cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.12978750
title: Additional file 2 of Development of robust targeted proteomics assays for cerebrospinal fluid biomarkers in multiple sclerosis

description: Additional file 2: Table S2. 287 proteins significantly changed between MS and Non-MS, but that were quantified in only one study in CSF-PR.
DOI: 10.6084/m9.figshare.12978750.v1
title: Additional file 2 of Development of robust targeted proteomics assays for cerebrospinal fluid biomarkers in multiple sclerosis

description: Additional file 2: Table S2. 287 proteins significantly changed between MS and Non-MS, but that were quantified in only one study in CSF-PR.
DOI: 10.6084/m9.figshare.12978756
title: Additional file 4 of Development of robust targeted proteomics assays for cerebrospinal fluid biomarkers in multiple sclerosis

description: Additional file 4: Table S4. All 1194 identified proteins from DDA protein depth experiment.
DOI: 10.6084/m9.figshare.12978753.v1
title: Additional file 3 of Development of robust targeted proteomics assays for cerebrospinal fluid biomarkers in multiple sclerosis

description: Additional file 3: Table S3. 120 proteins from Table S1 found in the DDA protein depth experiment.
DOI: 10.6084/m9.figshare.12978759
title: Additional file 5 of Development of robust targeted proteomics assays for cerebrospinal fluid biomarkers in multiple sclerosis

description: Additional file 5: Table S5. Data from the peptide stability experiment.
DOI: 10.6084/m9.figshare.12978759.v1
title: Additional file 5 of Development of robust targeted proteomics assays for cerebrospinal fluid biomarkers in multiple sclerosis

description: Additional file 5: Table S5. Data from the peptide stability experiment.
DOI: 10.6084/m9.figshare.12978762
title: Additional file 6 of Development of robust targeted proteomics assays for cerebrospinal fluid biomarkers in multiple sclerosis

description: Additional file 6: Table S6. Data from the trypsin digestion experiment.
DOI: 10.6084/m9.figshare.12978753
title: Additional file 3 of Development of robust targeted proteomics assays for cerebrospinal fluid biomarkers in multiple sclerosis

description: Additional file 3: Table S3. 120 proteins from Table S1 found in the DDA protein depth experiment.
DOI: 10.6084/m9.figshare.12978771
title: Additional file 9 of Development of robust targeted proteomics assays for cerebrospinal fluid biomarkers in multiple sclerosis

description: Additional file 9: Table S7. Data from the PRM RRMS vs. OND experiment.
DOI: 10.6084/m9.figshare.12978771.v1
title: Additional file 9 of Development of robust targeted proteomics assays for cerebrospinal fluid biomarkers in multiple sclerosis

description: Additional file 9: Table S7. Data from the PRM RRMS vs. OND experiment.
DOI: 10.6084/m9.figshare.12978780.v1
title: Additional file 1 of The lower bathyal and abyssal seafloor fauna of eastern Australia

description: Additional file 1: Supplementary Table S1. Provisional list of taxa identified from the voyage IN2017_V03.
DOI: 10.6084/m9.figshare.12978756.v1
title: Additional file 4 of Development of robust targeted proteomics assays for cerebrospinal fluid biomarkers in multiple sclerosis

description: Additional file 4: Table S4. All 1194 identified proteins from DDA protein depth experiment.
DOI: 10.6084/m9.figshare.12978780
title: Additional file 1 of The lower bathyal and abyssal seafloor fauna of eastern Australia

description: Additional file 1: Supplementary Table S1. Provisional list of taxa identified from the voyage IN2017_V03.
DOI: 10.6084/m9.figshare.12978762.v1
title: Additional file 6 of Development of robust targeted proteomics assays for cerebrospinal fluid biomarkers in multiple sclerosis

description: Additional file 6: Table S6. Data from the trypsin digestion experiment.
DOI: 10.6084/m9.figshare.12978836
title: Additional file 2 of NanoPASS: an easy-to-use user interface for nanoparticle dosimetry with the 3DSDD model

description: Additional file 2.
DOI: 10.6084/m9.figshare.12978836.v1
title: Additional file 2 of NanoPASS: an easy-to-use user interface for nanoparticle dosimetry with the 3DSDD model

description: Additional file 2.
DOI: 10.6084/m9.figshare.12978830
title: Additional file 2 of Biological observations in microbiota analysis are robust to the choice of 16S rRNA gene sequencing processing algorithm: case study on human milk microbiota

