Advanced search in Research products
Research products
arrow_drop_down
Searching FieldsTerms
Any field
arrow_drop_down
includes
arrow_drop_down
Include:
The following results are related to COVID-19. Are you interested to view more results? Visit OpenAIRE - Explore.
410 Research products, page 1 of 41

  • COVID-19
  • Research data
  • Other research products
  • 2013-2022
  • European Commission
  • EU

10
arrow_drop_down
Relevance
arrow_drop_down
  • Authors: 
    Dae-Kyum Kim; Knapp, Jennifer; Kuang, Da; Chawla, Aditya; Cassonnet, Patricia; Hunsang Lee; Dayag Sheykhkarimli; Payman Samavarchi-Tehrani; Abdouni, Hala; Ashyad Rayhan; +10 more
    Publisher: GSA Journals
    Project: EC | PREPARE (602525), CIHR

    Supplementary tables for "A comprehensive, flexible collection of SARS-CoV-2 coding regions"

  • Open Access
    Authors: 
    Bonfante, Francesco; Mazzetto, Eva; Zanardello, Claudia; Fortin, Andrea; Gobbo, Federica; Maniero, Silvia; Bigolaro, Michela; Davidson, Irit; Haddas, Ruth; Cattoli, Giovanni; +1 more
    Publisher: figshare
    Project: EC | ANIHWA (291815)

    Additional file 1. Tracheal and cloacal shedding of virus RNA of birds, in experiment 2. Shedding is expressed as both RRT-PCR Ct individual values and means ± standard deviations. Statistical was set at a P

  • Open Access
    Authors: 
    Bardi, Alessia; Kuchma, Iryna; Brobov, Evgeny; Truccolo, Ivana; Monteiro, Elizabete; Casalegno, Carlotta; Clary, Erin; Romanowski, Andrew; Pavone, Gina; Artini, Michele; +19 more
    Countries: Italy, Germany
    Project: EC | OpenAIRE-Advance (777541), EC | OpenAIRE Nexus (101017452)

    This dump provides access to the metadata records of publications, research data, software and projects that may be relevant to the Corona Virus Disease (COVID-19) fight. The dump contains records of the OpenAIRE COVID-19 Gateway, identified via full-text mining and inference techniques applied to the OpenAIRE Research Graph. The Graph is one of the largest Open Access collections of metadata records and links between publications, datasets, software, projects, funders, and organizations, aggregating 12,000+ scientific data sources world-wide, among which the Covid-19 data sources Zenodo COVID-19 Community, WHO (World Health Organization), BIP! FInder for COVID-19, Protein Data Bank, Dimensions, scienceOpen, and RSNA. The dump consists of a tar archive containing gzip files with one json per line. Each json is compliant to the schema available at https://doi.org/10.5281/zenodo.4723499.

  • Open Access
    Authors: 
    Aschenbrenner, Anna C.; Mouktaroudi, Maria; Krämer, Benjamin; Oestreich, Marie; Antonakos, Nikolaos; Nuesch-Germano, Melanie; Gkizeli, Konstantina; Bonaguro, Lorenzo; Reusch, Nico; Baßler, Kevin; +45 more
    Publisher: figshare
    Project: EC | TRAIN-OLD (833247), EC | SYSCID (733100)

    Additional file 10: Table S9. Predicted drugs.

  • Open Access
    Authors: 
    Carr, Ewan; Bendayan, Rebecca; Bean, Daniel; Stammers, Matt; Wenjuan Wang; Huayu Zhang; Searle, Thomas; Zeljko Kraljevic; Shek, Anthony; Phan, Hang T. T.; +38 more
    Publisher: figshare
    Project: EC | BigData Heart (116074), WT | Human Immune Response Var... (207511), UKRI | Deriving an actionable pa... (MR/S004149/1), UKRI | Using Knowledge Graph Lea... (MR/S00310X/1), UKRI | Semantic-based secure inf... (MR/S003991/1), EC | NanoCommons (731032)

    Additional file 5: Figure S1. Calibration (logistic and LOESS curves) of supplemented NEWS2 model for 3-day ICU/death model at validation sites.

