-grade serous tubo-ovarian cancer refined with single-cell RNA sequencing: specific cell subtypes influence survival and determine molecular subtype classification

description: Additional file 13: Table S11. CellPhoneDB output: list of interactions between cell phenotypes from 7 patients.
DOI: 10.6084/m9.figshare.14936536
title: Additional file 13 of High-grade serous tubo-ovarian cancer refined with single-cell RNA sequencing: specific cell subtypes influence survival and determine molecular subtype classification

description: Additional file 13: Table S11. CellPhoneDB output: list of interactions between cell phenotypes from 7 patients.
DOI: 10.6084/m9.figshare.14936539.v1
title: Additional file 14 of High-grade serous tubo-ovarian cancer refined with single-cell RNA sequencing: specific cell subtypes influence survival and determine molecular subtype classification

description: Additional file 14: Table S12. CellPhoneDB output: list of interactions across the 4 molecular subtypes: subgroup analysis of 4 patients.
DOI: 10.6084/m9.figshare.14936539
title: Additional file 14 of High-grade serous tubo-ovarian cancer refined with single-cell RNA sequencing: specific cell subtypes influence survival and determine molecular subtype classification

description: Additional file 14: Table S12. CellPhoneDB output: list of interactions across the 4 molecular subtypes: subgroup analysis of 4 patients.
DOI: 10.6084/m9.figshare.14936542
title: Additional file 15 of High-grade serous tubo-ovarian cancer refined with single-cell RNA sequencing: specific cell subtypes influence survival and determine molecular subtype classification

description: Additional file 15: Table S13. Effect of molecular subtypes on survival with or without correction for 6 prognostic phenotypes: meta-analysis.
DOI: 10.6084/m9.figshare.14936542.v1
title: Additional file 15 of High-grade serous tubo-ovarian cancer refined with single-cell RNA sequencing: specific cell subtypes influence survival and determine molecular subtype classification

description: Additional file 15: Table S13. Effect of molecular subtypes on survival with or without correction for 6 prognostic phenotypes: meta-analysis.
DOI: 10.6084/m9.figshare.14936545
title: Additional file 16 of High-grade serous tubo-ovarian cancer refined with single-cell RNA sequencing: specific cell subtypes influence survival and determine molecular subtype classification

description: Additional file 16: Table S14. Effect of 6 prognostic phenotypes on survival with or without correction for molecular subtypes: meta-analysis.
DOI: 10.6084/m9.figshare.14936545.v1
title: Additional file 16 of High-grade serous tubo-ovarian cancer refined with single-cell RNA sequencing: specific cell subtypes influence survival and determine molecular subtype classification

description: Additional file 16: Table S14. Effect of 6 prognostic phenotypes on survival with or without correction for molecular subtypes: meta-analysis.
DOI: 10.6084/m9.figshare.14936551
title: Additional file 2 of High-grade serous tubo-ovarian cancer refined with single-cell RNA sequencing: specific cell subtypes influence survival and determine molecular subtype classification

description: Additional file 2: Table S2. Single-cell RNA sequencing metrics and quality control indicators for each sample, major cell type and subcluster.