cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15151/esrf-es-771370291
title: Belgian BAG

description: The BAG includes groups situated at four Flemish universities: Antwerp, Brussels, Ghent and Leuven. Several of these groups are part of the elite Flemish Institute of Biotechnology (VIB). The proposed projects are highly diverse, including viral, prokaryotic and eukaryotic proteins with a strong focus on targets and processes of biomedical relevance. Many projects deal with membrane proteins, cell surface receptors and protein-protein complexes. Central to the research in the BAG associated groups is the employment of integrative methods in structural biology combining X-ray crystallography, SAXS, and cryo-electron microscopy. Many crystals in the various proposed projects are small in size and radiation sensitive, requiring the use of the high brilliance MX beam lines, preferably with micro-focused X-rays. This is a continuation of a previous Belgian BAG which has resulted in numerous top-tier publications.
DOI: 10.15151/esrf-es-847397111
title: Structural studies of RNA Polymerase from P. aeruginosa

description: We would like to understand the molecular mechanism of RNA polymerase function in transcription of P. aeruginosa using cryo-EM
DOI: 10.15151/esrf-es-813361131
title: Unveiling the topmost layers of spider silks by ultra-high resolution mapping of sections

description: While spider silk threads mainly consist of a core of partially crystalline silk proteins, it has been found that they also exhibit a very thin skin layer of distinct structure and a coating rich in lipids and glycoproteins. These outer layers are poorly researched, but can be assumed to be a major player governing the interaction of cells with spider silk threads, as observed in cell culture. Here we propose SAXS/WAXS mapping with ultra-high spatial resolution to examine the surface layer of thin cryo-cut sections of different spider silks that have shown different cell guiding behavior in cell culture. This approach allows studying surface layers from two orientations (along and normal to fiber axis) and the cryo-approach minimizes morphological changes. In a recent nano-SAXS/WAXS beamtime at ID13, we obtained very promising data, however with whole threads and with lower resolution. This follow-up work aims to characterize the surface layer systematically.
DOI: 10.5281/zenodo.6635400
title: Dataset of Performing Calculus with Epsilon-near-zero Metamaterials

description: Dataset of <em>Performing Calculus with Epsilon-near-zero Metamaterials</em>
DOI: 10.21227/cqs5-3f60
title: Federated Learning based Base Station Selection using LiDAR Data

description: The following folder contains the data simulated using the metholodgy described in the paper titled "Federated Learning based Base Station Selection using LiDAR Data"
DOI: 10.6084/m9.figshare.20055923
title: Data Underlying the research of Gurmeet Singh, research article entitled:"LOW BALF CD4 T CELLS COUNT IS ASSOCIATED WITH EXTUBATION FAILURE AND MORTALITY IN CRITICALLY ILL COVID-19 PNEUMONIA"

description: The data here is only for research paper validation of principal investigator / corresponding author Gurmeet Singh entitled: LOW BALF CD4 T CELLS COUNT IS ASSOCIATED WITH EXTUBATION FAILURE AND MORTALITY IN CRITICALLY ILL COVID-19 PNEUMONIA. The data consists of patients' clinical characteristics, laboratory profiles, and bronchoalveolar lavage fluid specimen results.
DOI: 10.6084/m9.figshare.20055923.v1
title: Data Underlying the research of Gurmeet Singh, research article entitled:"LOW BALF CD4 T CELLS COUNT IS ASSOCIATED WITH EXTUBATION FAILURE AND MORTALITY IN CRITICALLY ILL COVID-19 PNEUMONIA"

description: The data here is only for research paper validation of principal investigator / corresponding author Gurmeet Singh entitled: LOW BALF CD4 T CELLS COUNT IS ASSOCIATED WITH EXTUBATION FAILURE AND MORTALITY IN CRITICALLY ILL COVID-19 PNEUMONIA. The data consists of patients' clinical characteristics, laboratory profiles, and bronchoalveolar lavage fluid specimen results.
DOI: 10.21227/7png-jb17
title: Deep learning for CSI estimation in MassiveMIMO environments

description: Machine learning methods are poised to drastically improve the performance of many aspects of communication engineering, across all layers of the communication stack: from the physical layer to the application one.  In this competition, we focus on the problem of federated training of a deep CSI compressor for massive MIMO in 5G protocols and beyond.
DOI: 10.34740/kaggle/dsv/3786475
title: Russian Invasion of Ukraine
DOI: 10.5281/zenodo.6635542
title: Data from: How arbuscular mycorrhizal fungi drives herbaceous plants' C: N: P stoichiometry?