  • Open Access
    Authors: 
    Laoudias, Christos;
    Publisher: Zenodo
    Project: EC | KIOS CoE (739551)

    In late 2019, Covid-19 emerged and was soon declared a pandemic causing until now a massive health disruption and a huge impact on the global economy. Several governments around the world are still forced to take containment measures to curb the spread of the virus including partial or full lockdowns. At the same time, they rely heavily on human resources to perform manual Contact Tracing (CT) for alerting known contacts of the confirmed cases and breaking the infection chains early enough. However, CT does not scale well when the cases increase exponentially, due to the limited capacity of national public health authorities, and cannot identify possible hidden infections due to random encounters with strangers in crowded spaces such as restaurants, bars, theaters, public transportation, etc. To this end, Digital Contact Tracing (DCT) is becoming increasingly popular to enhance and empower CT, enabling automatic and faster identification and notification of exposed users. This presentation will first overview the different generations of DCT solutions from the privacy-invasive use of subscriber location data provided by cellular operators, to location monitoring mobile apps on GPS-equipped smartphones, to privacy-preserving mobile apps based on proximity sensing through Bluetooth. It will discuss the findings of recent studies with regards to the effectiveness of DCT and debate whether it has been ��� or has the potential to become ��� a game changer. Finally, it will outline the latest developments and trends in this active research field that are of interest to the IPIN community including presence tracing that aims to notify anonymously those users that have been in the same place (especially indoors) with an infected user, without necessarily satisfying the proximity constraint. Keynote @ 2021 International Conference on Indoor Positioning and Indoor Navigation.

  • Open Access English
    Authors: 
    Luca Fontanesi; Samuele Bovo; Giuseppina Schiavo; Valerio Joe Utzeri;
    Publisher: Zenodo
    Project: EC | EOSCsecretariat.eu (831644)

    VirAnimalOne is a project focused on large scale mining of publicly deposited genomic and transcriptomic datasets available from ENA/SRA and derived from pets, livestock and wild animal species: to identify unexpected coronavirus sequences; to mine the host animal genomes for potential variants that might confer resistance or susceptibility to SARS-CoV-2 and other coronaviruses known to infect both humans and animals; to phylogenetically and structurally evaluate host receptor conformations and infer potential animal susceptibility to coronavirus infections, with particular attention for SARS-Cov-2. Here, we report the pipeline, preliminary datasets and results produced in this project and related to the VirAnimalOne Technical Report: Technical_Report_VirAnimalOne_Pipeline. It reports and describes the bioinformatic pipeline used for the mining of the omics datasets. Tables S1-S6. Genome datasets used for mining activities. Table S7. List of host genes involved in coronavirus infection and used for mining polymorphisms in the host genome using the retrieved datasets. Table S8-S13. List of annotated variants in the selected host genes involved in coronavirus infection. Tables S14-S10. Viral sequences identified in the next-generation sequencing datasets generated from the selected domestic species. Warning: Please, check for updated versions as data can present some inaccuracies. Fundings: EOSCsecretariat.eu has received funding from the European Union's Horizon Programme call H2020-INFRAEOSC-05-2018-2019, grant Agreement number 831644.

  • Research data . 2020
    Open Access
    Authors: 
    Bergs, Rolf;
    Publisher: Mendeley
    Project: EC | ROBUST (727988)

    Dataset for the spatial econometric analysis of the change of greenhouse gas emissions during the Covid-19 pandemic (March-April 2020) for Southern Germany

  • Open Access English
    Authors: 
    Lalas, Dimitri; Gakis, Nikolaos; Mirasgedis, Sebastian; Georgopoulou, Elena; Sarafidis, Yannis; Doukas, Haris;
    Publisher: Zenodo
    Project: EC | PARIS REINFORCE (820846)

    This dataset contains the underlying data for the following publication: Lalas, D., Gakis, N., Mirasgedis, S., Georgopoulou, E., Sarafidis, Y., & Doukas, H. (2021). Energy and GHG Emissions Aspects of the COVID Impact in Greece. Energies, 14(7), 1955. https://doi.org/10.3390/en14071955.

  • Open Access
    Authors: 
    Kooistra, Emma J.; Waalders, Nicole J. B.; Grondman, Inge; Janssen, Nico A. F.; Nooijer, Aline H. De; Netea, Mihai G.; Veerdonk, Frank L. Van De; Ewalds, Esther; Hoeven, Johannes G. Van Der; Kox, Matthijs; +1 more
    Publisher: figshare
    Project: EC | TRAIN-OLD (833247)

    Additional file 4: Figure 2. Description of data: Use of medication. Differences of use of (a) corticosteroids, (b) remdesivir, and (c) chloroquine between anakinra group and control group during 10 days before and 10 days after alignment day (day 0). P values were calculated using Fisher’s exact tests.

