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- Research data . 2021Open AccessAuthors:Schmidl, Ravin Henry;Schmidl, Ravin Henry;Publisher: Zenodo
All of the data used for the construction of the COVID-19 KG. This included identifier mapping from ChEMBl, ChEBi and DrugBank to InChi Keys as well as the mapping from UniProt to Entrez identifiers.
Average popularityAverage popularity In bottom 99%Average influencePopularity: Citation-based measure reflecting the current impact.Average influence In bottom 99%Influence: Citation-based measure reflecting the total impact.add Add to ORCIDPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product. - Research data . 2021Open AccessAuthors:Wyper, Grant M. A.; Fletcher, Eilidh; Grant, Ian; Harding, Oliver; de Haro Moro, Maria Teresa; Stockton, Diane L.; McCartney, Gerry;Wyper, Grant M. A.; Fletcher, Eilidh; Grant, Ian; Harding, Oliver; de Haro Moro, Maria Teresa; Stockton, Diane L.; McCartney, Gerry;Publisher: figshare
Additional file 1.
Average popularityAverage popularity In bottom 99%Average influencePopularity: Citation-based measure reflecting the current impact.Average influence In bottom 99%Influence: Citation-based measure reflecting the total impact.add Add to ORCIDPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product. - Research data . 2020Open AccessAuthors:Zheng, Bo;Zheng, Bo;Publisher: figshare
Changes in China’s monthly PM2.5 emissions by source sector and by province
Average popularityAverage popularity In bottom 99%Average influencePopularity: Citation-based measure reflecting the current impact.Average influence In bottom 99%Influence: Citation-based measure reflecting the total impact.add Add to ORCIDPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product. - Research data . 2022Open Access GermanAuthors:an der Heiden, Matthias;an der Heiden, Matthias;Publisher: Zenodo
Das Nowcasting erstellt eine Schätzung des Verlaufs der Anzahl von bereits erfolgten SARS-CoV-2-Erkrankungsfällen in Deutschland unter Berücksichtigung des Diagnose-, Melde- und Übermittlungsverzugs. Aufbauend auf dem Nowcasting kann eine Schätzung der zeitabhängigen Reproduktionszahl R durchgeführt werden. Die Reproduktionszahl beschreibt, wie viele Menschen eine infizierte Person im Mittel ansteckt. Sie kann nicht alleine als Maß für Wirksamkeit/Notwendigkeit von Maßnahmen herangezogen werden. Wichtig sind außerdem u.a. die absolute Zahl der täglichen Neuinfektionen sowie die Schwere der Erkrankungen. Die absolute Zahl der Neuinfektionen muss klein genug sein, um eine effektive Kontaktpersonennachverfolgung zu ermöglichen und die Kapazitäten von Intensivbetten nicht zu überlasten.
Average popularityAverage popularity In bottom 99%Average influencePopularity: Citation-based measure reflecting the current impact.Average influence In bottom 99%Influence: Citation-based measure reflecting the total impact.add Add to ORCIDPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product. - Research data . 2020Authors:Kate Vyborny;Kate Vyborny;Publisher: American Economic AssociationAverage popularityAverage popularity In bottom 99%Average influencePopularity: Citation-based measure reflecting the current impact.Average influence In bottom 99%Influence: Citation-based measure reflecting the total impact.
add Add to ORCIDPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product. - Research data . 2022Open AccessAuthors:Angeles, Mary Rose; Wanni Arachchige Dona, Sithara; Nguyen, Huong Dieu; Le, Long Khanh-Dao; Hensher, Martin;Angeles, Mary Rose; Wanni Arachchige Dona, Sithara; Nguyen, Huong Dieu; Le, Long Khanh-Dao; Hensher, Martin;Publisher: figshare
Additional file 1.
