Demo Data from EDBT 2026 / reviewers in the wild / expert
Elena A. Vidal
dblp:197/8286
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2017
0000-0002-8208-7327ORCID · reported
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 › functional genomics
gene function prediction |
0.3 | 1 | 2017 | GENIUS: web server to predict local gene networks and key genes for biological functions · Bioinform. 2017 |
Bioinformatics and computational biology › network bioinformatics › biological network analysis › biological network inference
gene network inference |
0.3 | 1 | 2017 | GENIUS: web server to predict local gene networks and key genes for biological functions · Bioinform. 2017 |
Methods — techniques the papers use, named apart from their topics
support vector machine · 0.3machine learning · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2017 | GENIUS: web server to predict local gene networks and key genes for biological functionsabstractSummary: GENIUS is a user-friendly web server that uses a novel machine learning algorithm to infer functional gene networks focused on specific genes and experimental conditions that are relevant to biological functions of interest. These functions may have different levels of complexity, from specific biological processes to complex traits that involve several interacting processes. GENIUS also enriches the network with new genes related to the biological function of interest, with accuracies comparable to highly discriminative Support Vector Machine methods. Availability and Implementation: GENIUS currently supports eight model organisms and is freely available for public use at http://networks.bio.puc.cl/genius . Contact: [email protected]. Supplementary information: Supplementary data are available at Bioinformatics online. Tomas Puelma, Viviana Araus, Javier Canales, Elena A. Vidal, Juan M. Cabello, Alvaro Soto, Rodrigo A. Gutiérrez |
Bioinform. | 4 |