cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7688935
title: Supplementary Source Data

description: Supplementary Main Data.
DOI: 10.5281/zenodo.7688934
title: Supplementary Source Data

description: Supplementary Main Data.
DOI: 10.5517/ccdc.csd.cc21csmv
title: CCDC 1888167: Experimental Crystal Structure Determination

description: Related Article: Fortis-Valera, Monserrat, Bernès, Sylvain, Arroyo-Carmona, Rosa Elena, Pérez-Benítez, Aarón|2018|CSD Communication|||
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: 10.5281/zenodo.7688693
title: Supplementary Source Data

description: Supplementary Main Data.
DOI: 10.5281/zenodo.7688692
title: Supplementary Source Data

description: Supplementary Main Data.
DOI: 10.34740/kaggle/dsv/5088828
title: Mahanagar Yatayat Dataset
DOI: 10.6084/m9.figshare.22189198.v1
title: inSPIRE-External-Utilities

description: External Utilities used by inSPIRE. <br> Note this includes script from the open source fragpipe tool. Source of this script https://github.com/Nesvilab/FragPipe <br>
DOI: 10.5281/zenodo.7688957
title: Molecular subtypes and dietary patterns in breast cancer patients: a latent class analysis

description: Molecular subtypes and dietary patterns in breast cancer patients: a latent class analysis
description: Cite us
DOI: 10.5281/zenodo.7688956
title: Molecular subtypes and dietary patterns in breast cancer patients: a latent class analysis

description: Molecular subtypes and dietary patterns in breast cancer patients: a latent class analysis
description: Cite us
DOI: 10.5281/zenodo.7683358
title: Derivative products from "Spherical Harmonic Representation of Energetic Neutral Atom Flux Components Observed by IBEX" by Swaczyna, Dayeh, & Zirnstein

description: This dataset includes derivative data products obtained using the method described in: Swaczyna, Dayeh, & Zirnstein (2023), <em>Spherical Harmonic Representation of Energetic Neutral Atom Flux Components Observed by IBEX</em> The products have been derived from IBEX Data Release #16 (https://ibex.princeton.edu/DataRelease16). hvset_tabular_ram_cg.zip - results for ram-only Compton-Getting and survival probability corrected IBEX maps hvset_tabular_antiram_cg.zip - results for antiram-only Compton-Getting and survival probability corrected IBEX maps Each archive includes the following files: <em>com</em>_flux_<em>yyyy</em>_esa_<em>e</em>.txt - reconstructed flux map from spherical harmonic coefficients using the standard IBEX pixelization <em>com</em>_fvar_<em>yyyy</em>_esa_<em>e</em>.txt - reconstructed flux variance map from spherical harmonic coefficients using the standard IBEX pixelization <em>com</em>_ylm_coeff_<em>yyyy</em>_esa_<em>e</em>.txt - coefficients of the spherical harmonic representation <em>com</em>_ylm_mat_<em>yyyy</em>_esa_<em>e</em>.txt - covariance matrix providing uncertainties of the coefficients mask_ribbon_esa_<em>e</em>.txt - ribbon mask matrix_y.txt - matrix transforming the spherical harmonic coefficients into values in IBEX pixels where: <em>com </em>- indicate the included component of the ENA flux: gdf - Globally DIstirbuted Flux rib - IBEX ribbon tot - both components (total maps) <em>e</em> - enumerates IBEX energy steps (<em>e</em> = 2, 3, ... 6) <em>yyyy</em> - indicates map year (<em>yyyy</em> = 2009, 2010, ..., 2019 or 'single' for the time-combined map)
DOI: 10.5281/zenodo.7683357
title: Derivative products from "Spherical Harmonic Representation of Energetic Neutral Atom Flux Components Observed by IBEX" by Swaczyna, Dayeh, & Zirnstein

