cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.14431724.v1
title: Additional file 1 of Reliable genomic strategies for species classification of plant genetic resources

description: Additional file 1. Prediction accuracy per species and species representation. Classifiers are Random Forest (RF), Naive Bayes (NB), Neighbour-Joining (NJ), 1-Nearest Neighbour (1-NN), and 3-Nearest-Neighbours (3-NN), respectively. The number of accessions per species is denoted by ’n’. The best performance for each dataset is presented in bold.
DOI: 10.6084/m9.figshare.14431733
title: Additional file 4 of Reliable genomic strategies for species classification of plant genetic resources

description: Additional file 4. Tomato reseq dataset and predictions. List of resequenced tomato accessions included in this study, their a priori classifications and species predictions from all classifiers studied.
DOI: 10.6084/m9.figshare.14431736.v1
title: Additional file 5 of Reliable genomic strategies for species classification of plant genetic resources

description: Additional file 5. Sunflower dataset and predictions. List of sunflower accessions included in this study, their a priori classifications and species predictions from all classifiers studied.
DOI: 10.6084/m9.figshare.14431739
title: Additional file 6 of Reliable genomic strategies for species classification of plant genetic resources

description: Additional file 6. Tomato AFLP dataset and predictions. List of tomato AFLP accessions included in this study, their a priori classifications and species predictions from all classifiers studied.
DOI: 10.6084/m9.figshare.14431733.v1
title: Additional file 4 of Reliable genomic strategies for species classification of plant genetic resources

description: Additional file 4. Tomato reseq dataset and predictions. List of resequenced tomato accessions included in this study, their a priori classifications and species predictions from all classifiers studied.
DOI: 10.6084/m9.figshare.14431739.v1
title: Additional file 6 of Reliable genomic strategies for species classification of plant genetic resources

description: Additional file 6. Tomato AFLP dataset and predictions. List of tomato AFLP accessions included in this study, their a priori classifications and species predictions from all classifiers studied.
DOI: 10.6084/m9.figshare.14431736
title: Additional file 5 of Reliable genomic strategies for species classification of plant genetic resources

description: Additional file 5. Sunflower dataset and predictions. List of sunflower accessions included in this study, their a priori classifications and species predictions from all classifiers studied.
DOI: 10.6084/m9.figshare.14431766.v1
title: Additional file 1 of Count every newborn: EN-BIRTH study improving facility-based coverage and quality measurement in routine information systems

description: Additional file 1. Key findings of EN-BIRTH study.
DOI: 10.6084/m9.figshare.14431766
title: Additional file 1 of Count every newborn: EN-BIRTH study improving facility-based coverage and quality measurement in routine information systems

description: Additional file 1. Key findings of EN-BIRTH study.
DOI: 10.6084/m9.figshare.14431769.v1
title: Additional file of Revisiting the vascularity of the keratinized gingiva in the maxillary esthetic zone

description: Additional file of Revisiting the vascularity of the keratinized gingiva in the maxillary esthetic zone
DOI: 10.6084/m9.figshare.14431769
title: Additional file of Revisiting the vascularity of the keratinized gingiva in the maxillary esthetic zone

description: Additional file of Revisiting the vascularity of the keratinized gingiva in the maxillary esthetic zone
DOI: 10.25345/c5nj7k
title: MassIVE MSV000087216 - GNPS_Mouse_Plasma_lipophilic_ESN_CID
title: Lipophilic metabolites extracted from mouse plasma and stored in MeOH:toluene (9:1), CID-HCD and ESN
DOI: 10.5281/zenodo.3874937
title: LoDoPaB-CT Challenge Set

