Academic Journal
COVIDomic:A multi-modal cloud-based platform for identification of risk factors associated with COVID-19 severity
| العنوان: | COVIDomic:A multi-modal cloud-based platform for identification of risk factors associated with COVID-19 severity |
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| المؤلفون: | Naumov, Vladimir, Putin, Evgeny, Pushkov, Stefan, Kozlova, Ekaterina, Romantsov, Konstantin, Kalashnikov, Alexander, Galkin, Fedor, Tihonova, Nina, Shneyderman, Anastasia, Galkin, Egor, Zinkevich, Arsenii, Cope, Stephanie M., Sethuraman, Ramanathan, Oprea, Tudor I., Pearson, Alexander T., Tay, Savas, Agrawal, Nishant, Dubovenko, Alexey, Vanhaelen, Quentin, Ozerov, Ivan, Aliper, Alex, Izumchenko, Evgeny, Zhavoronkov, Alex |
| المصدر: | Naumov , V , Putin , E , Pushkov , S , Kozlova , E , Romantsov , K , Kalashnikov , A , Galkin , F , Tihonova , N , Shneyderman , A , Galkin , E , Zinkevich , A , Cope , S M , Sethuraman , R , Oprea , T I , Pearson , A T , Tay , S , Agrawal , N , Dubovenko , A , Vanhaelen , Q , Ozerov , I , Aliper , A , Izumchenko , E & Zhavoronkov , A 2021 , ' COVIDomic : .... |
| سنة النشر: | 2021 |
| المجموعة: | University of Copenhagen: Research / Forskning ved Københavns Universitet |
| مصطلحات موضوعية: | RNA, INFECTION, BIOMARKER, ALIGNMENT, PROTEASE, SARS |
| الوصف: | Author summary This article introduces COVIDomic, a new integrative multi-omics online platform designed to facilitate the analysis of the large amount of health data collected from COVID-19 patients. The COVIDomic platform includes a user-friendly interface and provides a set of bioinformatics tools for the analysis of multi-modal metatranscriptomic data to determine the origin of the coronavirus strain and the expected severity of the disease. An analytical workflow includes microbial pathogens community analysis, COVID-19 genetic epidemiology and patient stratification. These features allow studying the presence of common microbial organisms, their antibiotic resistance and the severity of the infection, as well as obtaining insights on the geographical locations from which the strain could have originated. Such openly distributed multi-modal platform will greatly accelerate the ongoing COVID-19 research and improve our readiness to respond to other infectious outbreaks. Coronavirus disease 2019 (COVID-19) is an acute infection of the respiratory tract that emerged in December 2019 in Wuhan, China. It was quickly established that both the symptoms and the disease severity may vary from one case to another and several strains of SARS-CoV-2 have been identified. To gain a better understanding of the wide variety of SARS-CoV-2 strains and their associated symptoms, thousands of SARS-CoV-2 genomes have been sequenced in dozens of countries. In this article, we introduce COVIDomic, a multi-omics online platform designed to facilitate the analysis and interpretation of the large amount of health data collected from patients with COVID-19. The COVIDomic platform provides a comprehensive set of bioinformatic tools for the multi-modal metatranscriptomic data analysis of COVID-19 patients to determine the origin of the coronavirus strain and the expected severity of the disease. An integrative analytical workflow, which includes microbial pathogens community analysis, COVID-19 genetic epidemiology and patient ... |
| نوع الوثيقة: | article in journal/newspaper |
| وصف الملف: | application/pdf |
| اللغة: | English |
| DOI: | 10.1371/journal.pcbi.1009183 |
| الاتاحة: | https://researchprofiles.ku.dk/da/publications/covidomic(488dbbda-1dcb-401f-962e-3872237d13bb).html https://doi.org/10.1371/journal.pcbi.1009183 https://curis.ku.dk/ws/files/275483806/journal.pcbi.1009183.pdf |
| Rights: | info:eu-repo/semantics/openAccess |
| رقم الانضمام: | edsbas.5A09D909 |
| قاعدة البيانات: | BASE |
| DOI: | 10.1371/journal.pcbi.1009183 |
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