cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.13095380
title: Data for "Genetic erosion reduces biomass temporal stability in wild fish populations."

description: "Prunier et al._Biomass_Genetic_Environmental data.txt": Data used in path analyses. For each STATION, the dataset provides : - sample WEIGHTs used in causal models, - total fish biomass BIOM, - biomass stability BSTA, - per capita mean biomass pcBIOM, - per capita mean biomass stability pcBSTA, - bottleneck probability BOT, - intraspecific genetic diversity IGD, - upstream-downstream gradient UGD - eutrophic gradient EG. Interactions are obtained as the cross-products of corresponding variables. <br> "Prunier et al._R-code.R" R-code used to perform path analyses and produce figures 2 to 4. <br> "SEM_interplot.R" Custom R-code to predict endogeneous variables with 95% confidence intervals (to be used with outputs from lavaan::parameterEstimates) <br> "Prunier_et_al._GeneticData.rda" Raw genetic data used to compute IGD, in .rda format. Loading this file in R opens "GeneticData", a list-object composed of three sublists (one for each species), each containing raw microsatellite individual genotypes in .genind format (R-library adegenet) and Poolseq population-based SNP allelic frequencies. <br> "Prunier et al._RawBiomassData.txt" For each station, each species and each sampling session (Year and Date provided), raw biomass (in g.m-²) and density (in number of individuals per m²) data. <br> "Prunier et al._RawEnvironmentalData.txt" For each station, environmental data (averaged over months and years for chemicals).
DOI: 10.6084/m9.figshare.13095380.v8
title: Data for "Genetic erosion reduces biomass temporal stability in wild fish populations."

description: "Prunier et al._Biomass_Genetic_Environmental data.txt": Data used in path analyses. For each STATION, the dataset provides : - sample WEIGHTs used in causal models, - total fish biomass BIOM, - biomass stability BSTA, - per capita mean biomass pcBIOM, - per capita mean biomass stability pcBSTA, - bottleneck probability BOT, - intraspecific genetic diversity IGD, - upstream-downstream gradient UGD - eutrophic gradient EG. Interactions are obtained as the cross-products of corresponding variables. <br> "Prunier et al._R-code.R" R-code used to perform path analyses and produce figures 2 to 4. <br> "SEM_interplot.R" Custom R-code to predict endogeneous variables with 95% confidence intervals (to be used with outputs from lavaan::parameterEstimates) <br> "Prunier_et_al._GeneticData.rda" Raw genetic data used to compute IGD, in .rda format. Loading this file in R opens "GeneticData", a list-object composed of three sublists (one for each species), each containing raw microsatellite individual genotypes in .genind format (R-library adegenet) and Poolseq population-based SNP allelic frequencies. <br> "Prunier et al._RawBiomassData.txt" For each station, each species and each sampling session (Year and Date provided), raw biomass (in g.m-²) and density (in number of individuals per m²) data. <br> "Prunier et al._RawEnvironmentalData.txt" For each station, environmental data (averaged over months and years for chemicals).
DOI: 10.34740/kaggle/dsv/5938346
title: Global Genomic Neurofibromatosis Neoplasia
DOI: 10.5281/zenodo.8042524
title: Georgia Interview Transcripts

description: Transcripts of interviews in both Georgian and Russian taken by Costanza Curro and Judith Pallot between January 2020 and November 2021 in Georgia. The population includes former prisoners, current prisoners, employees of Ministry of Justice.
DOI: 10.5281/zenodo.8042523
title: Georgia Interview Transcripts

description: Transcripts of interviews in both Georgian and Russian taken by Costanza Curro and Judith Pallot between January 2020 and November 2021 in Georgia. The population includes former prisoners, current prisoners, employees of Ministry of Justice.
DOI: 10.17617/4.cb
title: Systematic modulation of the lipid composition enables the tuning of liposome cellular uptake

description: Mateos Maroto, A., Gai, M., Brückner, M., da Costa Marques, R., Harley, I., Simon, J., et al. (2023). Systematic modulation of the lipid composition enables the tuning of liposome cellular uptake. Acta Biomaterialia, 158, 463-474. doi:10.1016/j.actbio.2022.12.058
DOI: 10.6084/m9.figshare.22710187.v1
title: Anolis lizard diet.xlsx

