cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.11707143
title: MOESM1 of Expanded complement of Niemann-Pick type C2-like protein genes in Clonorchis sinensis suggests functions beyond sterol binding and transport

description: Additional file 1: Table S1. Clonorchis sinensis NPC2-like proteins (Korean and Chinese isolates) with homology to SWISS-PROT NPC2 proteins, NPC2-like proteins in the NCBI-nr database and/or conserved ML domain (PF02221). Table S2. Predicted functional annotation of 35 Korean and 32 Chinese Clonorchis sinensis NPC2-like proteins and nine SWISS-PROT NPC2 proteins using SignalP, SWISS-PROT, InterProScan and I-TASSER. For each NPC2-like protein, the best I-TASSER model is shown, including the associated C-score, estimated topology modelling (TM) score, root-mean-square deviation of atomic positions (RMSD), predicted function, as well as the most similar target in the PDB database. Predicted transcription in different developmental stages and adult tissues is shown as log2 counts per million.
DOI: 10.6084/m9.figshare.11707143.v1
title: MOESM1 of Expanded complement of Niemann-Pick type C2-like protein genes in Clonorchis sinensis suggests functions beyond sterol binding and transport

description: Additional file 1: Table S1. Clonorchis sinensis NPC2-like proteins (Korean and Chinese isolates) with homology to SWISS-PROT NPC2 proteins, NPC2-like proteins in the NCBI-nr database and/or conserved ML domain (PF02221). Table S2. Predicted functional annotation of 35 Korean and 32 Chinese Clonorchis sinensis NPC2-like proteins and nine SWISS-PROT NPC2 proteins using SignalP, SWISS-PROT, InterProScan and I-TASSER. For each NPC2-like protein, the best I-TASSER model is shown, including the associated C-score, estimated topology modelling (TM) score, root-mean-square deviation of atomic positions (RMSD), predicted function, as well as the most similar target in the PDB database. Predicted transcription in different developmental stages and adult tissues is shown as log2 counts per million.
DOI: 10.6084/m9.figshare.11706837
title: MOESM2 of Control of glutamate release by complexes of adenosine and cannabinoid receptors

description: Additional file 2. Data values 1. EC50 values from Additional file 1: Figure S1. Data values 2. EC50 and Emax values from Additional file 1: Figure S2. Data values 3. Values of cAMP formation from Fig. 5. Data values 4. Values of constitutive activation (cAMP formation) from Fig. 7.
DOI: 10.6084/m9.figshare.11706837.v1
title: MOESM2 of Control of glutamate release by complexes of adenosine and cannabinoid receptors

description: Additional file 2. Data values 1. EC50 values from Additional file 1: Figure S1. Data values 2. EC50 and Emax values from Additional file 1: Figure S2. Data values 3. Values of cAMP formation from Fig. 5. Data values 4. Values of constitutive activation (cAMP formation) from Fig. 7.
DOI: 10.6084/m9.figshare.11706834
title: MOESM1 of PSMA PET for primary lymph node staging of intermediate and high-risk prostate cancer: an expedited systematic review

description: Additional file 1. PubMed search (text file)
DOI: 10.6084/m9.figshare.11706834.v1
title: MOESM1 of PSMA PET for primary lymph node staging of intermediate and high-risk prostate cancer: an expedited systematic review

description: Additional file 1. PubMed search (text file)
DOI: 10.6084/m9.figshare.11706006
title: Proteome database of Carnobacterium divergens DSM20623

description: <i>Carnobacterium divergens</i> is a Gram-positive bacterium belonging to the family of lactic acid bacteria. Not known to be pathogenic in humans, <i>C. divergens</i> is one of the less studied microorganisms. This work sought to provide fundamental information of the bacterium through parsing the UniProt proteome of <i>C. divergens</i> DSM20623 using an in-house MATLAB proteome analysis software. The resulting proteome database comprises protein name, amino acid sequence, number of residues, molecular weight and nucleotide sequence of protein, and should serve as a useful resource for guiding the design of molecular cloning experiments aimed at deciphering the molecular processes occurring in this bacterium.<br><br>
DOI: 10.6084/m9.figshare.11706006.v1
title: Proteome database of Carnobacterium divergens DSM20623

