Name
Abstract | ||
|---|---|---|
Networks have been an excellent framework for modeling complex biological information, but the methodological details of network-based tools are often described for a technical audience. We have developed Graphery, an interactive tutorial webserver that illustrates foundational graph concepts frequently used in network-based methods. Each tutorial describes a graph concept along with executable Python code that can be interactively run on a graph. Users navigate each tutorial using their choice of real-world biological networks that highlight the diverse applications of network algorithms. Graphery also allows users to modify the code within each tutorial or write new programs, which all can be executed without requiring an account. 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. GRAPHERY is available at https://graphery.reedcompbio.org/. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1093/nar/gkab420 | NUCLEIC ACIDS RESEARCH |
DocType | Volume | Issue |
Journal | 49 | W1 |
ISSN | Citations | PageRank |
0305-1048 | 0 | 0.34 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Heyuan Zeng | 1 | 0 | 0.34 |
| Jinbiao Zhang | 2 | 0 | 0.34 |
| Gabriel A. Preising | 3 | 0 | 0.34 |
| Tobias Rubel | 4 | 0 | 0.34 |
| Pramesh Singh | 5 | 0 | 0.34 |
| Anna Ritz | 6 | 0 | 0.34 |