description: Additional file 2: Table S2. Prevalence of classified genera in datasets processed by Qiime1 and Qiime2 after excluding OTUs/ASVs with less than 20 reads across each dataset. Table S4. Prevalence of classified genera in datasets processed by Qiime1 and Qiime2 after excluding OTUs/ASVs with less than 20 reads across each dataset and mean relative abundance of less than 0.01%.
DOI: 10.6084/m9.figshare.12978830.v1
title: Additional file 2 of Biological observations in microbiota analysis are robust to the choice of 16S rRNA gene sequencing processing algorithm: case study on human milk microbiota

description: Additional file 2: Table S2. Prevalence of classified genera in datasets processed by Qiime1 and Qiime2 after excluding OTUs/ASVs with less than 20 reads across each dataset. Table S4. Prevalence of classified genera in datasets processed by Qiime1 and Qiime2 after excluding OTUs/ASVs with less than 20 reads across each dataset and mean relative abundance of less than 0.01%.
DOI: 10.6084/m9.figshare.12978854
title: Additional file 2 of GMP-grade neural progenitor derivation and differentiation from clinical-grade human embryonic stem cells

description: Additional file 2: Table 1. Regents used in research-grade versus GMP-grade protocols.
DOI: 10.6084/m9.figshare.12978854.v1
title: Additional file 2 of GMP-grade neural progenitor derivation and differentiation from clinical-grade human embryonic stem cells

description: Additional file 2: Table 1. Regents used in research-grade versus GMP-grade protocols.
DOI: 10.6084/m9.figshare.12978869.v1
title: Additional file 1 of miRNAs expression signature potentially associated with lymphatic dissemination in locally advanced prostate cancer

description: Additional file 1 Table S1. Total of 301 miRNAs passed the read-counts-per-million (CPM) thresholds.
DOI: 10.6084/m9.figshare.12978875.v1
title: Additional file 3 of miRNAs expression signature potentially associated with lymphatic dissemination in locally advanced prostate cancer

description: Additional file 3 Table S3. The enriched pathways list of 157 genes that are targets of at least 5 microRNAs overexpressed in N1 tumors.
DOI: 10.6084/m9.figshare.12978872
title: Additional file 2 of miRNAs expression signature potentially associated with lymphatic dissemination in locally advanced prostate cancer

description: Additional file 2 Table S2. Spearman’s correlation analysis of microRNAs associated with lymphatic dissemination. (
DOI: 10.6084/m9.figshare.12978869
title: Additional file 1 of miRNAs expression signature potentially associated with lymphatic dissemination in locally advanced prostate cancer

description: Additional file 1 Table S1. Total of 301 miRNAs passed the read-counts-per-million (CPM) thresholds.
DOI: 10.6084/m9.figshare.12978872.v1
title: Additional file 2 of miRNAs expression signature potentially associated with lymphatic dissemination in locally advanced prostate cancer

description: Additional file 2 Table S2. Spearman’s correlation analysis of microRNAs associated with lymphatic dissemination. (
DOI: 10.6084/m9.figshare.12978875
title: Additional file 3 of miRNAs expression signature potentially associated with lymphatic dissemination in locally advanced prostate cancer

description: Additional file 3 Table S3. The enriched pathways list of 157 genes that are targets of at least 5 microRNAs overexpressed in N1 tumors.
DOI: 10.6084/m9.figshare.12978878.v1
title: Additional file 4 of miRNAs expression signature potentially associated with lymphatic dissemination in locally advanced prostate cancer

description: Additional file 4 Table S4. The enriched pathways list of 139 genes that are targets of at least 3 out of 9 microRNAs overexpressed in N0 tumors.
DOI: 10.6084/m9.figshare.12978881.v1
title: Additional file 1 of Variation in management of humeral and clavicular shaft fractures amongst fellowship trained orthopedic traumatologists

description: Additional file 1. Data: All survey responses are cited and the Chi-square results between each clinical scenario are provided.
DOI: 10.6084/m9.figshare.12978881
title: Additional file 1 of Variation in management of humeral and clavicular shaft fractures amongst fellowship trained orthopedic traumatologists

description: Additional file 1. Data: All survey responses are cited and the Chi-square results between each clinical scenario are provided.
DOI: 10.6084/m9.figshare.12978878
title: Additional file 4 of miRNAs expression signature potentially associated with lymphatic dissemination in locally advanced prostate cancer

description: Additional file 4 Table S4. The enriched pathways list of 139 genes that are targets of at least 3 out of 9 microRNAs overexpressed in N0 tumors.
DOI: 10.6084/m9.figshare.12978476
title: AM2_DATA