description: <i>Carnobacterium divergens</i> is a Gram-positive bacterium belonging to the family of lactic acid bacteria. Not known to be pathogenic in humans, <i>C. divergens</i> is one of the less studied microorganisms. This work sought to provide fundamental information of the bacterium through parsing the UniProt proteome of <i>C. divergens</i> DSM20623 using an in-house MATLAB proteome analysis software. The resulting proteome database comprises protein name, amino acid sequence, number of residues, molecular weight and nucleotide sequence of protein, and should serve as a useful resource for guiding the design of molecular cloning experiments aimed at deciphering the molecular processes occurring in this bacterium.<br><br>
DOI: 10.6084/m9.figshare.11705445
title: HHI_csv_files.zip

description: HHI and price data by year and by country for elemental production worldwide taken from USGS mineral commodity yearbooks.
DOI: 10.6084/m9.figshare.11705436
title: ACCESS-DATASET

description: A dataset analyzing the cluster data from Alibaba
DOI: 10.6084/m9.figshare.11705436.v1
title: ACCESS-DATASET

description: A dataset analyzing the cluster data from Alibaba
DOI: 10.6084/m9.figshare.11704782
title: Supplementary files for "Urinary levels of Endocrine Disrupting Chemicals are Associated with Changes in the Peri-pubertal Epigenome" by Kristian Almstrup, Hanne Frederiksen, Anna-Maria Andersson and Anders Juul

description: Supplementary file 1 to 3.<br>
DOI: 10.6084/m9.figshare.11704782.v1
title: Supplementary files for "Urinary levels of Endocrine Disrupting Chemicals are Associated with Changes in the Peri-pubertal Epigenome" by Kristian Almstrup, Hanne Frederiksen, Anna-Maria Andersson and Anders Juul

description: Supplementary file 1 to 3.<br>
DOI: 10.26180/5e2a1a8d74be7
title: Community efficiency during succession: a test of MacArthur’s minimisation principle in phytoplankton communities

description: The dataset includes data used to test MacArthur minimisation principle in phytoplankton communities (Ghedini et al. 2020 Ecology). It includes data on: 1. cell size, abundance and biovolume of each phytoplankton species in the communities2. light captured by the communities3. rates of oxygen evolution4. phytoplankton mortality5. nutrient uptake6. summary of energy wastage<br>
DOI: 10.6084/m9.figshare.11704491
title: Report of Mutualistic Associations, Nutrients, and Carbon under eCO2 (ROMANCE) v1.0 dataset

description: Data from elevated CO2 experiments on the effect of elevated CO2 on soil carbon storage and plant biomass<br>
DOI: 10.6084/m9.figshare.11704431
title: Patient 8

description: Atrial Tachycardia patient #2Part 1 contains the raw ultrasound RF dataPart 2 contains the B-mode, multi-2D and 3D-rendered EWI activation timings
DOI: 10.6084/m9.figshare.11704491.v2
title: Dataset of soil and biomass carbon responses to elevated CO2

description: Data from elevated CO2 experiments on the effect of elevated CO2 on soil carbon storage and plant biomass<br>
DOI: 10.6084/m9.figshare.11704491.v3
title: NAMASTE v1.0: a dataset to study the role of Nitrogen Availability and Mutualistic Associations in Soils and Terrestrial Ecosystems under elevated CO2.

description: Data from elevated CO2 experiments on the effect of elevated CO2 on soil carbon storage and plant biomass<br>
DOI: 10.6084/m9.figshare.11704419
title: Patient 7

description: Atrial Tachycardia patient #1Part 1 contains the raw ultrasound RF dataPart 2 contains the B-mode, multi-2D and 3D-rendered EWI activation timings
DOI: 10.6084/m9.figshare.11704491.v4
title: NAMASTE v1.0: a dataset to study the role of Nitrogen Availability and Mutualistic Associations in Soils and Terrestrial Ecosystems under elevated CO2.

description: Data from elevated CO2 experiments on the effect of elevated CO2 on soil carbon storage and plant biomass<br>
DOI: 10.6084/m9.figshare.11704491.v5
title: NAMASTE v1.0: a dataset to study the role of Nutrient Availability and Mutualistic Associations in Soils and Terrestrial Ecosystems under elevated CO2.

description: Data from elevated CO2 experiments on the effect of elevated CO2 on soil carbon storage and plant biomass<br>
DOI: 10.6084/m9.figshare.11704491.v6
title: NAMASTE v1.0: a dataset to study the role of Nutrient Availability and Mutualistic Associations in Soils and Terrestrial Ecosystems under elevated CO2.