description: This data comprehend the diet of six species of lizards of the genus <em>Anolis</em> in the Yasuní National Park. The dataset includes: species, lizard code, category of item found in lizard stomach, prey length, prey width and volume. Sampling was carried out for 70 days during June, July, August, and September 2012 in Yasuní National Park, Orellana Province, Ecuador, on the southern bank of the Tiputini River (76° 24´ 1.8 ´´ W; 0° 40´ 16.7´´ S). <br>
DOI: 10.6084/m9.figshare.22710187
title: Anolis lizard diet.xlsx

description: This data comprehend the diet of six species of lizards of the genus <em>Anolis</em> in the Yasuní National Park. The dataset includes: species, lizard code, category of item found in lizard stomach, prey length, prey width and volume. Sampling was carried out for 70 days during June, July, August, and September 2012 in Yasuní National Park, Orellana Province, Ecuador, on the southern bank of the Tiputini River (76° 24´ 1.8 ´´ W; 0° 40´ 16.7´´ S). <br>
DOI: 10.5281/zenodo.8040533
title: Cuvette Centrale subset region - monthly water level data

description: These data were derived using the methods described in the paper: https://www.mdpi.com/2072-4292/15/12/3099 The filenames beginning with 'WL_monthly' contain the monthly minimum, maximum, mean, and standard deviation of the estimated daily water levels for a subset of the Cuvette Centrale region in the Central Congo Basin. The filenames beginning with just 'WL_' contain the minimum, maximum, mean, and standard deviation of the estimated daily water levels over the 20-month study period, March 2019 to October 2020.
DOI: 10.5281/zenodo.8040532
title: Cuvette Centrale subset region - monthly water level data

description: These data were derived using the methods described in the paper: https://www.mdpi.com/2072-4292/15/12/3099 The filenames beginning with 'WL_monthly' contain the monthly minimum, maximum, mean, and standard deviation of the estimated daily water levels for a subset of the Cuvette Centrale region in the Central Congo Basin. The filenames beginning with just 'WL_' contain the minimum, maximum, mean, and standard deviation of the estimated daily water levels over the 20-month study period, March 2019 to October 2020.
DOI: 10.5281/zenodo.6367142
title: tgEDMD: Approximation of the Kolmogorov Operator in Tensor Train Format

description: Data sets required to re-produce numerical examples in Lücke, M. and Nüske, F. <em>tgEDMD: Approximation of the Kolmogorov Operator in Tensor Train Format</em>, arxiv 2111.09606 (2021) <strong>Lemon Slice Example:</strong> - Simulation_LS_Full.npy: Complete set of ten independent simulations, at time spacing 10^{-3}, each comprising 300,000 steps. - Simulation_LS_delta_100.npy: Downsampled set of ten independent simulations, at time spacing 10^{-1}, each comprising 3,000 steps. <strong>Deca Alanine Example:</strong> - Dih_Traj_*.npy: Trajectories of sixteen backbone dihedral angles for 50,000 steps each, at 10ps time spacing. - Dih_Jac_Traj_*.npy: Trajectories of Jacobian matrices for sixteen backbone dihedral angles. Derivatives are taken with respect to the Euclidean coordinates of 26 atoms required for the computation of the dihedrals, and evaluated for 50,000 steps each, at 10ps time spacing. - Timescales_MSM.npy: Implied timescales computed by MSM analysis of the same data set. Contains the first 499 timescales computed using seven different MSM lag times.
description: This research was partially funded by Deutsche Forschungsgemeinschaft (DFG) under Germany's Excellence Strategy via the Berlin Mathematics Research Center MATH+ (EXC- 2046/1 project ID: 390685689).
DOI: 10.5281/zenodo.6367143
title: tgEDMD: Approximation of the Kolmogorov Operator in Tensor Train Format

description: Data sets required to re-produce numerical examples in Lücke, M. and Nüske, F. <em>tgEDMD: Approximation of the Kolmogorov Operator in Tensor Train Format</em>, arxiv 2111.09606 (2021) <strong>Lemon Slice Example:</strong> - Simulation_LS_Full.npy: Complete set of ten independent simulations, at time spacing 10^{-3}, each comprising 300,000 steps. - Simulation_LS_delta_100.npy: Downsampled set of ten independent simulations, at time spacing 10^{-1}, each comprising 3,000 steps. <strong>Deca Alanine Example:</strong> - Dih_Traj_*.npy: Trajectories of sixteen backbone dihedral angles for 50,000 steps each, at 10ps time spacing. - Dih_Jac_Traj_*.npy: Trajectories of Jacobian matrices for sixteen backbone dihedral angles. Derivatives are taken with respect to the Euclidean coordinates of 26 atoms required for the computation of the dihedrals, and evaluated for 50,000 steps each, at 10ps time spacing. - Timescales_MSM.npy: Implied timescales computed by MSM analysis of the same data set. Contains the first 499 timescales computed using seven different MSM lag times.
description: This research was partially funded by Deutsche Forschungsgemeinschaft (DFG) under Germany's Excellence Strategy via the Berlin Mathematics Research Center MATH+ (EXC- 2046/1 project ID: 390685689).
DOI: 10.14278/rodare.938
title: Example Project Plan generated by HELIPORT