description: This is the data repository for the manuscript: "Relative roles of energy and momentum fluxes in the tropical response to extratropical thermal forcing", submitted to AMS.<br>Data are designed to be read and plotted via MATLAB and ncl.<br>The required data files (.mat/.nc) and code (.m/.ncl) for each figure are located in the corresponding directories.<br>Outputted figures are saved in 'svgfile' directory.<br><br>please see README in the file for more info.<br>
DOI: 10.5281/zenodo.4037565
title: Annual tornado counts

description: Annual tornado frequency on U.S. states scale
description: {"references": ["United States Storm Prediction Center , https://www.spc.noaa.gov/wcm/"]}
DOI: 10.5281/zenodo.4037564
title: Annual tornado counts

description: Annual tornado frequency on U.S. states scale
description: {"references": ["United States Storm Prediction Center , https://www.spc.noaa.gov/wcm/"]}
DOI: 10.5281/zenodo.4037573
title: Annual climate indices

description: Large scaleclimate indices including El Niño/Southern Oscillation (ENSO)-Nino3.4, Southern Oscillation Index (SOI), Arctic Oscillation (AO), Atlantic Multi-decadal Oscillation (AMO), Pacific Decadal Oscillation (PDO) and North Atlantic Oscillation (NAO).
description: {"references": ["National Oceanic and Atmospheric Administration's (NOAA's) National Centers for Environmental Prediction (NCEP)"]}
DOI: 10.5281/zenodo.4037572
title: Annual climate indices

description: Large scaleclimate indices including El Niño/Southern Oscillation (ENSO)-Nino3.4, Southern Oscillation Index (SOI), Arctic Oscillation (AO), Atlantic Multi-decadal Oscillation (AMO), Pacific Decadal Oscillation (PDO) and North Atlantic Oscillation (NAO).
description: {"references": ["National Oceanic and Atmospheric Administration's (NOAA's) National Centers for Environmental Prediction (NCEP)"]}
DOI: 10.6084/m9.figshare.11445894
title: Demagnetization Results and Compositions of Spinels

description: Three chips, ~ 1 cm in diameter and ~ 1 cm in height, were cut from each block sample. One specimen per block sample was alternating-field (AF) demagnetized using a Molspin AF demagnetizer. The other specimen was used for thermal demagnetization, in 40<sup>o</sup>C steps from 80 to 600<sup>o</sup>C using a Magnetic Measurements MMTD80 thermal demagnetizer. In addition to NRM, NRM* is also considered. NRM* is calculated by projecting the cumulative vector-difference curves towards the direction of initial NRM. Supplementary excel file includes all the observed 20 demagnetization data. Nine representative results were displayed as Figures. To identify the magnetic phases, microscopic experiments were carried out on the third specimen using scanning electron microscopy (SEM) and electron microprobe. For microscopic analysis, we used a field emission scanning electron microscope JSM7000F and Cameca SX100 electron probe x-ray micro analyzer. For quantitative analysis, 2 minute peak countings and 1 minute background countings were obtained in an accelerating voltage of 15-20 kV, 10 nA beam current, and 1 µm spot size. Metals are represented as bright contrast in all the images used in the present article because back-scattered SEM photography is used. Compositional data were determined by stoichiometric calculations using the equations of Barnes and Roeder (2001). All the compositional data used for this study is provided as supplementary documentary Tables.
DOI: 10.6084/m9.figshare.11445894.v1
title: Demagnetization Results and Compositions of Spinels

description: Three chips, ~ 1 cm in diameter and ~ 1 cm in height, were cut from each block sample. One specimen per block sample was alternating-field (AF) demagnetized using a Molspin AF demagnetizer. The other specimen was used for thermal demagnetization, in 40<sup>o</sup>C steps from 80 to 600<sup>o</sup>C using a Magnetic Measurements MMTD80 thermal demagnetizer. In addition to NRM, NRM* is also considered. NRM* is calculated by projecting the cumulative vector-difference curves towards the direction of initial NRM. Supplementary excel file includes all the observed 20 demagnetization data. Nine representative results were displayed as Figures. To identify the magnetic phases, microscopic experiments were carried out on the third specimen using scanning electron microscopy (SEM) and electron microprobe. For microscopic analysis, we used a field emission scanning electron microscope JSM7000F and Cameca SX100 electron probe x-ray micro analyzer. For quantitative analysis, 2 minute peak countings and 1 minute background countings were obtained in an accelerating voltage of 15-20 kV, 10 nA beam current, and 1 µm spot size. Metals are represented as bright contrast in all the images used in the present article because back-scattered SEM photography is used. Compositional data were determined by stoichiometric calculations using the equations of Barnes and Roeder (2001). All the compositional data used for this study is provided as supplementary documentary Tables.
DOI: 10.6084/m9.figshare.12978944
title: Semi-landmark File from A comparison of metrics for quantifying cranial suture complexity