description: Data from elevated CO2 experiments on the effect of elevated CO2 on soil carbon storage and plant biomass<br>
DOI: 10.6084/m9.figshare.11704266
title: esprit2_comparison.tar.gz

description: Comparison with Ensembl and ESPRIT.
DOI: 10.6084/m9.figshare.11704266.v1
title: esprit2_comparison.tar.gz

description: Comparison with Ensembl and ESPRIT.
DOI: 10.6084/m9.figshare.11704257
title: esprit2_predictions_wheat.tar.gz

description: Predictions on the whole putative wheat genome.
DOI: 10.6084/m9.figshare.11704257.v1
title: esprit2_predictions_wheat.tar.gz

description: Predictions on the whole putative wheat genome.
DOI: 10.6084/m9.figshare.11704245
title: Patient 6

description: Atrial Flutter patient #2Part 1 contains the raw ultrasound RF dataPart 2 contains the B-mode, multi-2D and 3D-rendered EWI activation timings
DOI: 10.6084/m9.figshare.11704248
title: esprit2_simulations.tar.gz

description: Results on simulated fragmentation.
DOI: 10.6084/m9.figshare.11704248.v1
title: esprit2_simulations.tar.gz

description: Results on simulated fragmentation.
DOI: 10.6084/m9.figshare.11704239
title: Patient 4

description: Premature Ventricular Contraction patient #2Part 1 contains the raw ultrasound RF dataPart 2 contains the B-mode, multi-2D and 3D-rendered EWI activation timings
DOI: 10.6084/m9.figshare.11704242
title: Patient 5

description: Atrial Flutter patient #1Part 1 contains the raw ultrasound RF dataPart 2 contains the B-mode, multi-2D and 3D-rendered EWI activation timings
DOI: 10.6084/m9.figshare.11704194
title: Raw data from "Novel Branch Centrality Measures for Electrical Power Systems Considering Both Load-serving and Circulating Currents"

description: Just the messy data underlying this paper<br>
DOI: 10.6084/m9.figshare.11704236.v2
title: Bayesian Inference for Regression Copulas

description: We propose a new semiparametric distributional regression smoother that is based on a copula decomposition of the joint distribution of the vector of response values. The copula is high-dimensional and constructed by inversion of a pseudo regression, where the conditional mean and variance are semiparametric functions of covariates modeled using regularized basis functions. By integrating out the basis coefficients, an implicit copula process on the covariate space is obtained, which we call a “regression copula.” We combine this with a nonparametric margin to define a copula model, where the entire distribution—including the mean and variance—of the response is a smooth semiparametric function of the covariates. The copula is estimated using both Hamiltonian Monte Carlo and variational Bayes; the latter of which is scalable to high dimensions. Using real data examples and a simulation study, we illustrate the efficacy of these estimators and the copula model. In a substantive example, we estimate the distribution of half-hourly electricity spot prices as a function of demand and two time covariates using radial bases and horseshoe regularization. The copula model produces distributional estimates that are locally adaptive with respect to the covariates, and predictions that are more accurate than those from benchmark models. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.11704194.v1
title: Raw data from "Novel Branch Centrality Measures for Electrical Power Systems Considering Both Load-serving and Circulating Currents"

description: Just the messy data underlying this paper<br>
DOI: 10.6084/m9.figshare.11704119
title: MetaDeformability Dataset

description: This datasets contains results presented in the following manuscript:<i>Urbanska, M., Muñoz, H.E.</i> et al., <i>Nat Methods</i> <b>17</b>, 587–593 (2020) <b><i>A comparison of microfluidic methods for high-throughput cell deformability measurements</i></b>https://doi.org/10.1038/s41592-020-0818-8<br><br><b> Abstract </b>The mechanical phenotype of a cell is an inherent biophysical marker of its state and function, with potential value in clinical diagnostics. Several microfluidic-based methods developed in recent years have enabled single-cell mechanophenotyping at throughputs comparable to flow cytometery. Here we present a highly standardized cross-laboratory study comparing three leading microfluidic-based approaches to measure cell mechanical phenotype: constriction-based deformability cytometry (cDC), shear flow deformability cytometry (sDC), and extensional flow deformability cytometry (xDC). We show that all three methods detect cell deformability changes induced by exposure to altered osmolarity. However, a dose-dependent deformability increase upon latrunculin B-induced actin disassembly was detected only with cDC and sDC, which suggests that when exposing cells to the higher strain rate imposed by xDC, other cell components dominate the response. The direct comparison presented here serves to unify deformability cytometry methods and provides context for the interpretation of deformability measurements performed using different platforms. <br> <b>Further information</b>The cross-laboratory study presented here focuses on comparing representatives of the three deformability cytometry methods: (i) an SMR-based cDC variant [1], (ii) RT-DC [2] as an example of sDC, (iii) DC [3] as an example of xDC.<br> <b>References</b>[1] Byun et al., 2013. Characterizing deformability and surface friction of cancer cells. PNAS 110(19): 7580-7585, https://doi.org/10.1073/pnas.1218806110[2] Otto et al., 2015. Real-time deformability cytometry: on-the-fly cell mechanical phenotyping. Nature Methods 12(3): 199-202, https://doi.org/10.1038/nmeth.3281[3] Gossett et al., 2012. Hydrodynamic stretching of single cells for large population mechanical phenotyping. PNAS 109(20): 7630-7635, https://doi.org/10.1073/pnas.1200107109<br> <b>Analysis codes</b>The accompanying analysis scripts necessary to generate the results presented in the manuscript from the dataset uploaded here are available on GitHub:https://github.com/dicarlo-lab/metadeformability<br><br>
DOI: 10.6084/m9.figshare.11704236.v3
title: Bayesian Inference for Regression Copulas

