  Networks provide a meaningful way to represent and analyze complex biological
information, but the methodological details of network-based tools are often
described for a technical audience. Graphery is a hands-on tutorial webserver
designed to help biological researchers understand the fundamental concepts
behind commonly-used graph algorithms. Each tutorial describes a graph concept
along with executable Python code that visualizes the concept in a code view
and a graph view. Graphery tutorials help researchers understand graph
statistics (such as degree distribution and network modularity) and classic
graph algorithms (such as shortest paths and random walks). Users navigate each
tutorial using their choice of real-world biological networks, ranging in scale
from molecular interaction graphs to ecological networks. Graphery also allows
users to modify the code within each tutorial or write new programs, which all
can be executed without requiring an account. Discipline-focused tutorials will
be essential to help researchers interpret their biological data. Graphery
accepts ideas for new tutorials and datasets that will be shaped by both
computational and biological researchers, growing into a community-contributed
learning platform. Availability: Graphery is available at
https://graphery.reedcompbio.org/.