description: This dataset includes derivative data products obtained using the method described in: Swaczyna, Dayeh, & Zirnstein (2023), <em>Spherical Harmonic Representation of Energetic Neutral Atom Flux Components Observed by IBEX</em> The products have been derived from IBEX Data Release #16 (https://ibex.princeton.edu/DataRelease16). hvset_tabular_ram_cg.zip - results for ram-only Compton-Getting and survival probability corrected IBEX maps hvset_tabular_antiram_cg.zip - results for antiram-only Compton-Getting and survival probability corrected IBEX maps Each archive includes the following files: <em>com</em>_flux_<em>yyyy</em>_esa_<em>e</em>.txt - reconstructed flux map from spherical harmonic coefficients using the standard IBEX pixelization <em>com</em>_fvar_<em>yyyy</em>_esa_<em>e</em>.txt - reconstructed flux variance map from spherical harmonic coefficients using the standard IBEX pixelization <em>com</em>_ylm_coeff_<em>yyyy</em>_esa_<em>e</em>.txt - coefficients of the spherical harmonic representation <em>com</em>_ylm_mat_<em>yyyy</em>_esa_<em>e</em>.txt - covariance matrix providing uncertainties of the coefficients mask_ribbon_esa_<em>e</em>.txt - ribbon mask matrix_y.txt - matrix transforming the spherical harmonic coefficients into values in IBEX pixels where: <em>com </em>- indicate the included component of the ENA flux: gdf - Globally DIstirbuted Flux rib - IBEX ribbon tot - both components (total maps) <em>e</em> - enumerates IBEX energy steps (<em>e</em> = 2, 3, ... 6) <em>yyyy</em> - indicates map year (<em>yyyy</em> = 2009, 2010, ..., 2019 or 'single' for the time-combined map)
DOI: 10.5519/qd.p7p4htzc
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (1674 records)
DOI: 10.5281/zenodo.5548401
title: Submerged aquatic vegetation biomass from the Saint Lawrence River (2006-2016) to compare estimation from quadrat-diver technique to rake collection and echosounding

description: Here we provide 4 datasets that describes 1) the comparison between quadrat and rake collected biomass (QR), 2) the comparison of rake biomass and biovolume, a biomass proxy derived from echosounding (RE), 3) a validation dataset that confronts quadrat measurements to quadrat prediction measured from echosounding using two intercalibration equations (derived from QR and RE datasets), and 4) a whole-system biomass estimation comparing biomass predicted from echosounding and from rake. Original data comes from the Saint Lawrence River, mainly from Lac Saint-Pierre, but for the QR dataset also from Lac Saint-François and Lac Saint-Louis. Data from the QR (2006-2009) and validation dataset (2016) were collected by Christiane Hudon, Environment and Climate Change Canada, while the RE dataset and part of the validation dataset were collected as part of a project led by the Groupe de recherche interuniversitaire en limnologie (GRIL, 2012-2015) and by Morgan Botrel Ph.D. candidate (2016-2017, Université de Montréal). Data were created for an article on a method to estimate SAV biomass, led by Morgan Botrel and supervisor Roxane Maranger, with co-supervisor Christiane Hudon and Pascale Biron. For the second version, the data is more clearly organized in the four categories mentioned above. Additionally, revised prediction equations were applied which modifies results used in the validation and whole-system datasets (dataset 2 and 4). Equations are presented in the associated publication: Botrel, M., C. Hudon, P.M. Biron, R. Maranger. Combining quadrat, rake and echosounding to estimate submerged aquatic vegetation biomass at the ecosystem scale. Limnology & Oceanography: Methods. Accepted (as of 2023/02/08)
DOI: 10.5281/zenodo.5548402
title: Submerged aquatic vegetation data from the Saint Lawrence River (2006-2016) to compare biomass estimation from quadrat-diver technique to rake collection and echosounding