description: Plant element stoichiometry is fundamental for preserving growth-related terrestrial ecosystem structures and functions. However, effects of arbuscular mycorrhizal fungi (AMF) on herbaceous plant element stoichiometry (carbon (C), nitrogen (N), and phosphorus (P)) remain unclear. In this study, we aimed at evaluating the potential effects of AMF on herbaceous plant C, N and P concentration and their C:N:P stoichiometry worldwide through a quantitative meta-analysis. We observed that AMF reduced C:P and N:P ratios in the shoot of plants by 35.83% and 54.23%, respectively, and in plant root organs by 36.24% and 46.35%, respectively. Conversely, C:N ratios increased in roots by 6.61%. The negative effect of AMF on N:P and C:P ratios in plant shoots and root organs is mainly attributed to the plant benefits in P and N concentrations. AMF impact on plant C:N:P stoichiometry depends on fungal and plant functional group identities and soil nutrient availability. Our results suggest that plant functional group identity affects plant nutrient concentration, which, in turn, controls herbaceous plant C:N:P stoichiometry. Also, we emphasize the importance of abiotic and biotic environmental factors in changing AMF effects on plant element stoichiometry. Therefore, clarifying the relationship between AMF and herbaceous plant C:N:P stoichiometry will improve our understanding of herbaceous plant stoichiometric variations in terrestrial ecosystems.
DOI: 10.5281/zenodo.6635541
title: Data from: How arbuscular mycorrhizal fungi drives herbaceous plants' C: N: P stoichiometry?

description: Plant element stoichiometry is fundamental for preserving growth-related terrestrial ecosystem structures and functions. However, effects of arbuscular mycorrhizal fungi (AMF) on herbaceous plant element stoichiometry (carbon (C), nitrogen (N), and phosphorus (P)) remain unclear. In this study, we aimed at evaluating the potential effects of AMF on herbaceous plant C, N and P concentration and their C:N:P stoichiometry worldwide through a quantitative meta-analysis. We observed that AMF reduced C:P and N:P ratios in the shoot of plants by 35.83% and 54.23%, respectively, and in plant root organs by 36.24% and 46.35%, respectively. Conversely, C:N ratios increased in roots by 6.61%. The negative effect of AMF on N:P and C:P ratios in plant shoots and root organs is mainly attributed to the plant benefits in P and N concentrations. AMF impact on plant C:N:P stoichiometry depends on fungal and plant functional group identities and soil nutrient availability. Our results suggest that plant functional group identity affects plant nutrient concentration, which, in turn, controls herbaceous plant C:N:P stoichiometry. Also, we emphasize the importance of abiotic and biotic environmental factors in changing AMF effects on plant element stoichiometry. Therefore, clarifying the relationship between AMF and herbaceous plant C:N:P stoichiometry will improve our understanding of herbaceous plant stoichiometric variations in terrestrial ecosystems.
DOI: 10.5281/zenodo.6366987
title: From the Ecosystem: How External Pull Requests Contribute to a Software Library

