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Start Over Author "Caruso, Francesca P." Topic covid-19
2 results on '"Caruso, Francesca P."'

1. A review of COVID-19 biomarkers and drug targets: resources and tools.

Author

Caruso, Francesca P, Scala, Giovanni, Cerulo, Luigi, and Ceccarelli, Michele

Subjects
*COVID-19, *BIOMARKERS, *VACCINE development, *MACHINE learning, *ARTIFICIAL intelligence
Abstract

The stratification of patients at risk of progression of COVID-19 and their molecular characterization is of extreme importance to optimize treatment and to identify therapeutic options. The bioinformatics community has responded to the outbreak emergency with a set of tools and resource to identify biomarkers and drug targets that we review here. Starting from a consolidated corpus of 27 570 papers, we adopt latent Dirichlet analysis to extract relevant topics and select those associated with computational methods for biomarker identification and drug repurposing. The selected topics span from machine learning and artificial intelligence for disease characterization to vaccine development and to therapeutic target identification. Although the way to go for the ultimate defeat of the pandemic is still long, the amount of knowledge, data and tools generated so far constitutes an unprecedented example of global cooperation to this threat. [ABSTRACT FROM AUTHOR]

Published
2021
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2. A review of COVID-19 biomarkers and drug targets: resources and tools

Author

Giovanni Scala, Michele Ceccarelli, Luigi Cerulo, Francesca Pia Caruso, Caruso, Francesca P, Scala, Giovanni, Cerulo, Luigi, and Ceccarelli, Michele

Subjects
Biomarker identification, Drug, AcademicSubjects/SCI01060, Coronavirus disease 2019 (COVID-19), Computer science, media_common.quotation_subject, MEDLINE, Disease, Antiviral Agents, Machine Learning, 03 medical and health sciences, Drug Delivery Systems, 0302 clinical medicine, Resource (project management), Humans, Molecular Biology, 030304 developmental biology, media_common, 0303 health sciences, SARS-CoV-2, Drug Repositioning, COVID-19, Articles, Data science, COVID-19 Drug Treatment, Drug repositioning, 030220 oncology & carcinogenesis, Identification (biology), Biomarkers, Information Systems
Abstract

The stratification of patients at risk of progression of COVID-19 and their molecular characterization is of extreme importance to optimize treatment and to identify therapeutic options. The bioinformatics community has responded to the outbreak emergency with a set of tools and resource to identify biomarkers and drug targets that we review here. Starting from a consolidated corpus of 27 570 papers, we adopt latent Dirichlet analysis to extract relevant topics and select those associated with computational methods for biomarker identification and drug repurposing. The selected topics span from machine learning and artificial intelligence for disease characterization to vaccine development and to therapeutic target identification. Although the way to go for the ultimate defeat of the pandemic is still long, the amount of knowledge, data and tools generated so far constitutes an unprecedented example of global cooperation to this threat.

Published
2020

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