description: Cranial sutures play critical roles in facilitating postnatal skull development and function. The diversity of function is reflected in the highly variable suture morphology and complexity. Suture complexity has seldom been studied, resulting in little consensus on the most appropriate approach for comparative, quantitative analyses. Here, we provide the first comprehensive comparison of current approaches for quantifying suture morphology, using a wide range of two-dimensional suture outlines across extinct and extant mammals (<i>n</i> = 79). Five complexity metrics (sinuosity index (SI), suture complexity index (SCI), fractal dimension (FD) box counting, FD madogram and a windowed short-time Fourier transform with power spectrum density (PSD) calculation) were compared with each other and with the shape variation in the dataset. Analyses of suture shape demonstrate that the primary axis of variation captured attributes other than complexity, supporting the use of a complexity metric over raw shape data for sutural complexity analyses. Each approach captured different aspects of complexity. PSD successfully discriminates different sutural features, such as looping patterns and interdigitation amplitude and number, while SCI best-captured variation in interdigitation number alone. Therefore, future studies should consider the relevant attributes for their question when selecting a metric for comparative analysis of suture variation, function and evolution.
DOI: 10.6084/m9.figshare.12978944.v1
title: Semi-landmark File from A comparison of metrics for quantifying cranial suture complexity

description: Cranial sutures play critical roles in facilitating postnatal skull development and function. The diversity of function is reflected in the highly variable suture morphology and complexity. Suture complexity has seldom been studied, resulting in little consensus on the most appropriate approach for comparative, quantitative analyses. Here, we provide the first comprehensive comparison of current approaches for quantifying suture morphology, using a wide range of two-dimensional suture outlines across extinct and extant mammals (<i>n</i> = 79). Five complexity metrics (sinuosity index (SI), suture complexity index (SCI), fractal dimension (FD) box counting, FD madogram and a windowed short-time Fourier transform with power spectrum density (PSD) calculation) were compared with each other and with the shape variation in the dataset. Analyses of suture shape demonstrate that the primary axis of variation captured attributes other than complexity, supporting the use of a complexity metric over raw shape data for sutural complexity analyses. Each approach captured different aspects of complexity. PSD successfully discriminates different sutural features, such as looping patterns and interdigitation amplitude and number, while SCI best-captured variation in interdigitation number alone. Therefore, future studies should consider the relevant attributes for their question when selecting a metric for comparative analysis of suture variation, function and evolution.
DOI: 10.6084/m9.figshare.12978949.v1
title: TableS5_WGCNATargetsWMotif.csv from Tissue-specific developmental regulation and isoform usage underlie the role of <i>doublesex</i> in sex differentiation and mimicry in <i>Papilio</i> swallowtails

description: List of genes co-expressed with dsx that contain dsx binding motif
DOI: 10.6084/m9.figshare.12978949
title: TableS5_WGCNATargetsWMotif.csv from Tissue-specific developmental regulation and isoform usage underlie the role of <i>doublesex</i> in sex differentiation and mimicry in <i>Papilio</i> swallowtails

description: List of genes co-expressed with dsx that contain dsx binding motif
DOI: 10.6084/m9.figshare.12978952
title: Tables2_dsx-transcriptome_SRASubmission.csv from Tissue-specific developmental regulation and isoform usage underlie the role of <i>doublesex</i> in sex differentiation and mimicry in <i>Papilio</i> swallowtails

description: Accession details for individual raw transcriptome sequences in the NCBI SRA database
DOI: 10.6084/m9.figshare.12978952.v1
title: Tables2_dsx-transcriptome_SRASubmission.csv from Tissue-specific developmental regulation and isoform usage underlie the role of <i>doublesex</i> in sex differentiation and mimicry in <i>Papilio</i> swallowtails

description: Accession details for individual raw transcriptome sequences in the NCBI SRA database
DOI: 10.6084/m9.figshare.12978958
title: TableS4_WGCNA.csv from Tissue-specific developmental regulation and isoform usage underlie the role of <i>doublesex</i> in sex differentiation and mimicry in <i>Papilio</i> swallowtails

description: Details of genes co-expressed with dsx in mimetic (female) wings, female abdomen, non-mimetic (male) wings and male abdomen
DOI: 10.6084/m9.figshare.12978958.v1
title: TableS4_WGCNA.csv from Tissue-specific developmental regulation and isoform usage underlie the role of <i>doublesex</i> in sex differentiation and mimicry in <i>Papilio</i> swallowtails