description: Here we provide 4 datasets that describes 1) the comparison between quadrat and rake collected biomass (QR), 2) the comparison of rake biomass and biovolume, a biomass proxy derived from echosounding (RE), 3) a validation dataset that confront quadrat measurements to quadrat prediction measured from echosounding using two intercalibration equations (derived from QR and RE datasets), and 4) a whole-system biomass estimation comparing biomass predicted from echosounding and from rake. Original data comes from the Saint Lawrence River, mainly from Lac Saint-Pierre, but for the QR dataset also from Lac Saint-François and Lac Saint-Louis. Data from the QR (2006-2009) and validation dataset (2016) were collected by Christiane Hudon, Environment and Climate Change Canada, while the RE dataset and part of the validation dataset were collected as part of a project led by the Groupe de recherche interuniversitaire en limnologie (GRIL, 2012-2015) and by Morgan Botrel Ph.D. candidate (2016-2017, Université de Montréal). Data were created for an article on a method to estimate SAV biomass, led by Morgan Botrel and supervisor Roxane Maranger, with co-supervisor Christiane Hudon and Pascale Biron.
DOI: 10.5281/zenodo.7622140
title: Submerged aquatic vegetation biomass from the Saint Lawrence River (2006-2016) to compare estimation from quadrat-diver technique to rake collection and echosounding

description: Here we provide 4 datasets that describes 1) the comparison between quadrat and rake collected biomass (QR), 2) the comparison of rake biomass and biovolume, a biomass proxy derived from echosounding (RE), 3) a validation dataset that confronts quadrat measurements to quadrat prediction measured from echosounding using two intercalibration equations (derived from QR and RE datasets), and 4) a whole-system biomass estimation comparing biomass predicted from echosounding and from rake. Original data comes from the Saint Lawrence River, mainly from Lac Saint-Pierre, but for the QR dataset also from Lac Saint-François and Lac Saint-Louis. Data from the QR (2006-2009) and validation dataset (2016) were collected by Christiane Hudon, Environment and Climate Change Canada, while the RE dataset and part of the validation dataset were collected as part of a project led by the Groupe de recherche interuniversitaire en limnologie (GRIL, 2012-2015) and by Morgan Botrel Ph.D. candidate (2016-2017, Université de Montréal). Data were created for an article on a method to estimate SAV biomass, led by Morgan Botrel and supervisor Roxane Maranger, with co-supervisor Christiane Hudon and Pascale Biron. For the second version, the data is more clearly organized in the four categories mentioned above. Additionally, revised prediction equations were applied which modifies results used in the validation and whole-system datasets (dataset 2 and 4). Equations are presented in the associated publication: Botrel, M., C. Hudon, P.M. Biron, R. Maranger. Combining quadrat, rake and echosounding to estimate submerged aquatic vegetation biomass at the ecosystem scale. Limnology & Oceanography: Methods. Accepted (as of 2023/02/08)
DOI: 10.5281/zenodo.7688948
title: Medication and condition codes used to develop a computable phenotype for Crohn's Disease incident cases

description: Lists of medication and condition concepts used for Crohn's disease incident case phenotyping as described in my Master's Thesis "Machine Learning Based Prediction of Incident Cases of Crohn’s Disease Using Electronic Health Records From a Large Integrated Health System". ibd_medication.csv contains medication names, OMOP Concept IDs, RxNorm codes and a flag indicating whether the medication is IBD-specific (i.e., antibiotics and glucocorticoides are marked as unspecific) ibd_conditions.csv contains condition names, OMOP Concept IDs, SNOMED CT codes and a categorical column indicating whether the condition refers to Crohn's Disease (CD), Ulcerative Colitis (UC), or Inflammatory bowel disease unclassified (IBD-U) ibd_symptoms.csv contains symptom names, OMOP Concept IDs, containing symptom group categories, and a flag indicating whether the symptom was added because it is a SNOMED CT descendent code of another code on the list. The list was created based on the IBD symptoms Read Code list provided by Blackwell et. al, 2021, doi:10.1093/ecco-jcc/jjaa146 IBD, Inflammatory Bowel Disease; OMOP, Observational Medical Outcomes Partnership; SNOMED CT, Systematized Nomenclature of Medicine Clinial Terms.
DOI: 10.5281/zenodo.7688949
title: Medication and condition codes used to develop a computable phenotype for Crohn's Disease incident cases