Average popularityAverage popularity In bottom 99%Average influencePopularity: Citation-based measure reflecting the current impact.Average influence In bottom 99%Influence: Citation-based measure reflecting the total impact.add Add to ORCIDPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product. - Research data . 2021Open Access GermanAuthors:Robert Koch-Institut;Robert Koch-Institut;Publisher: Zenodo
Für die Planung von Maßnahmen zur Eindämmung von COVID-19 kommt der genauen Kenntnis der Eigenschaften von SARS-CoV-2 eine zentrale Bedeutung zu. Eine besondere Rolle spielen in diesem Zusammenhang Mutationen des Virus. Für eine erfolgreiche Eindämmung der Pandemie ist es daher entscheidend, einen detaillierten Überblick über die Ausbreitungsmuster spezifischer SARS-CoV-2-Mutationen zu erhalten und auch neue Mutation frühzeitig zu entdecken.Hierfür stellt das Robert Koch-Institut die Systeme zur bundesweiten molekularen Surveillance bereit. Jedes Labor in Deutschland, das SARS-CoV-2 sequenziert, ist laut der Verordnung zur molekulargenetischen Surveillance des Coronavirus SARS-CoV-2 verpflichtet, dem Robert Koch-Institut die Sequenz- und zugehörige Metadaten zu übermitteln. Technisch erfolgt diese Übermittlung über den Deutschen Elektronischen Sequenzdaten-Hub (DESH).Im Projekt "OSEDA - Offene Sequenzdaten" verpflichtet sich das RKI, die aufgearbeiteten und qualitätskontrollierten Sequenzdaten zusammen mit einer Auswahl von klinisch-epidemiologischen Daten über die öffentlich zugängliche Repositorien des European Nucleotide Archive) und GISAID für weitere Forschungsvorhaben bereitzustellen.
Average popularityAverage popularity In bottom 99%Average influencePopularity: Citation-based measure reflecting the current impact.Average influence In bottom 99%Influence: Citation-based measure reflecting the total impact.add Add to ORCIDPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product. - Research data . 2022Authors:Cheng, Susan; Figueiredo, Jane;Cheng, Susan; Figueiredo, Jane;
doi: 10.21430/m36er193hy
Publisher: ImmPortWe report data on uptake and perspectives on SARS-CoV-2 vaccination and postvaccination adverse reactions in 208 recently diagnosed patients with cancer (median age 63 years, 52.4% women, 33.2% non-White minorities, Table 1 ) at a large healthcare system in Los Angeles spanning the timeline from limited vaccine availability to broader dissemination (November 2020 to July 2021). Vaccine hesitancy and perspectives were measured using a modified version of the World Health Organization Vaccine Hesitancy Scale (Supplementary Material, available at https://doi.org/10.1016/j.annonc.2021.10.005).3 A self-administered symptoms questionnaire was given to vaccinated recipients after dose 1 (D1) and D2 for messenger RNA (mRNA) SARS-CoV-2 vaccines. Electronic medical records provided correlative clinical information. Chi-square tests were used to assess differences for categorical variables and a Wilcoxon rank-sum test for continuous variables (Stata v. 15.1). All tests were two-sided and considered statistically significant at P < 0.05.
Average popularityAverage popularity In bottom 99%Average influencePopularity: Citation-based measure reflecting the current impact.Average influence In bottom 99%Influence: Citation-based measure reflecting the total impact.add Add to ORCIDPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product. - Research data . 2020
This dataset includes CSV files which contain the tweet IDs. The tweets have been collected by the model deployed here at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for corona virus-related tweets, using filters: language “en”, and keywords “corona”, "coronavirus", "covid", "covid19" and variants of "sarscov2". As per the Twitter Developer Policy, it is not possible for me to provide information other than the Tweet IDs (this dataset has been completely re-designed on March 20, 2020, to comply with data sharing policies set by Twitter). Note: This dataset should be solely used for non-commercial research purpose (ignore every other LICENSE category given in this page).If you're looking for geolocation-based COVID-19 sentiment data: http://dx.doi.org/10.21227/fpsb-jz61 +-------------------------------+
add Add to ORCIDPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product. - Authors:Jennifer K Quint;Jennifer K Quint;Publisher: Faculty Opinions LtdAverage popularityAverage popularity In bottom 99%Average influencePopularity: Citation-based measure reflecting the current impact.Average influence In bottom 99%Influence: Citation-based measure reflecting the total impact.
add Add to ORCIDPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.