description: Observation data for the LoDoPaB-CT challenge, which asks to reconstruct CT images of the human lung from (simulated) low photon count measurements. The setting is identical to the one of the LoDoPaB-CT dataset (documented in this Data Descriptor article), which is supposed to be employed for training learned methods. This challenge set contains observations for a separate set of patients. Python utilities for accessing this challenge set and creating the submission file are available at github.com/jleuschn/lodopab_challenge. The LoDoPaB-CT dataset for training can be accessed using the DIVal python library (github.com/jleuschn/dival). Like for the LoDoPaB-CT dataset, reconstructions from the LIDC/IDRI dataset are used as a basis for this challenge set. The ZIP file contains multiple HDF5 files. Each HDF5 file contains one HDF5 dataset named <code>"data"</code>, that provides a number of samples (128 except for the last file). For example, the <code>n</code>-th observation sample is stored in the file <code>"observation_challenge_%03d.hdf5"</code> where <code>"%03d"</code> is <code>floor(n / 128)</code>, at row <code>(n mod 128)</code> of <code>"data"</code>. For this challenge set no patient IDs are provided (in contrast to the fully public parts of the LoDoPaB-CT dataset), since the reconstruction algorithm should not rely on this information. <em>Acknowledgements</em> Johannes Leuschner, Maximilian Schmidt and Daniel Otero Baguer acknowledge the support by the Deutsche<br> Forschungsgemeinschaft (DFG) within the framework of GRK 2224/1 “π3: Parameter Identification – Analysis,<br> Algorithms, Applications”. We thank Simon Arridge, Ozan Öktem, Carola-Bibiane Schönlieb and Christian<br> Etmann for the fruitful discussion about the procedure, and Felix Lucka and Jonas Adler for their ideas and<br> helpful feedback on the simulation setup. The authors acknowledge the National Cancer Institute and the Foundation for the National Institutes of Health, and their critical role in the creation of the free publicly available LIDC/IDRI Database used in this study.
DOI: 10.5281/zenodo.3874936
title: LoDoPaB-CT Challenge Set

description: Observation data for the LoDoPaB-CT challenge, which asks to reconstruct CT images of the human lung from (simulated) low photon count measurements. The setting is identical to the one of the LoDoPaB-CT dataset (documented in this Data Descriptor article), which is supposed to be employed for training learned methods. This challenge set contains observations for a separate set of patients. Python utilities for accessing this challenge set and creating the submission file are available at github.com/jleuschn/lodopab_challenge. The LoDoPaB-CT dataset for training can be accessed using the DIVal python library (github.com/jleuschn/dival). Like for the LoDoPaB-CT dataset, reconstructions from the LIDC/IDRI dataset are used as a basis for this challenge set. The ZIP file contains multiple HDF5 files. Each HDF5 file contains one HDF5 dataset named <code>"data"</code>, that provides a number of samples (128 except for the last file). For example, the <code>n</code>-th observation sample is stored in the file <code>"observation_challenge_%03d.hdf5"</code> where <code>"%03d"</code> is <code>floor(n / 128)</code>, at row <code>(n mod 128)</code> of <code>"data"</code>. For this challenge set no patient IDs are provided (in contrast to the fully public parts of the LoDoPaB-CT dataset), since the reconstruction algorithm should not rely on this information. <em>Acknowledgements</em> Johannes Leuschner, Maximilian Schmidt and Daniel Otero Baguer acknowledge the support by the Deutsche<br> Forschungsgemeinschaft (DFG) within the framework of GRK 2224/1 “π3: Parameter Identification – Analysis,<br> Algorithms, Applications”. We thank Simon Arridge, Ozan Öktem, Carola-Bibiane Schönlieb and Christian<br> Etmann for the fruitful discussion about the procedure, and Felix Lucka and Jonas Adler for their ideas and<br> helpful feedback on the simulation setup. The authors acknowledge the National Cancer Institute and the Foundation for the National Institutes of Health, and their critical role in the creation of the free publicly available LIDC/IDRI Database used in this study.
DOI: 10.6084/m9.figshare.14431874
title: Additional file 2 of Research priorities for rare neurological diseases: a representative view of patient representatives and healthcare professionals from the European Reference Network for Rare Neurological Diseases

description: Additional file 2. The country and disease group focus of the survey’s respondents.
DOI: 10.6084/m9.figshare.14431874.v1
title: Additional file 2 of Research priorities for rare neurological diseases: a representative view of patient representatives and healthcare professionals from the European Reference Network for Rare Neurological Diseases

description: Additional file 2. The country and disease group focus of the survey’s respondents.
DOI: 10.6084/m9.figshare.14431925
title: Additional file 1 of LMTK3 inhibition affects microtubule stability

description: Additional file 1: Supplementary Table S1. Identified proteins and comparative quantification of TMT label intensities.
DOI: 10.6084/m9.figshare.14431925.v1
title: Additional file 1 of LMTK3 inhibition affects microtubule stability

description: Additional file 1: Supplementary Table S1. Identified proteins and comparative quantification of TMT label intensities.
DOI: 10.6084/m9.figshare.14431937
title: Additional file of Values and validity of fetal parameters by ultrasound and Doppler as markers of fetal lung maturity

description: Additional file of Values and validity of fetal parameters by ultrasound and Doppler as markers of fetal lung maturity
DOI: 10.6084/m9.figshare.14431937.v1
title: Additional file of Values and validity of fetal parameters by ultrasound and Doppler as markers of fetal lung maturity

