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The currently emerging pathogen SARS-CoV-2 has produced the global pandemic crisis by causing COVID-19. The unique and novel genetic makeup of SARS-CoV-2 has created hurdles in biological research, due to which the potential drug/vaccine candidates have not yet been discovered by the scientific community. Meanwhile, the advantages of bioinformatics in viral research had created a milestone since last few decades. The exploitation of bioinformatics tools and techniques has successfully interpreted this viral genomics architecture. Some major in silico studies involving next-generation sequencing, genome-wide association studies, computer-aided drug design etc. have been effectively applied in COVID-19 research methodologies and discovered novel information on SARS-CoV-2 in several ways. Nowadays the implementation of in silico studies in COVID-19 research has not only sequenced the SARS-CoV-2 genome but also properly analyzed the sequencing errors, evolutionary relationship, genetic variations, putative drug candidates against SARS-CoV-2 viral genes etc. within a very short time period. These would be very needful towards further research on COVID-19 pandemic and essential for vaccine development against SARS-CoV-2 which will save public health.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7744275 | PMC |
http://dx.doi.org/10.1016/j.mgene.2020.100844 | DOI Listing |
J Clin Invest
September 2025
The University of Texas at Austin, Austin, United States of America.
Background: Following SARS-CoV-2 infection, ~10-35% of COVID-19 patients experience long COVID (LC), in which debilitating symptoms persist for at least three months. Elucidating biologic underpinnings of LC could identify therapeutic opportunities.
Methods: We utilized machine learning methods on biologic analytes provided over 12-months after hospital discharge from >500 COVID-19 patients in the IMPACC cohort to identify a multi-omics "recovery factor", trained on patient-reported physical function survey scores.
JAMA Netw Open
September 2025
Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia.
Importance: Long COVID (ie, post-COVID-19 condition) is a substantial public health concern, and its association with health-related social needs, such as food insecurity, remains poorly understood. Identifying modifiable risk factors like food insecurity and interventions like food assistance programs is critical for reducing the health burden of long COVID.
Objective: To investigate the association of food insecurity with long COVID and to assess the modifying factors of Supplemental Nutrition Assistance Program (SNAP) participation and employment status.
JAMA Netw Open
September 2025
Centre de recherche intégrée pour un système apprenant en santé et services sociaux, Centre intégré de santé et de services sociaux de Chaudière-Appalaches, Lévis, Québec, Canada.
Importance: Caregivers of community-dwelling older adults play a protective role in emergency department (ED) care transitions. When the demands of caregiving result in caregiver burden, ED returns can ensue.
Objective: To develop models describing whether caregiver burden is associated with ED revisits and hospital admissions up to 30 days after discharge from an initial ED visit.