2 research outputs found

    SARS-CoV-2 Wastewater Genomic Surveillance: Approaches, Challenges, and Opportunities

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    During the SARS-CoV-2 pandemic, wastewater-based genomic surveillance (WWGS) emerged as an efficient viral surveillance tool that takes into account asymptomatic cases and can identify known and novel mutations and offers the opportunity to assign known virus lineages based on the detected mutations profiles. WWGS can also hint towards novel or cryptic lineages, but it is difficult to clearly identify and define novel lineages from wastewater (WW) alone. While WWGS has significant advantages in monitoring SARS-CoV-2 viral spread, technical challenges remain, including poor sequencing coverage and quality due to viral RNA degradation. As a result, the viral RNAs in wastewater have low concentrations and are often fragmented, making sequencing difficult. WWGS analysis requires advanced computational tools that are yet to be developed and benchmarked. The existing bioinformatics tools used to analyze wastewater sequencing data are often based on previously developed methods for quantifying the expression of transcripts or viral diversity. Those methods were not developed for wastewater sequencing data specifically, and are not optimized to address unique challenges associated with wastewater. While specialized tools for analysis of wastewater sequencing data have also been developed recently, it remains to be seen how they will perform given the ongoing evolution of SARS-CoV-2 and the decline in testing and patient-based genomic surveillance. Here, we discuss opportunities and challenges associated with WWGS, including sample preparation, sequencing technology, and bioinformatics methods.Comment: V Munteanu and M Saldana contributed equally to this work A Smith and S Mangul jointly supervised this work For correspondence: [email protected]

    Architecting software concurrency

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    Nowadays, the majority of software systems are inherently concurrent. Anyway, internal and external concurrent activities increase the complexity of systems' behavior. Adequate architecting can significantly decrease implementation errors. This work is motivated by the desire to understand how concurrency can constrain or influence software architecting. As a result, in the paper a methodological architecting framework applied for systems with "concurrency-intensive architecture" is described. This special term is defined to emphasize architectures, in which concurrent interactions are crucial. Also in the paper potential models for each phase of architecting framework are indicated
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