description: This dataset contains the metadata for an example project generated using the project export button in our prototype scientific project lifecycle and workflow management system HELIPORT (HELmholtz ScIentific Project WORkflow PlaTform). The metadata schema is still under development and this entry will be updated to reflect further developments.
DOI: 10.25345/c5wp9th5z
title: MassIVE MSV000092171 - TGFbeta released by Schwann cells increases Cholangiocarcinoma malignant features inducing migration and proliferation in an in vitro model of perineural invasion
title: 30 ug of proteins extracted from each sample were loaded on a pre cast acrylamide gradient gel and run for about 10 minutes in MOPS buffer. Stained bands were excised, destained in ammonium bicarbonate/water/ acetonitrile, and after the reduction and alkylation of cysteine residues, an enzymatic digestion with trypsin was performed at 37C O.N. After digestion, the resulted peptide solution was removed from bands and stored in a new tube; a peptide extraction step was done with a Acetonitrile/Formic acid 2.5% (50:50, v:v) solution in order to extract peptides entirely from bands; this solution was collected with the previous O.N. digested mixtures. Then, the mixture was dried down in a vacuum centrifuge and resuspended in 100 uL of a solution containing 95% water, 5% acetonitrile, and 0.1% formic acid. 5uL of the resulted peptide solution was injected in an Ultimate 3000 UHPLC (Dionex, Thermo Fisher Scientific) coupled with an Orbitrap Fusion Tribrid mass spectrometer (Thermo Fisher Scientific, CA, United States). Peptides were desalted on a trap column (Acclaim PepMap 100 C18, Thermo Fisher Scientific) and then separated on a 20 cm long silica capillary (Silica Tips FS 360 75 8, New Objective, MA, United States), packed in house with a C18, 1.9 um, 100 Angstrom resin (Michrom BioResources, CA, United States). The analytical separation was run for 180 min using a gradient of buffer A (95% water, 5% acetonitrile, and 0.1% formic acid) and buffer B (95% acetonitrile, 5% water, and 0.1% formic acid). The chromatographic starting point was 5% of buffer B, in 5 minutes B rose to 6% , in 130 minutes to 32%, after 25 minutes to 55% and in 4 minutes up to 80% of B. Full scan MS data were acquired in the 350 1,550 m/z range in the Orbitrap with 120K resolution. Data dependent acquisition was performed in top speed mode (3 s long maximum total cycle): the most intense precursors were selected through a monoisotopic precursor selection (MIPS) filter and with charge &gt;1, quadrupole isolated and fragmented by higher energy collision dissociation (HCD) (32% collision energy). Fragment ions were analyzed in the ion trap with rapid scan rate. Raw data were analyzed by Proteome Discoverer 2.4 (Thermo Fisher Scientific) using the Homo Sapiens database from UniProtKB/Swiss Prot database. Spectral matches were filtered using Percolator node, based on q values, with 1% false discovery rate (FDR). Only master proteins were taken into account and only specific trypsin cleavages with two miscleavages were admitted. Cysteine carbamydomethylation was set as static modification, while methionine oxidation and N acetylation on protein terminus were set as variable modifications. 15 ppm and 0.6 Da tolerance were considered for MS an MS /MS data assignment, respectively. Quantification was based on precursor intensity of unique and razor peptides using match between runs option.
DOI: 10.5281/zenodo.8042664
title: SeisSol Examples TPV33 mesh file

description: This mesh file is being used to run the SCEC benchmark TPV33 with SeisSol. I have used the scripts in https://github.com/SeisSol/Examples/commit/2158653e100100c1570cbd5dbdc7172719762753 to create the mesh.
DOI: 10.5281/zenodo.6856524
title: Surface Survey and Legacy Data in the Upper Plain of the Heraion of Perachora: The Perachora Peninsula Archaeological Project 2020 [Digital Supplement]

