SUMMARY: Treenome Browser is a web browser tool to interactively visualize millions of genomes alongside huge phylogenetic trees. AVAILABILITY AND IMPLEMENTATION: Treenome Browser for SARS-CoV-2 can be accessed at cov2tree.org, or at taxonium.org for user-provided trees. Source code and documentation are available at github.com/theosanderson/taxonium and docs.taxonium.org/en/latest/treenome.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MOTIVATION: Phylogenetic tree optimization is necessary for precise analysis of evolutionary and transmission dynamics, but existing tools are inadequate for handling the scale and pace of data produced during the coronavirus disease 2019 (COVID-19) pandemic. One transformative approach, online phylogenetics, aims to incrementally add samples to an ever-growing phylogeny, but there are no previously existing approaches that can efficiently optimize this vast phylogeny under the time constraints of the pandemic. RESULTS: Here, we present matOptimize, a fast and memory-efficient phylogenetic tree optimization tool based on parsimony that can be parallelized across multiple CPU threads and nodes, and provides orders of magnitude improvement in runtime and peak memory usage compared to existing state-of-the-art methods. We have developed this method particularly to address the pressing need during the COVID-19 pandemic for daily maintenance and optimization of a comprehensive SARS-CoV-2 phylogeny. matOptimize is currently helping refine on a daily basis possibly the largest-ever phylogenetic tree, containing millions of SARS-CoV-2 sequences. AVAILABILITY AND IMPLEMENTATION: The matOptimize code is freely available as part of the UShER package (https://github.com/yatisht/usher) and can also be installed via bioconda (https://bioconda.github.io/recipes/usher/README.html). All scripts we used to perform the experiments in this manuscript are available at https://github.com/yceh/matOptimize-experiments. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The internet is about to change from a pure network of computers to a network of more or less intelligent devices, the computer being just one of them. Examples of this change are the concepts of smart applications like smart homes, smart traffic control and guidance systems, smart power grids, or smart buildings. These systems require among others a high degree of robustness, reliability, scalability, safety, and security. In this paper, we concentrate on the data exchange and management aspect and introduce a security concept for scalable and easy-to-use Generic Data Services, called SeGDS. It covers application scenarios from embedded field devices for data acquisition to large-scale generic data applications and data management. The concept is based largely on proven standard enterprise hardware and standard solutions. As a first application, we report about transport and management of mass data originating from high-resolution electrical data devices, which measure parameters of the electrical grid with a high sample rate. The shown solution is intended to be a contribution to concepts of a secure, flexible, but comparably inexpensive management of large amounts of data coming from modern smart power grids or other comparable smart applications.