description: Additional file of Values and validity of fetal parameters by ultrasound and Doppler as markers of fetal lung maturity
DOI: 10.6084/m9.figshare.14431967
title: Additional file of A controlled study on the diagnostic accuracy of panoramic and peri-apical radiography for detecting furcation involvement

description: Additional file of A controlled study on the diagnostic accuracy of panoramic and peri-apical radiography for detecting furcation involvement
DOI: 10.6084/m9.figshare.14431967.v1
title: Additional file of A controlled study on the diagnostic accuracy of panoramic and peri-apical radiography for detecting furcation involvement

description: Additional file of A controlled study on the diagnostic accuracy of panoramic and peri-apical radiography for detecting furcation involvement
DOI: 10.6084/m9.figshare.14432027.v1
title: Additional file of Antimicrobial use and resistance in Escherichia coli from healthy food-producing animals in Guadeloupe

description: Additional file of Antimicrobial use and resistance in Escherichia coli from healthy food-producing animals in Guadeloupe
DOI: 10.6084/m9.figshare.14432042.v1
title: Additional file of Behavioural and psychological symptoms of dementia in patients with Alzheimer’s disease and family caregiver burden: a path analysis

description: Additional file of Behavioural and psychological symptoms of dementia in patients with Alzheimer’s disease and family caregiver burden: a path analysis
DOI: 10.6084/m9.figshare.14432042
title: Additional file of Behavioural and psychological symptoms of dementia in patients with Alzheimer’s disease and family caregiver burden: a path analysis

description: Additional file of Behavioural and psychological symptoms of dementia in patients with Alzheimer’s disease and family caregiver burden: a path analysis
DOI: 10.6084/m9.figshare.14432141
title: Additional file 1 of Quantifying steric hindrance and topological obstruction to protein structure superposition

description: Additional file 1. SupplementaryDataCATH2_4Domains.m. Matlab script that loads and explains all the raw data from all CATH2.4 alignments. It produces figures and may be altered to investigate the data further.
DOI: 10.6084/m9.figshare.14432141.v1
title: Additional file 1 of Quantifying steric hindrance and topological obstruction to protein structure superposition

description: Additional file 1. SupplementaryDataCATH2_4Domains.m. Matlab script that loads and explains all the raw data from all CATH2.4 alignments. It produces figures and may be altered to investigate the data further.
DOI: 10.6084/m9.figshare.14432147
title: Additional file 3 of Quantifying steric hindrance and topological obstruction to protein structure superposition

description: Additional file 3. Data from aligning CATH2.4 domains. NeamTM3to20NoEndContraction.mat Data from global RMSD and TM-align alignments of alpha carbon backbone curves. The maximal length of Reidemeister moves is varied from 3 to 20 and end-contractions are not allowed. Similar data for the smooth representation of the backbone curve are contained in NeamTMSmooth3to20NoEndContraction.mat and in NeamTMSmooth3to20EndContraction.matwhen allowing end-contractions of MaxLength=2/residues.
DOI: 10.6084/m9.figshare.14432144
title: Additional file 2 of Quantifying steric hindrance and topological obstruction to protein structure superposition

description: Additional file 2. Data from aligning CATH2.4 domains. NeamTM3to20NoEndContraction.mat Data from global RMSD and TM-align alignments of alpha carbon backbone curves. The maximal length of Reidemeister moves is varied from 3 to 20 and end-contractions are not allowed. Similar data for the smooth representation of the backbone curve are contained in NeamTMSmooth3to20NoEndContraction.mat and in NeamTMSmooth3to20EndContraction.matwhen allowing end-contractions of MaxLength=2/residues.
DOI: 10.6084/m9.figshare.14432150.v1
title: Additional file 4 of Quantifying steric hindrance and topological obstruction to protein structure superposition

description: Additional file 4. Data from aligning CATH2.4 domains. NeamTM3to20NoEndContraction.mat Data from global RMSD and TM-align alignments of alpha carbon backbone curves. The maximal length of Reidemeister moves is varied from 3 to 20 and end-contractions are not allowed. Similar data for the smooth representation of the backbone curve are contained in NeamTMSmooth3to20NoEndContraction.mat and in NeamTMSmooth3to20EndContraction.matwhen allowing end-contractions of MaxLength = 2/residues.
DOI: 10.6084/m9.figshare.14432150
title: Additional file 4 of Quantifying steric hindrance and topological obstruction to protein structure superposition