64,596 Research products, page 1 of 6,460
Loading
- Research data . 2021Open AccessAuthors:Schmidl, Ravin Henry;Schmidl, Ravin Henry;Publisher: Zenodo
All of the data used for the construction of the COVID-19 KG. This included identifier mapping from ChEMBl, ChEBi and DrugBank to InChi Keys as well as the mapping from UniProt to Entrez identifiers.
Average popularityAverage popularity In bottom 99%Average influencePopularity: Citation-based measure reflecting the current impact.Average influence In bottom 99%Influence: Citation-based measure reflecting the total impact.add Add to ORCIDPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product. - Research data . 2021Open AccessAuthors:Wyper, Grant M. A.; Fletcher, Eilidh; Grant, Ian; Harding, Oliver; de Haro Moro, Maria Teresa; Stockton, Diane L.; McCartney, Gerry;Wyper, Grant M. A.; Fletcher, Eilidh; Grant, Ian; Harding, Oliver; de Haro Moro, Maria Teresa; Stockton, Diane L.; McCartney, Gerry;Publisher: figshare
Additional file 1.
Average popularityAverage popularity In bottom 99%Average influencePopularity: Citation-based measure reflecting the current impact.Average influence In bottom 99%Influence: Citation-based measure reflecting the total impact.add Add to ORCIDPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product. - Research data . 2020Open AccessAuthors:Zheng, Bo;Zheng, Bo;Publisher: figshare
Changes in China’s monthly PM2.5 emissions by source sector and by province
Average popularityAverage popularity In bottom 99%Average influencePopularity: Citation-based measure reflecting the current impact.Average influence In bottom 99%Influence: Citation-based measure reflecting the total impact.add Add to ORCIDPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product. - Research data . 2022Open Access GermanAuthors:an der Heiden, Matthias;an der Heiden, Matthias;Publisher: Zenodo
Das Nowcasting erstellt eine Schätzung des Verlaufs der Anzahl von bereits erfolgten SARS-CoV-2-Erkrankungsfällen in Deutschland unter Berücksichtigung des Diagnose-, Melde- und Übermittlungsverzugs. Aufbauend auf dem Nowcasting kann eine Schätzung der zeitabhängigen Reproduktionszahl R durchgeführt werden. Die Reproduktionszahl beschreibt, wie viele Menschen eine infizierte Person im Mittel ansteckt. Sie kann nicht alleine als Maß für Wirksamkeit/Notwendigkeit von Maßnahmen herangezogen werden. Wichtig sind außerdem u.a. die absolute Zahl der täglichen Neuinfektionen sowie die Schwere der Erkrankungen. Die absolute Zahl der Neuinfektionen muss klein genug sein, um eine effektive Kontaktpersonennachverfolgung zu ermöglichen und die Kapazitäten von Intensivbetten nicht zu überlasten.
Average popularityAverage popularity In bottom 99%Average influencePopularity: Citation-based measure reflecting the current impact.Average influence In bottom 99%Influence: Citation-based measure reflecting the total impact.add Add to ORCIDPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product. - Research data . 2020Authors:Kate Vyborny;Kate Vyborny;Publisher: American Economic AssociationAverage popularityAverage popularity In bottom 99%Average influencePopularity: Citation-based measure reflecting the current impact.Average influence In bottom 99%Influence: Citation-based measure reflecting the total impact.
add Add to ORCIDPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product. - Research data . 2022Open AccessAuthors:Angeles, Mary Rose; Wanni Arachchige Dona, Sithara; Nguyen, Huong Dieu; Le, Long Khanh-Dao; Hensher, Martin;Angeles, Mary Rose; Wanni Arachchige Dona, Sithara; Nguyen, Huong Dieu; Le, Long Khanh-Dao; Hensher, Martin;Publisher: figshare
Additional file 1.
