Summary
Detection and analysis of viral genomes with Nanopore sequencing has shown great promise in the surveillance of pathogen outbreaks. However, the number of virus detection pipelines supporting Nanopore sequencing is very limited. Here, we present VirPipe, a new pipeline for the detection of viral genomes from Nanopore or Illumina sequencing input featuring streamlined installation and customization.
Availability
VirPipe Source code and documentation are freely available for download at https://github.com/KijinKims/VirPipe, implemented in Python and Nextflow.
Supplementary information
Supplementary data are available at Bioinformatics online.
As computing technology becomes more pervasive and mobile services are deployed, ubiquitous applications will need flexible access control mechanisms and more suitable access control decisions. Despite the recent advances in access control approaches applicable to ubiquitous applications, there remain issues that impede the development of effective access control for ubiquitous applications. Amongst them are the lack of contextbased models for access control, and reliance on identity or capability-based access control schemes. In this paper, we propose intelligent system using a neural network algorithm for ubiquitous applications, which extends the role based access control with context constraints. Also we apply a neural network algorithm for making access decisions.
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