description: Details of genes co-expressed with dsx in mimetic (female) wings, female abdomen, non-mimetic (male) wings and male abdomen
DOI: 10.6084/m9.figshare.12978941
title: random_number.txt

description: <b>generate 1000 random numbers over the range 0-100</b>
DOI: 10.6084/m9.figshare.12978941.v1
title: random_number.txt

description: <b>generate 1000 random numbers over the range 0-100</b>
DOI: 10.6084/m9.figshare.12978974
title: Supporting data from Measuring friction at an interface using ultrasonic response

description: This file includes the data used in figures and tables in this paper and the data of contact nonlinearity measured at the interface from various contact pairs using nonlinear ultrasonic response in experiments.
DOI: 10.6084/m9.figshare.12978974.v1
title: Supporting data from Measuring friction at an interface using ultrasonic response

description: This file includes the data used in figures and tables in this paper and the data of contact nonlinearity measured at the interface from various contact pairs using nonlinear ultrasonic response in experiments.
DOI: 10.6084/m9.figshare.12978989
title: equation.txt

description: <b>generate new numbers from the original 1000 using the equation y=3x+6</b>
DOI: 10.6084/m9.figshare.12978989.v1
title: equation.txt

description: <b>generate new numbers from the original 1000 using the equation y=3x+6</b>
DOI: 10.6084/m9.figshare.12979006.v1
title: File S2 from Statistical modelling of bacterial promoter sequences for regulatory motif discovery with the help of transcriptome data: application to <i>Listeria monocytogenes</i>

description: Detailed information on the predicted regulons associated to each of the 40 stable motifs. Table in XLSX format.
DOI: 10.6084/m9.figshare.12979012.v1
title: File S1 from Statistical modelling of bacterial promoter sequences for regulatory motif discovery with the help of transcriptome data: application to <i>Listeria monocytogenes</i>

description: PWMs for the 40 stable motifs.
DOI: 10.6084/m9.figshare.12979006
title: File S2 from Statistical modelling of bacterial promoter sequences for regulatory motif discovery with the help of transcriptome data: application to <i>Listeria monocytogenes</i>

description: Detailed information on the predicted regulons associated to each of the 40 stable motifs. Table in XLSX format.
DOI: 10.6084/m9.figshare.12979012
title: File S1 from Statistical modelling of bacterial promoter sequences for regulatory motif discovery with the help of transcriptome data: application to <i>Listeria monocytogenes</i>

description: PWMs for the 40 stable motifs.
DOI: 10.6084/m9.figshare.12979018
title: File S3 from Statistical modelling of bacterial promoter sequences for regulatory motif discovery with the help of transcriptome data: application to <i>Listeria monocytogenes</i>

description: Most likely positions for the occurrences of the 40 stable motifs. Table in XLSX format.
DOI: 10.6084/m9.figshare.12979018.v1
title: File S3 from Statistical modelling of bacterial promoter sequences for regulatory motif discovery with the help of transcriptome data: application to <i>Listeria monocytogenes</i>

description: Most likely positions for the occurrences of the 40 stable motifs. Table in XLSX format.
DOI: 10.5281/zenodo.4037253
title: Wikidata Dump People?

description: RDF dump of wikidata produced with wdumps. <br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.5281/zenodo.4037252
title: Wikidata Dump People?

description: RDF dump of wikidata produced with wdumps. <br> View on wdumper <b>entity count</b>: 0, <b>statement count</b>: 0, <b>triple count</b>: 0
DOI: 10.6084/m9.figshare.12979024
title: Supplementary material part2 from The structure of autocatalytic networks, with application to early biochemistry

description: Composition of maxRAF and maxCAF obtained with the network of M. maripaludis with a single organic cofactor (NAD) in the food set
DOI: 10.6084/m9.figshare.12979024.v1
title: Supplementary material part2 from The structure of autocatalytic networks, with application to early biochemistry

description: Composition of maxRAF and maxCAF obtained with the network of M. maripaludis with a single organic cofactor (NAD) in the food set
DOI: 10.6084/m9.figshare.12979026.v1
title: Dataset Set2 from How quickly can we predict trimethoprim resistance using alchemical free energy methods?

description: Alchemical free energies for the simulations in Set2, as described in Table 1 of the paper.
DOI: 10.6084/m9.figshare.12979026
title: Dataset Set2 from How quickly can we predict trimethoprim resistance using alchemical free energy methods?

description: Alchemical free energies for the simulations in Set2, as described in Table 1 of the paper.