description: Additional file 4. Data from aligning CATH2.4 domains. NeamTM3to20NoEndContraction.mat Data from global RMSD and TM-align alignments of alpha carbon backbone curves. The maximal length of Reidemeister moves is varied from 3 to 20 and end-contractions are not allowed. Similar data for the smooth representation of the backbone curve are contained in NeamTMSmooth3to20NoEndContraction.mat and in NeamTMSmooth3to20EndContraction.matwhen allowing end-contractions of MaxLength = 2/residues.
DOI: 10.6084/m9.figshare.14432153
title: Additional file of Quantifying steric hindrance and topological obstruction to protein structure superposition

description: Additional file of Quantifying steric hindrance and topological obstruction to protein structure superposition
DOI: 10.6084/m9.figshare.14432147.v1
title: Additional file 3 of Quantifying steric hindrance and topological obstruction to protein structure superposition

description: Additional file 3. Data from aligning CATH2.4 domains. NeamTM3to20NoEndContraction.mat Data from global RMSD and TM-align alignments of alpha carbon backbone curves. The maximal length of Reidemeister moves is varied from 3 to 20 and end-contractions are not allowed. Similar data for the smooth representation of the backbone curve are contained in NeamTMSmooth3to20NoEndContraction.mat and in NeamTMSmooth3to20EndContraction.matwhen allowing end-contractions of MaxLength=2/residues.
DOI: 10.6084/m9.figshare.14432144.v1
title: Additional file 2 of Quantifying steric hindrance and topological obstruction to protein structure superposition

description: Additional file 2. Data from aligning CATH2.4 domains. NeamTM3to20NoEndContraction.mat Data from global RMSD and TM-align alignments of alpha carbon backbone curves. The maximal length of Reidemeister moves is varied from 3 to 20 and end-contractions are not allowed. Similar data for the smooth representation of the backbone curve are contained in NeamTMSmooth3to20NoEndContraction.mat and in NeamTMSmooth3to20EndContraction.matwhen allowing end-contractions of MaxLength=2/residues.
DOI: 10.6084/m9.figshare.14432153.v1
title: Additional file of Quantifying steric hindrance and topological obstruction to protein structure superposition

description: Additional file of Quantifying steric hindrance and topological obstruction to protein structure superposition
DOI: 10.6084/m9.figshare.14432174.v1
title: Additional file of Marker-trait association analysis for drought tolerance in smooth bromegrass

description: Additional file of Marker-trait association analysis for drought tolerance in smooth bromegrass
DOI: 10.6084/m9.figshare.14432174
title: Additional file of Marker-trait association analysis for drought tolerance in smooth bromegrass

description: Additional file of Marker-trait association analysis for drought tolerance in smooth bromegrass
DOI: 10.6084/m9.figshare.14432183.v1
title: Additional file 3 of Haem relieves hyperoxia-mediated inhibition of HMEC-1 cell proliferation, migration and angiogenesis by inhibiting BACH1 expression

description: Additional file 3 Original Western blot images. Fig. S1 Effect of haem on HRMEC cell proliferation. a, Diagram showing the effect of different concentrations of haem on HRMEC- cell proliferation as detected by the CCK-8 method. All data are presented as the means ± SD, and the experiment was repeated three times (n = 3). One-way ANOVA or multivariate ANOVA was performed. b, Diagram showing the effect of different incubation times of 20 μM haem on HRMEC cell proliferation as detected by the CCK-8 method. All data are presented as the mean ± SD, and the experiment was repeated three times (n = 3). Multivariate ANOVA with repeated measurements test was performed. c, Images representative of the proliferative activity of HRMEC cells as measured by the EdU assay. Under a laser confocal microscope, proliferating cells were stained green (488), and nuclei were stained blue (DAPI). The arrow indicates a representative HRMEC cell with proliferative activity (scale bar = 200 μm). d-f, Quantitative analysis of the total number of cells, the number of cells with proliferative activity and the percentage of cells with proliferative activity among HRMEC cells subjected to different treatments. All data are presented as the means ± SD, and the experiment was repeated three times (n = 3). One-way ANOVA or multivariate ANOVA was performed. Fig. S2 Effect of haem on the angiogenesis of HRMEC cells. a, Images of the capillary-like tube formation of HRMEC cells stained green (488) after 48 h of culture under different conditions. Under hyperoxic conditions alone, the vascular network was fragmented and disordered. Upon the addition of 20 μM haem, the vascular network was more complete and denser (scale bar = 200 μM). b-d, Quantitative analysis of the number of junctions, length and area of capillary-like tubes formed by HRMEC cells. All data are presented as the means ± SD, and the experiment was repeated three times (n = 3). One-way ANOVA or multivariate ANOVA was performed.
DOI: 10.6084/m9.figshare.14432183
title: Additional file 3 of Haem relieves hyperoxia-mediated inhibition of HMEC-1 cell proliferation, migration and angiogenesis by inhibiting BACH1 expression

