Cluster Attention for Graph Machine Learning

arXiv:2604.07492v1 Announce Type: cross Abstract: Message Passing Neural Networks have recently become the most popular approach to graph machine learning tasks; however, their receptive field

Long-read sequencing has shown a rapid technological development during the last years. It has been established as the standard method for the sequencing of plant genomes and has also gained importance for full plasmid sequencing. As Sanger sequencing has a limited read length of about 1 kb, long read sequencing offers a great advantage, as the full plasmid can be sequenced in one read. Here, we present a cost-effective workflow to sequence full plasmids and compare the results against an expectation. The per plasmid cost of this workflow is determined by the number of plasmids investigated simultaneously, but can be lower than the price of a single Sanger sequencing reaction. We developed a workflow for automatic data processing, which allows us to complete sequencing and data analysis within a day.

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