description: Lists of medication and condition concepts used for Crohn's disease incident case phenotyping as described in my Master's Thesis "Machine Learning Based Prediction of Incident Cases of Crohn’s Disease Using Electronic Health Records From a Large Integrated Health System". ibd_medication.csv contains medication names, OMOP Concept IDs, RxNorm codes and a flag indicating whether the medication is IBD-specific (i.e., antibiotics and glucocorticoides are marked as unspecific) ibd_conditions.csv contains condition names, OMOP Concept IDs, SNOMED-CT codes and a categorical column indicating whether the condition refers to Crohn's Disease (CD), Ulcerative Colitis (UC), or Inflammatory bowel disease unclassified (IBD-U) IBD, Inflammatory Bowel Disease.
DOI: 10.5281/zenodo.7688995
title: Medication and condition codes used to develop a computable phenotype for Crohn's Disease incident cases

description: Lists of medication and condition concepts used for Crohn's disease incident case phenotyping as described in my Master's Thesis "Machine Learning Based Prediction of Incident Cases of Crohn’s Disease Using Electronic Health Records From a Large Integrated Health System". ibd_medication.csv contains medication names, OMOP Concept IDs, RxNorm codes and a flag indicating whether the medication is IBD-specific (i.e., antibiotics and glucocorticoides are marked as unspecific) ibd_conditions.csv contains condition names, OMOP Concept IDs, SNOMED CT codes and a categorical column indicating whether the condition refers to Crohn's Disease (CD), Ulcerative Colitis (UC), or Inflammatory bowel disease unclassified (IBD-U) ibd_symptoms.csv contains symptom names, OMOP Concept IDs, containing symptom group categories, and a flag indicating whether the symptom was added because it is a SNOMED CT descendent code of another code on the list. The list was created based on the IBD symptoms Read Code list provided by Blackwell et. al, 2021, doi:10.1093/ecco-jcc/jjaa146 IBD, Inflammatory Bowel Disease; OMOP, Observational Medical Outcomes Partnership; SNOMED CT, Systematized Nomenclature of Medicine Clinial Terms.
DOI: 10.5281/zenodo.7688590
title: Entity Typing Datasets

description: These are the datasets used in the Entity Type Prediction task for Knowledge Graph Completion. <strong>DB630k_Fine-grained_Hierarchical.zip</strong> dataset has been used in the papers [1] and [2]. It is an extended version of DBpedia630k dataset originally created for Text classification and is available here. <strong>FIGER.zip</strong> dataset has also been used in the papers [1] and [2]. <strong>MultilingualETdata.zip</strong> dataset has been used in the paper [3] <strong>NamesETdata.zip</strong> dataset has been used in the paper [4]. The CaLiGraph test dataset can also be downloaded here. [1] Biswas R, Sofronova R, Sack H, Alam M. Cat2type: Wikipedia category embeddings for entity typing in knowledge graphs. InProceedings of the 11th on Knowledge Capture Conference 2021 Dec 2 (pp. 81-88). [2] Biswas R, Portisch J, Paulheim H, Sack H, Alam M. Entity type prediction leveraging graph walks and entity descriptions. In The Semantic Web–ISWC 2022: 21st International Semantic Web Conference, Virtual Event, October 23–27, 2022, Proceedings 2022 Oct 16 (pp. 392-410). Cham: Springer International Publishing. [3] Biswas R, Chen Y, Paulheim H, Sack H, Alam M. It’s All in the Name: Entity Typing Using Multilingual Language Models. In The Semantic Web: ESWC 2022 Satellite Events: Hersonissos, Crete, Greece, May 29–June 2, 2022, Proceedings 2022 Jul 20 (pp. 36-41). Cham: Springer International Publishing. [4] Biswas R, Sofronova R, Alam M, Heist N, Paulheim H, Sack H. Do judge an entity by its name! entity typing using language models. In The Semantic Web: ESWC 2021 Satellite Events: Virtual Event, June 6–10, 2021, Revised Selected Papers 18 2021 (pp. 65-70). Springer International Publishing.
DOI: 10.5281/zenodo.7688589
title: Entity Typing Datasets