description: Additional file 3 Original Western blot images. Fig. S1 Effect of haem on HRMEC cell proliferation. a, Diagram showing the effect of different concentrations of haem on HRMEC- cell proliferation as detected by the CCK-8 method. All data are presented as the means ± SD, and the experiment was repeated three times (n = 3). One-way ANOVA or multivariate ANOVA was performed. b, Diagram showing the effect of different incubation times of 20 μM haem on HRMEC cell proliferation as detected by the CCK-8 method. All data are presented as the mean ± SD, and the experiment was repeated three times (n = 3). Multivariate ANOVA with repeated measurements test was performed. c, Images representative of the proliferative activity of HRMEC cells as measured by the EdU assay. Under a laser confocal microscope, proliferating cells were stained green (488), and nuclei were stained blue (DAPI). The arrow indicates a representative HRMEC cell with proliferative activity (scale bar = 200 μm). d-f, Quantitative analysis of the total number of cells, the number of cells with proliferative activity and the percentage of cells with proliferative activity among HRMEC cells subjected to different treatments. All data are presented as the means ± SD, and the experiment was repeated three times (n = 3). One-way ANOVA or multivariate ANOVA was performed. Fig. S2 Effect of haem on the angiogenesis of HRMEC cells. a, Images of the capillary-like tube formation of HRMEC cells stained green (488) after 48 h of culture under different conditions. Under hyperoxic conditions alone, the vascular network was fragmented and disordered. Upon the addition of 20 μM haem, the vascular network was more complete and denser (scale bar = 200 μM). b-d, Quantitative analysis of the number of junctions, length and area of capillary-like tubes formed by HRMEC cells. All data are presented as the means ± SD, and the experiment was repeated three times (n = 3). One-way ANOVA or multivariate ANOVA was performed.
DOI: 10.6084/m9.figshare.14432210
title: Additional file of Identification of key genes involved in tumor immune cell infiltration and cetuximab resistance in colorectal cancer

description: Additional file of Identification of key genes involved in tumor immune cell infiltration and cetuximab resistance in colorectal cancer
DOI: 10.6084/m9.figshare.14432210.v1
title: Additional file of Identification of key genes involved in tumor immune cell infiltration and cetuximab resistance in colorectal cancer

description: Additional file of Identification of key genes involved in tumor immune cell infiltration and cetuximab resistance in colorectal cancer
DOI: 10.6084/m9.figshare.14432219
title: Additional file 3 of Discovery of novel community-relevant small proteins in a simplified human intestinal microbiome

description: Additional file 2. Supplement Table 4.
DOI: 10.6084/m9.figshare.14432219.v1
title: Additional file 3 of Discovery of novel community-relevant small proteins in a simplified human intestinal microbiome

description: Additional file 2. Supplement Table 4.
DOI: 10.6084/m9.figshare.14432222
title: Additional file 4 of Discovery of novel community-relevant small proteins in a simplified human intestinal microbiome

description: Additional file 3. Supplement Table 6.
DOI: 10.6084/m9.figshare.14432225
title: Additional file 5 of Discovery of novel community-relevant small proteins in a simplified human intestinal microbiome

description: Additional file 4. Supplement Table 8.
DOI: 10.6084/m9.figshare.14432228
title: Additional file 6 of Discovery of novel community-relevant small proteins in a simplified human intestinal microbiome

description: Additional file 5. Supplement Table 9.
DOI: 10.6084/m9.figshare.14432228.v1
title: Additional file 6 of Discovery of novel community-relevant small proteins in a simplified human intestinal microbiome

description: Additional file 5. Supplement Table 9.
DOI: 10.6084/m9.figshare.14432231
title: Additional file of Discovery of novel community-relevant small proteins in a simplified human intestinal microbiome

description: Additional file of Discovery of novel community-relevant small proteins in a simplified human intestinal microbiome
DOI: 10.6084/m9.figshare.14432231.v1
title: Additional file of Discovery of novel community-relevant small proteins in a simplified human intestinal microbiome

description: Additional file of Discovery of novel community-relevant small proteins in a simplified human intestinal microbiome