Demo Data from EDBT 2026 / reviewers in the wild / expert
Alberto Calderone
dblp:146/3055
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2018
0000-0003-0876-1595ORCID · verified
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author
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 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology
biological data visualization |
0.3 | 1 | 2018 | SPV: a JavaScript Signaling Pathway Visualizer · Bioinform. 2018 |
Bioinformatics and computational biology › biological network › network biology
molecular interaction network |
0.1 | 1 | 2018 | SPV: a JavaScript Signaling Pathway Visualizer · Bioinform. 2018 |
Bioinformatics and computational biology › protein analysis › protein-protein interaction
protein-protein interaction network |
0.1 | 1 | 2018 | SPV: a JavaScript Signaling Pathway Visualizer · Bioinform. 2018 |
Methods — techniques the papers use, named apart from their topics
scalable vector graphics · 0.3javascript · 0.3d3.js · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2018 | SPV: a JavaScript Signaling Pathway VisualizerabstractSummary: The visualization of molecular interactions annotated in web resources is useful to offer to users such information in a clear intuitive layout. These interactions are frequently represented as binary interactions that are laid out in free space where, different entities, cellular compartments and interaction types are hardly distinguishable. Signaling Pathway Visualizer is a free open source JavaScript library, which offers a series of pre-defined elements, compartments and interaction types meant to facilitate the representation of signaling pathways consisting of causal interactions without neglecting simple protein-protein interaction networks. Availability and implementation: Freely available under Apache version 2 license; Source code: https://github.com/Sinnefa/SPV_Signaling_Pathway_Visualizer_v1.0. Language: JavaScript; Web technology: Scalable Vector Graphics; Libraries: D3.js. Alberto Calderone, Gianni Cesareni |
Bioinform. | 1 |