description: <strong>The digital Supplement </strong>contains figures in original size (TIFF) & digital data (SHP, CSV). The data can be also found in the linked GitHub repository https://github.com/sdam-au/perachora-medit-arch/. <strong>Abstract</strong> The Perachora Peninsula Archaeological Project held its first season of intensive surface survey from 12 January to 2 February 2020, during which time we focused on the region called the Upper Plain, situated above the sanctuary of Hera, which was in use from the 8th to the 2nd century BC. The nature of this area has been disputed, with Humfry Payne seeing it as a substantial town, while Richard Tomlinson referred to it as “a sporadic scatter of structures.” In order to clarify the nature of the settlement we employed a two-pronged effort: first to verify and document the legacy data in Tomlinson’s plan of the area, and second to conduct intensive surface survey from the boundary of the sanctuary to Lake Vouliagmeni. Within three weeks, our teams measured, photographed, and took the coordinates of nearly all the structures on Tomlinson’s plan, which included domestic structures, a small temple, and an extensive waterworks system, and several that had not been previously recorded. Building A 1 and the Fountain House were cleared and recorded using photogrammetry. The survey’s finds informed our legacy data verification efforts. Densities across all land types were high: nearly 23,000 artefacts were counted, and all but nine survey units produced artefacts. A preliminary analysis of the ceramics indicates a consistent habitation from the Archaic through the Classical period. Concentrations of miniature votives and fine wares were also found on hillsides, possibly indicating open-air shrines. Our work also highlights the need to conserve the structures in the Upper Plain.<br>
DOI: 10.5281/zenodo.8042663
title: SeisSol Examples TPV33 mesh file

description: This mesh file is being used to run the SCEC benchmark TPV33 with SeisSol. I have used the scripts in https://github.com/SeisSol/Examples/commit/2158653e100100c1570cbd5dbdc7172719762753 to create the mesh.
DOI: 10.5281/zenodo.6856523
title: Surface Survey and Legacy Data in the Upper Plain of the Heraion of Perachora: The Perachora Peninsula Archaeological Project 2020 [Digital Supplement with updated polygons from 2020]

description: <strong>The digital Supplement </strong>contains figures in original size (TIFF) & digital data (SHP, CSV). The data can be also found in the linked GitHub repository https://github.com/sdam-au/perachora-medit-arch/. <strong>Abstract</strong> The Perachora Peninsula Archaeological Project held its first season of intensive surface survey from 12 January to 2 February 2020, during which time we focused on the region called the Upper Plain, situated above the sanctuary of Hera, which was in use from the 8th to the 2nd century BC. The nature of this area has been disputed, with Humfry Payne seeing it as a substantial town, while Richard Tomlinson referred to it as “a sporadic scatter of structures.” In order to clarify the nature of the settlement we employed a two-pronged effort: first to verify and document the legacy data in Tomlinson’s plan of the area, and second to conduct intensive surface survey from the boundary of the sanctuary to Lake Vouliagmeni. Within three weeks, our teams measured, photographed, and took the coordinates of nearly all the structures on Tomlinson’s plan, which included domestic structures, a small temple, and an extensive waterworks system, and several that had not been previously recorded. Building A 1 and the Fountain House were cleared and recorded using photogrammetry. The survey’s finds informed our legacy data verification efforts. Densities across all land types were high: nearly 23,000 artefacts were counted, and all but nine survey units produced artefacts. A preliminary analysis of the ceramics indicates a consistent habitation from the Archaic through the Classical period. Concentrations of miniature votives and fine wares were also found on hillsides, possibly indicating open-air shrines. Our work also highlights the need to conserve the structures in the Upper Plain.
DOI: 10.5281/zenodo.8042635
title: Surface Survey and Legacy Data in the Upper Plain of the Heraion of Perachora: The Perachora Peninsula Archaeological Project 2020 [Digital Supplement with updated polygons from 2020]