Advanced search in Research products
Research products
arrow_drop_down
Searching FieldsTerms
Any field
arrow_drop_down
includes
arrow_drop_down
Include:
The following results are related to COVID-19. Are you interested to view more results? Visit OpenAIRE - Explore.
410 Research products, page 1 of 41
  • Authors: 
    Dae-Kyum Kim; Knapp, Jennifer; Kuang, Da; Chawla, Aditya; Cassonnet, Patricia; Hunsang Lee; Dayag Sheykhkarimli; Payman Samavarchi-Tehrani; Abdouni, Hala; Ashyad Rayhan; +10 more
    Publisher: GSA Journals
    Project: EC | PREPARE (602525), CIHR

    Supplementary tables for "A comprehensive, flexible collection of SARS-CoV-2 coding regions"

  • Open Access
    Authors: 
    Bonfante, Francesco; Mazzetto, Eva; Zanardello, Claudia; Fortin, Andrea; Gobbo, Federica; Maniero, Silvia; Bigolaro, Michela; Davidson, Irit; Haddas, Ruth; Cattoli, Giovanni; +1 more
    Publisher: figshare
    Project: EC | ANIHWA (291815)

    Additional file 1. Tracheal and cloacal shedding of virus RNA of birds, in experiment 2. Shedding is expressed as both RRT-PCR Ct individual values and means ± standard deviations. Statistical was set at a P

  • Open Access
    Authors: 
    Bardi, Alessia; Kuchma, Iryna; Brobov, Evgeny; Truccolo, Ivana; Monteiro, Elizabete; Casalegno, Carlotta; Clary, Erin; Romanowski, Andrew; Pavone, Gina; Artini, Michele; +19 more
    Countries: Italy, Germany
    Project: EC | OpenAIRE-Advance (777541), EC | OpenAIRE Nexus (101017452)

    This dump provides access to the metadata records of publications, research data, software and projects that may be relevant to the Corona Virus Disease (COVID-19) fight. The dump contains records of the OpenAIRE COVID-19 Gateway, identified via full-text mining and inference techniques applied to the OpenAIRE Research Graph. The Graph is one of the largest Open Access collections of metadata records and links between publications, datasets, software, projects, funders, and organizations, aggregating 12,000+ scientific data sources world-wide, among which the Covid-19 data sources Zenodo COVID-19 Community, WHO (World Health Organization), BIP! FInder for COVID-19, Protein Data Bank, Dimensions, scienceOpen, and RSNA. The dump consists of a tar archive containing gzip files with one json per line. Each json is compliant to the schema available at https://doi.org/10.5281/zenodo.4723499.

  • Open Access
    Authors: 
    Aschenbrenner, Anna C.; Mouktaroudi, Maria; Krämer, Benjamin; Oestreich, Marie; Antonakos, Nikolaos; Nuesch-Germano, Melanie; Gkizeli, Konstantina; Bonaguro, Lorenzo; Reusch, Nico; Baßler, Kevin; +45 more
    Publisher: figshare
    Project: EC | TRAIN-OLD (833247), EC | SYSCID (733100)

    Additional file 10: Table S9. Predicted drugs.

  • Open Access
    Authors: 
    Carr, Ewan; Bendayan, Rebecca; Bean, Daniel; Stammers, Matt; Wenjuan Wang; Huayu Zhang; Searle, Thomas; Zeljko Kraljevic; Shek, Anthony; Phan, Hang T. T.; +38 more
    Publisher: figshare
    Project: EC | BigData Heart (116074), WT | Human Immune Response Var... (207511), UKRI | Deriving an actionable pa... (MR/S004149/1), UKRI | Using Knowledge Graph Lea... (MR/S00310X/1), UKRI | Semantic-based secure inf... (MR/S003991/1), EC | NanoCommons (731032)

    Additional file 5: Figure S1. Calibration (logistic and LOESS curves) of supplemented NEWS2 model for 3-day ICU/death model at validation sites.