description: Third-party libraries are now commonplace when building contemporary software applications. Despite their popular use, most libraries are open source software that often rely on volunteer (usually unpaid and overworked) contributions from outside the core team (external). To understand the role that these contributions play to sustain third-party libraries, we analyze Pull Requests (PRs) submitted from outside the core team of contributors (i.e., External PRs). We analyze 945,291 PRs from the NPM ecosystem to empirically investigate External PR prevalence, acceptance, need for attention, and content. Our findings indicate that External PR are indeed prevalent (75.02% of all received PRs are External PR and 88.87% submitted on average). Interestingly, External PRs are just as likely to be accepted compared to Internal PRs (50% per package). For a package, we find that on average, 26.75% of External PRs submitted are linked to an already existing issue, and require the attention of the core team, with labels such as breaking changes, urgent, and on-hold. In a qualitative analysis, we find that External PRs focus on documentation (44 out of 384 PRs), which is different to adding new features (380 out of 384 PRs) for Bot PRs, and refactoring (34 out of 384 PRs) for Internal PRs. The study confirms that external contributions play a key role in the ecosystem, and reinforces the call for help, especially from single maintainer libraries that serve a massive client user-base.
DOI: 10.34740/kaggle/dsv/3786749
title: AutoXGB
DOI: 10.6084/m9.figshare.19091738
title: Suporting data for Hawlena, H. et al. (2022). Frontiers in Ecology & Evolution.

description: Suporting data for Hawlena, H. et al. (2022). <em>Frontiers in Ecology & Evolution</em>, 10:898074. doi: 10.3389/fevo.2022.898074
DOI: 10.6084/m9.figshare.19091738.v4
title: Suporting data for Hawlena, H. et al. (2022). Frontiers in Ecology & Evolution.

description: Suporting data for Hawlena, H. et al. (2022). <em>Frontiers in Ecology & Evolution</em>, 10:898074. doi: 10.3389/fevo.2022.898074
DOI: 10.6084/m9.figshare.19091738.v3
title: Suporting data for Hawlena, H. et al. (2022). Frontiers in Ecology & Evolution.

description: Suporting data for Hawlena, H. et al. (2022). <em>Frontiers in Ecology & Evolution</em>, 10:898074. doi: 10.3389/fevo.2022.898074
DOI: 10.6084/m9.figshare.20055950
title: Data

description: Sequencing data and Python file for data processing
DOI: 10.6084/m9.figshare.20055950.v1
title: Data

description: Sequencing data and Python file for data processing
DOI: 10.5517/ccdc.csd.cc284q16
title: CCDC 2089897: Experimental Crystal Structure Determination

description: Related Article: Bidong Zhang, Katarzyna Kurpiewska, Alexander Dömling|2022|J.Org.Chem.|87|7085|doi:10.1021/acs.joc.2c00244
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc284q27
title: CCDC 2089898: Experimental Crystal Structure Determination

description: Related Article: Bidong Zhang, Katarzyna Kurpiewska, Alexander Dömling|2022|J.Org.Chem.|87|7085|doi:10.1021/acs.joc.2c00244
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc28jrh2
title: CCDC 2101474: Experimental Crystal Structure Determination

description: Related Article: Srinivas Vangara, Nagarjuna Kommu, Vikranth Thaltiri, M. Balaraju, Akhila K. Sahoo|2022|J.Org.Chem.|87|7202|doi:10.1021/acs.joc.2c00410
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc28jrj3
title: CCDC 2101475: Experimental Crystal Structure Determination

description: Related Article: Srinivas Vangara, Nagarjuna Kommu, Vikranth Thaltiri, M. Balaraju, Akhila K. Sahoo|2022|J.Org.Chem.|87|7202|doi:10.1021/acs.joc.2c00410
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc28jrk4
title: CCDC 2101476: Experimental Crystal Structure Determination

description: Related Article: Srinivas Vangara, Nagarjuna Kommu, Vikranth Thaltiri, M. Balaraju, Akhila K. Sahoo|2022|J.Org.Chem.|87|7202|doi:10.1021/acs.joc.2c00410
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc28jrl5
title: CCDC 2101477: Experimental Crystal Structure Determination

description: Related Article: Srinivas Vangara, Nagarjuna Kommu, Vikranth Thaltiri, M. Balaraju, Akhila K. Sahoo|2022|J.Org.Chem.|87|7202|doi:10.1021/acs.joc.2c00410
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc28jrm6
title: CCDC 2101478: Experimental Crystal Structure Determination

description: Related Article: Srinivas Vangara, Nagarjuna Kommu, Vikranth Thaltiri, M. Balaraju, Akhila K. Sahoo|2022|J.Org.Chem.|87|7202|doi:10.1021/acs.joc.2c00410
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc28jph0
title: CCDC 2101412: Experimental Crystal Structure Determination