description: These are the datasets used in the Entity Type Prediction task for Knowledge Graph Completion. <strong>DB630k_Fine-grained_Hierarchical.zip</strong> dataset has been used in the papers [1] and [2]. It is an extended version of DBpedia630k dataset originally created for Text classification and is available here. <strong>FIGER.zip</strong> dataset has also been used in the papers [1] and [2]. <strong>MultilingualETdata.zip</strong> dataset has been used in the paper [3] <strong>NamesETdata.zip</strong> dataset has been used in the paper [4]. The CaLiGraph test dataset can also be downloaded here. [1] Biswas R, Sofronova R, Sack H, Alam M. Cat2type: Wikipedia category embeddings for entity typing in knowledge graphs. InProceedings of the 11th on Knowledge Capture Conference 2021 Dec 2 (pp. 81-88). [2] Biswas R, Portisch J, Paulheim H, Sack H, Alam M. Entity type prediction leveraging graph walks and entity descriptions. In The Semantic Web–ISWC 2022: 21st International Semantic Web Conference, Virtual Event, October 23–27, 2022, Proceedings 2022 Oct 16 (pp. 392-410). Cham: Springer International Publishing. [3] Biswas R, Chen Y, Paulheim H, Sack H, Alam M. It’s All in the Name: Entity Typing Using Multilingual Language Models. In The Semantic Web: ESWC 2022 Satellite Events: Hersonissos, Crete, Greece, May 29–June 2, 2022, Proceedings 2022 Jul 20 (pp. 36-41). Cham: Springer International Publishing. [4] Biswas R, Sofronova R, Alam M, Heist N, Paulheim H, Sack H. Do judge an entity by its name! entity typing using language models. In The Semantic Web: ESWC 2021 Satellite Events: Virtual Event, June 6–10, 2021, Revised Selected Papers 18 2021 (pp. 65-70). Springer International Publishing.
DOI: 10.6084/m9.figshare.22194118.v1
title: Datasets used in SweepNet

description: Datasets used in the paper "SweepNet"
DOI: 10.17636/10184562
title: COVID-19 Associated Acute Kidney Injury: Long Term Outcomes (Statistical Analysis Plan)

description: This prospective analysis of retrospectively collected data as detailed within the EthICAL study will focus on the long-term renal function and mortality associated with acute kidney injury within COVID-19 patients admitted to five acute hospitals within East London during the pandemic. It will also examine the incidence, risk factors, and outcomes associated with acute kidney injury within COVID-19 patients admitted to five acute hospitals within East London during the second wave of the pandemic.
DOI: 10.26036/cnp0003206
title: Nymphoides indica

description: Here, we present a haplotype-resolved assembly of Nymphoides indica using HiFi reads and high-throughput chromatin conformation capture (Hi-C) technologies. The high-quality reference enable a better understanding of the genetic basis of distyly, and provide valuable resources for future N. indica research.
DOI: 10.15472/kuxdqj
title: Registros de plantas epífitas y hemiepífitas de Colombia de la colección FMB

description: I2D-BIO_2022_109. El conjunto de datos contiene 1580 registros de epífitas y hemiepífitas presentes en la colección FMB obtenidos en el marco del proyecto "Datos basados en colecciones para acciones de conservación: Promoviendo la participación de tomadores de decisiones para salvar epífitas amenazadas globalmente en Colombia". Los registros provienen de 25 departamentos de Colombia, donde los más representados son Boyacá, Santander, Cundinamarca, Nariño, Chocó y Antioquía. Estos datos se encuentran disponibles En http://i2d.humboldt.org.co/ceiba/resource.do?r=epifitas_fmb_2022 y en el recurso correspondiente al Herbario FMB disponible en: http://doi.org/10.15472/ighftu
DOI: 10.48527/rxsati/yv8hau
title: sgh0201a17a7a16.tab