description: We propose a new semiparametric distributional regression smoother that is based on a copula decomposition of the joint distribution of the vector of response values. The copula is high-dimensional and constructed by inversion of a pseudo regression, where the conditional mean and variance are semiparametric functions of covariates modeled using regularized basis functions. By integrating out the basis coefficients, an implicit copula process on the covariate space is obtained, which we call a “regression copula.” We combine this with a nonparametric margin to define a copula model, where the entire distribution—including the mean and variance—of the response is a smooth semiparametric function of the covariates. The copula is estimated using both Hamiltonian Monte Carlo and variational Bayes; the latter of which is scalable to high dimensions. Using real data examples and a simulation study, we illustrate the efficacy of these estimators and the copula model. In a substantive example, we estimate the distribution of half-hourly electricity spot prices as a function of demand and two time covariates using radial bases and horseshoe regularization. The copula model produces distributional estimates that are locally adaptive with respect to the covariates, and predictions that are more accurate than those from benchmark models. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.11704236.v4
title: Bayesian Inference for Regression Copulas

description: We propose a new semiparametric distributional regression smoother that is based on a copula decomposition of the joint distribution of the vector of response values. The copula is high-dimensional and constructed by inversion of a pseudo regression, where the conditional mean and variance are semiparametric functions of covariates modeled using regularized basis functions. By integrating out the basis coefficients, an implicit copula process on the covariate space is obtained, which we call a “regression copula.” We combine this with a nonparametric margin to define a copula model, where the entire distribution—including the mean and variance—of the response is a smooth semiparametric function of the covariates. The copula is estimated using both Hamiltonian Monte Carlo and variational Bayes; the latter of which is scalable to high dimensions. Using real data examples and a simulation study, we illustrate the efficacy of these estimators and the copula model. In a substantive example, we estimate the distribution of half-hourly electricity spot prices as a function of demand and two time covariates using radial bases and horseshoe regularization. The copula model produces distributional estimates that are locally adaptive with respect to the covariates, and predictions that are more accurate than those from benchmark models. Supplementary materials for this article are available online.
DOI: 10.6084/m9.figshare.11704119.v1
title: MetaDeformability Dataset

description: This datasets contains results presented in the manuscript published in 2020 by <i>Urbanska, Muñoz</i> et al.:<br><b><i>A comparison of microfluidic methods for high-throughput cell deformability measurements</i></b>https://doi.org/…<b><br> Abstract </b>The mechanical phenotype of a cell is an inherent biophysical marker of its state and function, with potential value in clinical diagnostics. Several microfluidic-based methods developed in recent years have enabled single-cell mechanophenotyping at throughputs comparable to flow cytometery. Here we present a highly standardized cross-laboratory study comparing three leading microfluidic-based approaches to measure cell mechanical phenotype: constriction-based deformability cytometry (cDC), shear flow deformability cytometry (sDC), and extensional flow deformability cytometry (xDC). We show that all three methods detect cell deformability changes induced by exposure to altered osmolarity. However, a dose-dependent deformability increase upon latrunculin B-induced actin disassembly was detected only with cDC and sDC, which suggests that when exposing cells to the higher strain rate imposed by xDC, other cell components dominate the response. The direct comparison presented here serves to unify deformability cytometry methods and provides context for the interpretation of deformability measurements performed using different platforms. <br> <b>Further information</b>The cross-laboratory study presented here focuses on comparing representatives of the three deformability cytometry methods: (i) an SMR-based cDC variant [1], (ii) RT-DC [2] as an example of sDC, (iii) DC [3] as an example of xDC.<br> <b>References</b>[1] Byun et al., 2013. Characterizing deformability and surface friction of cancer cells. PNAS 110(19): 7580-7585, https://doi.org/10.1073/pnas.1218806110[2] Otto et al., 2015. Real-time deformability cytometry: on-the-fly cell mechanical phenotyping. Nature Methods 12(3): 199-202, https://doi.org/10.1038/nmeth.3281[3] Gossett et al., 2012. Hydrodynamic stretching of single cells for large population mechanical phenotyping. PNAS 109(20): 7630-7635, https://doi.org/10.1073/pnas.1200107109<br> <b>Analysis codes</b>The accompanying analysis scripts necessary to generate the results presented in the manuscript from the dataset uploaded here are available on GitHub:https://github.com/dicarlo-lab/metadeformability<br>
DOI: 10.6084/m9.figshare.11704119.v2
title: MetaDeformability Dataset