description: Related Article: Srinivas Vangara, Nagarjuna Kommu, Vikranth Thaltiri, M. Balaraju, Akhila K. Sahoo|2022|J.Org.Chem.|87|7202|doi:10.1021/acs.joc.2c00410
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc28jpj1
title: CCDC 2101413: Experimental Crystal Structure Determination

description: Related Article: Srinivas Vangara, Nagarjuna Kommu, Vikranth Thaltiri, M. Balaraju, Akhila K. Sahoo|2022|J.Org.Chem.|87|7202|doi:10.1021/acs.joc.2c00410
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc28jpk2
title: CCDC 2101414: Experimental Crystal Structure Determination

description: Related Article: Srinivas Vangara, Nagarjuna Kommu, Vikranth Thaltiri, M. Balaraju, Akhila K. Sahoo|2022|J.Org.Chem.|87|7202|doi:10.1021/acs.joc.2c00410
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.6084/m9.figshare.20055983
title: Local polygon mesh data of Chicago

description: The data is a local polygon mesh model of Chicago, which is located in a local 3D Cartesian coordinate. In this local coordinate system, the X, Y, and Z coordinate ranges of the model are [0.0 km, 1.9992km], [0.0 km, 1.893km], and [0.0 km, 0.443 km], respectively. The format of this data is OBJ.<br>
DOI: 10.6084/m9.figshare.20056083.v1
title: Additional file 9 of Linking gastrointestinal microbiota and metabolome dynamics to clinical outcomes in paediatric haematopoietic stem cell transplantation

description: Additional file 8: Figure S7. Fluctuating taxa landscape in the first 100 days post-transplantation. Relative abundance of taxa found to be dominant in the cohort during the first 100 days. The fitted line shows a local polynomial regression fit calculated using glm, with the grey region indicating the 95% CI.
DOI: 10.6084/m9.figshare.20056083
title: Additional file 9 of Linking gastrointestinal microbiota and metabolome dynamics to clinical outcomes in paediatric haematopoietic stem cell transplantation

description: Additional file 8: Figure S7. Fluctuating taxa landscape in the first 100 days post-transplantation. Relative abundance of taxa found to be dominant in the cohort during the first 100 days. The fitted line shows a local polynomial regression fit calculated using glm, with the grey region indicating the 95% CI.
DOI: 10.6084/m9.figshare.20056104.v1
title: Additional file 1 of Literacy-adapted, electronic family history assessment for genetics referral in primary care: patient user insights from qualitative interviews

description: Additional file 1. Interview guide questions by topic. Contains all questions in semi-structured interview guide utilized by interviewer (KFM).
DOI: 10.6084/m9.figshare.20056107
title: Additional file 2 of Literacy-adapted, electronic family history assessment for genetics referral in primary care: patient user insights from qualitative interviews

description: Additional file 2. Codebook definitions of all qualitative codes used. Contains the codebook codes and code definitions utilized by coders during analysis.
DOI: 10.6084/m9.figshare.20056104
title: Additional file 1 of Literacy-adapted, electronic family history assessment for genetics referral in primary care: patient user insights from qualitative interviews

description: Additional file 1. Interview guide questions by topic. Contains all questions in semi-structured interview guide utilized by interviewer (KFM).
DOI: 10.6084/m9.figshare.20056107.v1
title: Additional file 2 of Literacy-adapted, electronic family history assessment for genetics referral in primary care: patient user insights from qualitative interviews

description: Additional file 2. Codebook definitions of all qualitative codes used. Contains the codebook codes and code definitions utilized by coders during analysis.
DOI: 10.6084/m9.figshare.20056110
title: Additional file 3 of Literacy-adapted, electronic family history assessment for genetics referral in primary care: patient user insights from qualitative interviews

description: Additional file 3. Interviewee characteristics on per-cohort basis. Contains the information provided in Table 1, subdivided into the four cohorts described in this study.
DOI: 10.6084/m9.figshare.20056110.v1
title: Additional file 3 of Literacy-adapted, electronic family history assessment for genetics referral in primary care: patient user insights from qualitative interviews

