Demo Data from VLDB 2026 / reviewers in the wild / expert
Mikayla Webster
dblp:211/6362
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2018
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Bioinformatics and computational biology · 100% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › network bioinformatics › biological network analysis › network visualization
biological network visualization |
0.3 | 1 | 2018 | Interactive network visualization in Jupyter notebooks: visJS2jupyter · Bioinform. 2018 |
Bioinformatics and computational biology › biological network
network biology |
0.3 | 1 | 2018 | Interactive network visualization in Jupyter notebooks: visJS2jupyter · Bioinform. 2018 |
Methods — techniques the papers use, named apart from their topics
network propagation · 0.3interactive visualization · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2018 | Interactive network visualization in Jupyter notebooks: visJS2jupyterabstractMotivation: Network biology is widely used to elucidate mechanisms of disease and biological processes. The ability to interact with biological networks is important for hypothesis generation and to give researchers an intuitive understanding of the data. We present visJS2jupyter, a tool designed to embed interactive networks in Jupyter notebooks to streamline network analysis and to promote reproducible research. Results: The tool provides functions for performing and visualizing useful network operations in biology, including network overlap, network propagation around a focal set of genes, and co-localization of two sets of seed genes. visJS2jupyter uses the JavaScript library vis.js to create interactive networks displayed within Jupyter notebook cells with features including drag, click, hover, and zoom. We demonstrate the functionality of visJS2jupyter applied to a biological question, by creating a network propagation visualization to prioritize risk-related genes in autism. Availability and implementation: The visJS2jupyter package is distributed under the MIT License. The source code, documentation and installation instructions are freely available on GitHub at https://github.com/ucsd-ccbb/visJS2jupyter. The package can be downloaded at https://pypi.python.org/pypi/visJS2jupyter. Contact: [email protected]. Supplementary information: Supplementary data are available at Bioinformatics online. Sara Brin Rosenthal, Julia Len, Mikayla Webster, Aaron Gary, Amanda Birmingham, Kathleen M. Fisch |
Bioinform. | 3 |