  • Open Access
    Authors: 
    Laoudias, Christos;
    Publisher: Zenodo
    Project: EC | KIOS CoE (739551)

    In late 2019, Covid-19 emerged and was soon declared a pandemic causing until now a massive health disruption and a huge impact on the global economy. Several governments around the world are still forced to take containment measures to curb the spread of the virus including partial or full lockdowns. At the same time, they rely heavily on human resources to perform manual Contact Tracing (CT) for alerting known contacts of the confirmed cases and breaking the infection chains early enough. However, CT does not scale well when the cases increase exponentially, due to the limited capacity of national public health authorities, and cannot identify possible hidden infections due to random encounters with strangers in crowded spaces such as restaurants, bars, theaters, public transportation, etc. To this end, Digital Contact Tracing (DCT) is becoming increasingly popular to enhance and empower CT, enabling automatic and faster identification and notification of exposed users. This presentation will first overview the different generations of DCT solutions from the privacy-invasive use of subscriber location data provided by cellular operators, to location monitoring mobile apps on GPS-equipped smartphones, to privacy-preserving mobile apps based on proximity sensing through Bluetooth. It will discuss the findings of recent studies with regards to the effectiveness of DCT and debate whether it has been ��� or has the potential to become ��� a game changer. Finally, it will outline the latest developments and trends in this active research field that are of interest to the IPIN community including presence tracing that aims to notify anonymously those users that have been in the same place (especially indoors) with an infected user, without necessarily satisfying the proximity constraint. Keynote @ 2021 International Conference on Indoor Positioning and Indoor Navigation.

  • Open Access English
    Authors: 
    Luca Fontanesi; Samuele Bovo; Giuseppina Schiavo; Valerio Joe Utzeri;
    Publisher: Zenodo
    Project: EC | EOSCsecretariat.eu (831644)

    VirAnimalOne is a project focused on large scale mining of publicly deposited genomic and transcriptomic datasets available from ENA/SRA and derived from pets, livestock and wild animal species: to identify unexpected coronavirus sequences; to mine the host animal genomes for potential variants that might confer resistance or susceptibility to SARS-CoV-2 and other coronaviruses known to infect both humans and animals; to phylogenetically and structurally evaluate host receptor conformations and infer potential animal susceptibility to coronavirus infections, with particular attention for SARS-Cov-2. Here, we report the pipeline, preliminary datasets and results produced in this project and related to the VirAnimalOne Technical Report: Technical_Report_VirAnimalOne_Pipeline. It reports and describes the bioinformatic pipeline used for the mining of the omics datasets. Tables S1-S6. Genome datasets used for mining activities. Table S7. List of host genes involved in coronavirus infection and used for mining polymorphisms in the host genome using the retrieved datasets. Table S8-S13. List of annotated variants in the selected host genes involved in coronavirus infection. Tables S14-S10. Viral sequences identified in the next-generation sequencing datasets generated from the selected domestic species. Warning: Please, check for updated versions as data can present some inaccuracies. Fundings: EOSCsecretariat.eu has received funding from the European Union's Horizon Programme call H2020-INFRAEOSC-05-2018-2019, grant Agreement number 831644.

  • Research data . 2020
    Open Access
    Authors: 
    Bergs, Rolf;
    Publisher: Mendeley
    Project: EC | ROBUST (727988)

    Dataset for the spatial econometric analysis of the change of greenhouse gas emissions during the Covid-19 pandemic (March-April 2020) for Southern Germany

  • Open Access English
    Authors: 
    Lalas, Dimitri; Gakis, Nikolaos; Mirasgedis, Sebastian; Georgopoulou, Elena; Sarafidis, Yannis; Doukas, Haris;
    Publisher: Zenodo
    Project: EC | PARIS REINFORCE (820846)

    This dataset contains the underlying data for the following publication: Lalas, D., Gakis, N., Mirasgedis, S., Georgopoulou, E., Sarafidis, Y., & Doukas, H. (2021). Energy and GHG Emissions Aspects of the COVID Impact in Greece. Energies, 14(7), 1955. https://doi.org/10.3390/en14071955.

  • Open Access
    Authors: 
    Kooistra, Emma J.; Waalders, Nicole J. B.; Grondman, Inge; Janssen, Nico A. F.; Nooijer, Aline H. De; Netea, Mihai G.; Veerdonk, Frank L. Van De; Ewalds, Esther; Hoeven, Johannes G. Van Der; Kox, Matthijs; +1 more
    Publisher: figshare
    Project: EC | TRAIN-OLD (833247)

    Additional file 4: Figure 2. Description of data: Use of medication. Differences of use of (a) corticosteroids, (b) remdesivir, and (c) chloroquine between anakinra group and control group during 10 days before and 10 days after alignment day (day 0). P values were calculated using Fisher’s exact tests.