description: <strong>The digital Supplement </strong>contains figures in original size (TIFF) & digital data (SHP, CSV). The data can be also found in the linked GitHub repository https://github.com/sdam-au/perachora-medit-arch/. <strong>Abstract</strong> The Perachora Peninsula Archaeological Project held its first season of intensive surface survey from 12 January to 2 February 2020, during which time we focused on the region called the Upper Plain, situated above the sanctuary of Hera, which was in use from the 8th to the 2nd century BC. The nature of this area has been disputed, with Humfry Payne seeing it as a substantial town, while Richard Tomlinson referred to it as “a sporadic scatter of structures.” In order to clarify the nature of the settlement we employed a two-pronged effort: first to verify and document the legacy data in Tomlinson’s plan of the area, and second to conduct intensive surface survey from the boundary of the sanctuary to Lake Vouliagmeni. Within three weeks, our teams measured, photographed, and took the coordinates of nearly all the structures on Tomlinson’s plan, which included domestic structures, a small temple, and an extensive waterworks system, and several that had not been previously recorded. Building A 1 and the Fountain House were cleared and recorded using photogrammetry. The survey’s finds informed our legacy data verification efforts. Densities across all land types were high: nearly 23,000 artefacts were counted, and all but nine survey units produced artefacts. A preliminary analysis of the ceramics indicates a consistent habitation from the Archaic through the Classical period. Concentrations of miniature votives and fine wares were also found on hillsides, possibly indicating open-air shrines. Our work also highlights the need to conserve the structures in the Upper Plain.
DOI: 10.5281/zenodo.8042638
title: Datos brutos pertenecientes al estudio "Los datos abiertos en las publicaciones científicas en educación"

description: Datos brutos pertenecientes al estudio "Los datos abiertos en las publicaciones científicas en educación". Análisis de la información suplementaria y de los datos brutos de investigación en Ciencias de la Educación como motor del cambio social. Años 2021-2022.
DOI: 10.5281/zenodo.8042639
title: Datos brutos pertenecientes al estudio "Los datos abiertos en las publicaciones científicas en educación"

description: Datos brutos pertenecientes al estudio "Los datos abiertos en las publicaciones científicas en educación". Análisis de la información suplementaria y de los datos brutos de investigación en Ciencias de la Educación como motor del cambio social. Años 2021-2022.
DOI: 10.5281/zenodo.8042132
title: Prostate MRI clinically significant cancer

description: This data set is part of the public development data for the 2023 Automated Universal Classification Challenge (AUC23). The data set concerns clinically significant prostate cancer classification on bi-parametric magnetic resonance imaging (bpMRI) and was derived from the Prostate Imaging: Cancer AI (PI-CAI) challenge's public training and development dataset (v2.0). The data set was originally introduced and described by Saha et al. (2022), and no images or patient information were added. Data was restructured in compliance with the AUC23 challenge format. The data set contains 1500 anonymized prostate bpMRI scans from 1476 patients acquired between 2012-2021 at three centers (Radboud University Medical Center, University Medical Center Groningen, Ziekenhuis Groep Twente) based in The Netherlands. Images are 4D tensors: 0: 3D Axial T2-weighted imaging (T2W) 1: 3D Axial apparent diffusion coefficient maps (ADC) 2: 3D Axial high b-value (≥ 1000 s/mm2) diffusion-weighted imaging (HBV) Classification labels: 0: Benign or indolent prostate cancer 1: Clinically significant prostate cancer (csPCa) Folder structure: imagesTr (root folder with all patients and studies)<br> ├── 10417_1000424_0000.mha (axial T2W imaging for study 1000424)<br> ├── 10417_1000424_0001.mha (axial ADC imaging for study 1000424)<br> ├── 10417_1000424_0002.mha (axial HBV imaging for study 1000424)<br> ├── ...<br> ├── 11251_1001274_0000.mha (axial T2W imaging for study 1001274)<br> ├── 11251_1001274_0001.mha (axial ADC imaging for study 1001274)<br> ├── 11251_1001274_0002.mha (axial HBV imaging for study 1001274)<br> ├── ... Please cite the following article if you are using the PI-CAI: Public Training and Development Dataset: <pre><code>A. Saha, J. J. Twilt, J. S. Bosma, B. van Ginneken, D. Yakar, M. Elschot, J. Veltman, J. J. Fütterer, M. de Rooij, H. Huisman, "Artificial Intelligence and Radiologists at Prostate Cancer Detection in MRI: The PI-CAI Challenge (Study Protocol)", DOI: 10.5281/zenodo.6522364 </code></pre>
description: {"references": ["Saha, Anindo, Twilt, Jasper Jonathan, Bosma, Joeran Sander, van Ginneken, Bram, Yakar, Derya, Elschot, Mattijs, Veltman, Jeroen, F\u00fctterer, Jurgen, de Rooij, Maarten, & Huisman, Henkjan. (2022). Artificial Intelligence and Radiologists at Prostate Cancer Detection in MRI: The PI-CAI Challenge (Study Protocol) (1.0). Zenodo. https://doi.org/10.5281/zenodo.6522364", "https://pi-cai.grand-challenge.org/PI-CAI/"]}