description: This datasets contains results presented in the following manuscript:<i>Urbanska, M., Muñoz, H.E.</i> et al., <i>Nat Methods</i> <b>17</b>, 587–593 (2020) <b><i>A comparison of microfluidic methods for high-throughput cell deformability measurements</i></b>https://doi.org/10.1038/s41592-020-0818-8<br><br><b> Abstract </b>The mechanical phenotype of a cell is an inherent biophysical marker of its state and function, with potential value in clinical diagnostics. Several microfluidic-based methods developed in recent years have enabled single-cell mechanophenotyping at throughputs comparable to flow cytometery. Here we present a highly standardized cross-laboratory study comparing three leading microfluidic-based approaches to measure cell mechanical phenotype: constriction-based deformability cytometry (cDC), shear flow deformability cytometry (sDC), and extensional flow deformability cytometry (xDC). We show that all three methods detect cell deformability changes induced by exposure to altered osmolarity. However, a dose-dependent deformability increase upon latrunculin B-induced actin disassembly was detected only with cDC and sDC, which suggests that when exposing cells to the higher strain rate imposed by xDC, other cell components dominate the response. The direct comparison presented here serves to unify deformability cytometry methods and provides context for the interpretation of deformability measurements performed using different platforms. <br> <b>Further information</b>The cross-laboratory study presented here focuses on comparing representatives of the three deformability cytometry methods: (i) an SMR-based cDC variant [1], (ii) RT-DC [2] as an example of sDC, (iii) DC [3] as an example of xDC.<br> <b>References</b>[1] Byun et al., 2013. Characterizing deformability and surface friction of cancer cells. PNAS 110(19): 7580-7585, https://doi.org/10.1073/pnas.1218806110[2] Otto et al., 2015. Real-time deformability cytometry: on-the-fly cell mechanical phenotyping. Nature Methods 12(3): 199-202, https://doi.org/10.1038/nmeth.3281[3] Gossett et al., 2012. Hydrodynamic stretching of single cells for large population mechanical phenotyping. PNAS 109(20): 7630-7635, https://doi.org/10.1073/pnas.1200107109<br> <b>Analysis codes</b>The accompanying analysis scripts necessary to generate the results presented in the manuscript from the dataset uploaded here are available on GitHub:https://github.com/dicarlo-lab/metadeformability<br><br>
DOI: 10.6084/m9.figshare.11704071
title: ENABLING SMARTPHONE PUSH NOTIFICATIONS: THE EFFECT OF A FRAMED OPT-IN REQUEST

description: This dataset allow to examine the influence of two different approaches for framing this opt-in request based on the likelihood of the user accepting it: focusing on the experiential benefits the user would eventually receive through the information provided by the push notifications (moderated by the personal involvement with the app) and focusing on the social proof aspect, i.e. the behaviour of the majority of app users (moderated by the user’s susceptibility to interpersonal influence). Variables are 7-Likert scales.
DOI: 10.6084/m9.figshare.11704071.v1
title: A BETTER WAY TO GET AN OPT IN: THE EFFECT OF A FRAMED OPT-IN REQUEST

description: This dataset allow to examine the influence of two different approaches for framing this opt-in request based on the likelihood of the user accepting it: focusing on the experiential benefits the user would eventually receive through the information provided by the push notifications (moderated by the personal involvement with the app) and focusing on the social proof aspect, i.e. the behaviour of the majority of app users (moderated by the user’s susceptibility to interpersonal influence). Variables are 7-Likert scales.