description: :unav
DOI: 10.48527/rxsati/b5pihd
title: sgh0201a8c87da4.tab

description: :unav
DOI: 10.48527/rxsati/dqvwld
title: sgh0201e9248493.tab

description: :unav
DOI: 10.48527/rxsati/a8uckk
title: sgh020149c615c5.tab

description: :unav
DOI: 10.48527/rxsati/fki7vr
title: sgh020125bce03a.tab

description: :unav
DOI: 10.48527/rxsati/oi6upm
title: sgh02018fe9be2c.tab

description: :unav
DOI: 10.48527/rxsati/nu71xu
title: sgh020177a7a91d.tab

description: :unav
DOI: 10.48527/rxsati/ica8s1
title: sgh0201b9b7d045.tab

description: :unav
DOI: 10.48527/rxsati/krxog1
title: sgh02019d93db3f.tab

description: :unav
DOI: 10.48527/rxsati/yjodcz
title: sgh02015d5c61cc.tab

description: :unav
DOI: 10.48527/rxsati/vzqkqa
title: sgh020102d29c86.tab

description: :unav
DOI: 10.48527/rxsati/eqhorr
title: sgh020114a6a800.tab

description: :unav
DOI: 10.48527/rxsati/mt7xpm
title: sgh0201f6cb55ed.tab

description: :unav
DOI: 10.48527/rxsati/kli96o
title: README.md

description: :unav
DOI: 10.48527/rxsati
title: Home comfort dataset

description: This dataset was collected as part of the Smart Green Homes (SGH) project. The project aimed to develop integrated product and technology solutions for households, raising standards of comfort, safety, and user satisfaction to a new level and, at the same time, respond to the problems of sustainability of the planet, increasing energy efficiency and reducing the emission of gaseous pollutants and the consumption of water. This specific dataset was collected from a set of volunteers. The dataset is comprised of 13 Comma-Separated Values (CSV) files, each one containing the logs associated with each tenant. The name of each file contains the respective tenant identification. Each file is divided into 2 columns: the date and the information. The first line has the purpose of naming each of them name and info, respectively, for processing purposes. For more details regarding the structure of the dataset, please check the README.md
DOI: 10.6084/m9.figshare.22188193
title: Data_S_Evolutionary Aspects of Selenium Binding Protein 1

description: DS1 - Alighment of SBP Proteins DS2 - TaxIDs (NCBI) of eucaryotic species without SBP homologs DS3 - Protein IDs (UniProt) not previously known as SBP homologs (unexpected) DS4 - Jalview project file (Java executable) containing the alignment of Data_S1 with 43 invariant positions DS5 - Chimera session file (Python executable) with a known SBP structure and highlighted residues (see text)
DOI: 10.6084/m9.figshare.22194610
title: Geographical coordenates and ecological variables

description: Occurrence points of each specimen used in the ecological analyses and values of the environmental variables. <br>
DOI: 10.6084/m9.figshare.22194610.v1
title: Geographical coordenates and ecological variables

description: Occurrence points of each specimen used in the ecological analyses and values of the environmental variables. <br>
DOI: 10.35009/cfccis-8w70
title: Hyperspectral Polarization Grain Size Data Set 2021
DOI: 10.5519/qd.ppagvtdi
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (5467352 records)
DOI: 10.6084/m9.figshare.15052347.v1
title: Metabolic efficiency affects the seminal relationship between pathogen growth rate and virulence - Dataset.xlsx

description: Dataset for the manuscript "<b>Metabolic efficiency affects the seminal relationship between pathogen growth rate and virulence</b>"<b> </b>
DOI: 10.3886/e181581v1-133185
title: Data and Code for: When a Doctor Falls from the Sky: The Impact of Easing Doctor Supply Constraints on Mortality

description: Data and code accompanying the article<br>
DOI: 10.5519/qd.npl5xh49
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (0 records)