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Reverse transcription (RT)-PCR, the principal diagnostic method applied in the world-wide struggle against COVID-19, is capable of detecting a single molecule of a viral genome. Correctly designed and practiced RT-PCR assays for SARS-CoV-2 should not cross react with similar but distinct viral pathogens, such as the coronaviruses associated with the common cold, and should perform with very high analytical sensitivity. This analytical performance is predicated on the ability of the method to detect the presence of the selected nucleic acid target, without detection of a false positive signal.
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http://dx.doi.org/10.1093/clinchem/hvaa214 | DOI Listing |
Eur Neuropsychopharmacol
August 2025
Department of Statistics and Data Science, Cornell University, Ithaca, NY 14853, USA. Electronic address:
Nutr Res
July 2025
Department of Paediatrics: Child and Youth Health, School of Medicine, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand; Environmental-Occupational Health Sciences and Non-Communicable Diseases Research Center, Research Institute for Health Sciences, Chiang Mai U
Nutr Res
July 2025
Steno Diabetes Center Aarhus, Aarhus University Hospital, Aarhus N, Denmark; Department of Clinical Medicine, Faculty of Health, Aarhus University, Aarhus N, Denmark; Danish National Center for Obesity, Aarhus N, Denmark.
Pediatr Surg Int
July 2025
Department of Pediatric Surgery, Complejo Asistencial Universitario de León, C/Altos de Nava S/N, Castilla y León, 24008, León, Spain.
bioRxiv
June 2025
Department of Statistics, The Ohio State University, Columbus, OH 43210.
Hi-C and single cell Hi-C (scHi-C) data are now routinely generated for studying an array of biological questions of interest, including whole genome chromatin organization to gain a better understanding of the chromosome three-dimensional hierarchical structure: compartments, Topologically Associated Domains (TADs), and long-range interactions. Due to concerns about data quality, especially for scHi-C because of its sparsity, data quality improvement is seen as a necessary step before performing analyses to answer biological questions. As such, methods have been developed accordingly, among them is a set of methods that are "random walk"- based, including random walk with a limited number of steps (RWS) and random walk with restart (RWR).
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