Average popularityAverage popularity In bottom 99%Average influencePopularity: Citation-based measure reflecting the current impact.Average influence In bottom 99%Influence: Citation-based measure reflecting the total impact.add Add to ORCIDPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product. - Research data . 2021Open Access GermanAuthors:Robert Koch-Institut;Robert Koch-Institut;Publisher: Zenodo
Für die Planung von Maßnahmen zur Eindämmung von COVID-19 kommt der genauen Kenntnis der Eigenschaften von SARS-CoV-2 eine zentrale Bedeutung zu. Eine besondere Rolle spielen in diesem Zusammenhang Mutationen des Virus. Für eine erfolgreiche Eindämmung der Pandemie ist es daher entscheidend, einen detaillierten Überblick über die Ausbreitungsmuster spezifischer SARS-CoV-2-Mutationen zu erhalten und auch neue Mutation frühzeitig zu entdecken.Hierfür stellt das Robert Koch-Institut die Systeme zur bundesweiten molekularen Surveillance bereit. Jedes Labor in Deutschland, das SARS-CoV-2 sequenziert, ist laut der Verordnung zur molekulargenetischen Surveillance des Coronavirus SARS-CoV-2 verpflichtet, dem Robert Koch-Institut die Sequenz- und zugehörige Metadaten zu übermitteln. Technisch erfolgt diese Übermittlung über den Deutschen Elektronischen Sequenzdaten-Hub (DESH).Im Projekt "OSEDA - Offene Sequenzdaten" verpflichtet sich das RKI, die aufgearbeiteten und qualitätskontrollierten Sequenzdaten zusammen mit einer Auswahl von klinisch-epidemiologischen Daten über die öffentlich zugängliche Repositorien des European Nucleotide Archive) und GISAID für weitere Forschungsvorhaben bereitzustellen.
Average popularityAverage popularity In bottom 99%Average influencePopularity: Citation-based measure reflecting the current impact.Average influence In bottom 99%Influence: Citation-based measure reflecting the total impact.add Add to ORCIDPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product. - Research data . 2022Authors:Cheng, Susan; Figueiredo, Jane;Cheng, Susan; Figueiredo, Jane;
doi: 10.21430/m36er193hy
Publisher: ImmPortWe report data on uptake and perspectives on SARS-CoV-2 vaccination and postvaccination adverse reactions in 208 recently diagnosed patients with cancer (median age 63 years, 52.4% women, 33.2% non-White minorities, Table 1 ) at a large healthcare system in Los Angeles spanning the timeline from limited vaccine availability to broader dissemination (November 2020 to July 2021). Vaccine hesitancy and perspectives were measured using a modified version of the World Health Organization Vaccine Hesitancy Scale (Supplementary Material, available at https://doi.org/10.1016/j.annonc.2021.10.005).3 A self-administered symptoms questionnaire was given to vaccinated recipients after dose 1 (D1) and D2 for messenger RNA (mRNA) SARS-CoV-2 vaccines. Electronic medical records provided correlative clinical information. Chi-square tests were used to assess differences for categorical variables and a Wilcoxon rank-sum test for continuous variables (Stata v. 15.1). All tests were two-sided and considered statistically significant at P < 0.05.
Average popularityAverage popularity In bottom 99%Average influencePopularity: Citation-based measure reflecting the current impact.Average influence In bottom 99%Influence: Citation-based measure reflecting the total impact.add Add to ORCIDPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product. - Research data . 2020
This dataset includes CSV files which contain the tweet IDs. The tweets have been collected by the model deployed here at https://live.rlamsal.com.np. The model monitors the real-time Twitter feed for corona virus-related tweets, using filters: language “en”, and keywords “corona”, "coronavirus", "covid", "covid19" and variants of "sarscov2". As per the Twitter Developer Policy, it is not possible for me to provide information other than the Tweet IDs (this dataset has been completely re-designed on March 20, 2020, to comply with data sharing policies set by Twitter). Note: This dataset should be solely used for non-commercial research purpose (ignore every other LICENSE category given in this page).If you're looking for geolocation-based COVID-19 sentiment data: http://dx.doi.org/10.21227/fpsb-jz61 +-------------------------------+
add Add to ORCIDPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product. - Authors:Jennifer K Quint;Jennifer K Quint;Publisher: Faculty Opinions LtdAverage popularityAverage popularity In bottom 99%Average influencePopularity: Citation-based measure reflecting the current impact.Average influence In bottom 99%Influence: Citation-based measure reflecting the total impact.
add Add to ORCIDPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.