description: Additional file 3. Interviewee characteristics on per-cohort basis. Contains the information provided in Table 1, subdivided into the four cohorts described in this study.
DOI: 10.6084/m9.figshare.20056209
title: Additional file 2 of Mutations in ALK signaling pathways conferring resistance to ALK inhibitor treatment lead to collateral vulnerabilities in neuroblastoma cells

description: Additional file 2: Table S2. Normalized read counts. CRISPR-Cas9 knockout screen-Normalized read counts (related to Figure 1).
DOI: 10.6084/m9.figshare.20056209.v1
title: Additional file 2 of Mutations in ALK signaling pathways conferring resistance to ALK inhibitor treatment lead to collateral vulnerabilities in neuroblastoma cells

description: Additional file 2: Table S2. Normalized read counts. CRISPR-Cas9 knockout screen-Normalized read counts (related to Figure 1).
DOI: 10.6084/m9.figshare.20056212
title: Additional file 3 of Mutations in ALK signaling pathways conferring resistance to ALK inhibitor treatment lead to collateral vulnerabilities in neuroblastoma cells

description: Additional file 3: Table S3. MAGeCK VISPR analysis. CRISPR-Cas9 knockout screen-MAGeCK VISPR analysis (related to Figure 1).
DOI: 10.6084/m9.figshare.20056212.v1
title: Additional file 3 of Mutations in ALK signaling pathways conferring resistance to ALK inhibitor treatment lead to collateral vulnerabilities in neuroblastoma cells

description: Additional file 3: Table S3. MAGeCK VISPR analysis. CRISPR-Cas9 knockout screen-MAGeCK VISPR analysis (related to Figure 1).
DOI: 10.6084/m9.figshare.20056215
title: Additional file 4 of Mutations in ALK signaling pathways conferring resistance to ALK inhibitor treatment lead to collateral vulnerabilities in neuroblastoma cells

description: Additional file 4: Table S4. Gene beta scores cutoff at p0.01. CRISPR-Cas9 knockout screen- Gene beta scores cutoff at p0.01 (related to Figure 1).
DOI: 10.6084/m9.figshare.20056215.v1
title: Additional file 4 of Mutations in ALK signaling pathways conferring resistance to ALK inhibitor treatment lead to collateral vulnerabilities in neuroblastoma cells

description: Additional file 4: Table S4. Gene beta scores cutoff at p0.01. CRISPR-Cas9 knockout screen- Gene beta scores cutoff at p0.01 (related to Figure 1).
DOI: 10.6084/m9.figshare.20056221
title: Additional file 5 of Mutations in ALK signaling pathways conferring resistance to ALK inhibitor treatment lead to collateral vulnerabilities in neuroblastoma cells

description: Additional file 5: Table S5. Oligonucleotides used. Oligonucleotides used in this study (related to Figures 1, 2 and 4).
DOI: 10.6084/m9.figshare.20056221.v1
title: Additional file 5 of Mutations in ALK signaling pathways conferring resistance to ALK inhibitor treatment lead to collateral vulnerabilities in neuroblastoma cells

description: Additional file 5: Table S5. Oligonucleotides used. Oligonucleotides used in this study (related to Figures 1, 2 and 4).
DOI: 10.6084/m9.figshare.20056236
title: Additional file 1 of Lipid droplet dynamics in healthy and pyometra-affected canine endometrium

description: Additional file 1.
DOI: 10.6084/m9.figshare.20056236.v1
title: Additional file 1 of Lipid droplet dynamics in healthy and pyometra-affected canine endometrium

description: Additional file 1.
DOI: 10.6084/m9.figshare.20056240
title: Additional file 1 of Association of single nucleotide polymorphisms (SNPs) with gastric cancer susceptibility and prognosis in population in Wuwei, Gansu, China

description: Additional file 1: Table S1. The detailed histopathology and pathological TNM information of all samples.
DOI: 10.6084/m9.figshare.20056240.v1
title: Additional file 1 of Association of single nucleotide polymorphisms (SNPs) with gastric cancer susceptibility and prognosis in population in Wuwei, Gansu, China

description: Additional file 1: Table S1. The detailed histopathology and pathological TNM information of all samples.